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PEER REVIEWED, EVIDENCE-BASED INFORMATION FOR CLINICIANS AND RESEARCHERS IN NEUROSCIENCE

CNS Summit 2023 Abstracts of Poster Presentations

A Message from the Editor

Dear Colleagues:

Welcome to the annual CNS Summit Abstracts of Poster Presentations supplement to Innovations in Clinical Neuroscience. We are pleased to provide you with this reference guide to some of the innovative research presented during the CNS Summit 2023 event. The supplement is also available online by visiting www.innovationscns.com.

This supplement is just a small representation of the cutting-edge research, innovative ideas, and collaborative efforts shared via the CNS Summit platform. The annual CNS Summit and its year-round programming are designed to encourage and facilitate open channels of communication and data sharing across all disciplines of medical research—with the ultimate goal of achieving optimal patient outcomes. 

In this abstract supplement, we’ve organized CNS Summit 2023 poster abstracts into the following groups for your convenience and easy reference:

  • Artificial Intelligence (AI)/Machine-based Learning
  • Assessment Devices and Tools
  • Biomarkers
  • Decentralized and Virtual Clinical Trials
  • Investigative Drug Compounds and Therapies
  • Treatment Devices and Tools
  • Trial Methodology
  • Wearables and Mobile Applications (Apps)

We hope you find the CNS Summit 2023 Abstracts of Poster Presentations supplement to Innovations in Clinical Neuroscience informative and that it provides you with a useful snapshot of the research being presented at the annual CNS Summit event. Visit www.cnssummit.org for more information.

As always, we welcome your feedback and participation.

Sincerely,

Amir Kalali, MD

Editor, Innovations in Clinical Neuroscience


Artificial Intelligence (AI)/Machine-based Learning

A Sleep EEG-based Machine Learning Classifier to Distinguish Parkinson’s Disease from Healthy Controls

Authors: Jay Pathmanathan, Kevin Zheng, Christine Vietz, Jacob Donoghue, Kolia Sadeghi

Affiliations: Beacon Biosignals in Boston, MA.

Background/Objective: Sleep pathology is common in and, in some cases, predictive of Parkinson’s disease (PD). We sought to develop a machine learning (ML) classifier of PD versus healthy controls using spectral power derived from sleep electroencephalography (EEG).

Design: A retrospective cohort study using a large database of polysomnography data linked to clinical diagnoses was conducted.

Results: Frontal, central, and occipital EEG polysomnography channels from 49 patients who received a diagnosis of PD and 2,880 controls were used to calculate absolute spectral power in the delta, theta, alpha, and beta bands. An L1-regularized logistic regression model was trained with EEG spectral power as input to discriminate between controls and participants with PD. Model results demonstrated two populations, with subjects younger than 50 years of age poorly separating from age-matched controls. The model demonstrated an area under the receiver operating characteristic curve (AUC) of 0.75 for all subjects and 0.89 for subjects over the age of 65 years.

Conclusion: A model using only sleep EEG power spectral features was able to distinguish older patients with PD from age-matched controls. Model performance was age dependent, with poor discriminative power for younger (age <50 years) patients. These findings could be explained by a disease-specific effect on EEG spectral power, exacerbated with disease duration or severity. Future analyses will be required to examine treatment effects and the utility of combining spectral power with measures of rapid eye movement (REM) without atonia (known to be predictive of PD).

Funding/financial disclosures: Beacon Biosignals is a commercial entity focused on analysis of time series neurophysiological data and the development of neurophysiological biomarkers.

Characterizing Disease Progression in Multiple Sclerosis Subtypes Using RWD: Feasibility of Applying a Machine Learning Model to Address Missing Data

Authors: Pedro Alves, Zachary Bryant, Michelle Leavy, Gary Curhan, Costas Boussios, Carl D. Marci

Background/Objective: The Expanded Disability Status Score (EDSS) is a validated, clinician-administered scale for measuring disability in multiple sclerosis (MS) that is widely used in clinical trials but recorded inconsistently in real-world data (RWD) sources. A machine learning model was developed to estimate EDSS scores at discrete time points using routinely recorded, unstructured clinical notes from neurologists and applied RWD in patients with MS with very good performance.1 The objective was to assess the feasibility of using this model to reduce the number of missing scores for EDSS to support the characterization of disability progression in patients with relapsing remitting MS (RRMS) who are transitioning to secondary progressive MS (SPMS).

Design: The model was applied to the OM1 MS PremiOM Dataset, a RWD source containing deidentified, deterministically linked clinical and administrative data from 2013 to 2021 on over 17,000 patients with MS managed by neurologists in the United States (US). Patients with RRMS and SPMS who had a clinician-administered or estimated EDSS score were included in the analytic cohort.

Results: The cohort included 4,366 patients; 3,568 had RRMS, 556 had SPMS, and 242 were transitioning from RRMS to SPMS. Patients in the RRMS subgroup were younger than patients in the other groups, while sex and race were similar across the subgroups. A total of 3,404 clinician-administered EDSS scores were documented. Application of the model resulted in an additional 46,644 estimated EDSS scores available for analysis, allowing for a more complete description of disability by age in patients with RRMS and SPMS.

Conclusion: Application of this model to estimate EDSS scores in a RWD source increases the number of patients available for studies of disease progression and outcomes, thereby improving the utility of RWD sources for MS research and informing the understanding of disability during the transition from RRMS to SPMS.

Funding/financial disclosures: Not provided.

Reference:

Alves P, Green E, Leavy M, et al. Validation of a machine learning approach to estimate expanded disability status scale scores for multiple sclerosis. Mult Scler J Exp Transl Clin. 2022;8(2):20552173221108635.

Continuous Monitoring of Upper Limb Function in Neurological Disorders

Authors: Adonay S. Nunes, Ilkay Yildiz Potter, Ram Kinker Mishra, Ashkan Vaziri

Affiliations: BioSensics LLC, Newton, MA.

Background/Objective: Goal-directed movements (GDMs) reflect the ability to execute planned motor commands with hand trajectories toward specific target locations. Our objective was to develop a deep learning model to automatically detect GDMs from accelerometer activity captured by a wearable device and test its sensitivity in classifying subjects with stroke.

Design: Thirty participants were recruited for the study, 20 stroke survivors (average age: 54.4 years) and 10 control participants (average age: 53.8 years). Participants wore six-axis inertial measurement units (IMUs) on each wrist and performed a series of activities of daily living. The dataset comprised of 49,254 time windows.

A deep learning model (XCM) was trained to classify GDM or non-GDM from accelerometer and velocity data. Leave-one-subject-out cross-validation was used to test the models’ performance. To further probe the utility of GDMs, we trained one model using features from GDM periods and another using the whole recording and tested which one could better classify stroke and control participants.

Results: The GDM classification model achieved an area under the curve (AUC) of 0.90, sensitivity of 0.81, specificity of 0.84, and F1 of 0.82. The model trained with GDM features achieved a balanced accuracy of 0.9, sensitivity of 1, and specificity of 0.8, outperforming the equivalent model trained on features extracted from the entire recording (accuracy: 0.75, sensitivity: 1, specificity: 0.5).

Conclusion: Our findings suggest that our deep learning model holds significant potential for real-world application in stroke rehabilitation and monitoring of neurodegenerative diseases. The ability to identify stroke survivors and quantify stroke severity based on GDM features further underscores the clinical relevance of this work.

Funding/financial disclosures: Research reported in this publication was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Number R44HD084035. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Development of Machine Learning Model for Estimating PHQ-9 Scores Using Clinical Notes from Real-World Data Sources

Authors: Jonathan Gerber, Carl Marci, Michelle Leavy, Pedro Alves, Costas Boussios

Background/Objective: The Patient Health Questionnaire-9 (PHQ-9) is a validated patient-reported measure for assessing depressive symptoms and symptom severity. However, documentation of the PHQ-9 is inconsistent in real-world data (RWD) sources, such as electronic medical records (EMRs), which limits the potential role of these data sources for supporting research studies.

Design: A machine learning (ML) model was developed to generate estimated PHQ-9 (ePHQ-9) scores using clinical notes from visits with mental health professionals. Data were drawn from the OM1 PremiOM Major Depressive Disorder (MDD) Dataset, a RWD source containing data on over 490,000 patients with MDD. Patients with both recorded PHQ-9 scores and clinical notes were identified and randomly assigned to a training cohort to train a validation cohort. Notes were transformed via medical language processing. To assess model performance, the area under the receiver operating characteristic curve (AUC) was calculated using a binarized version of the outcome, and continuous ePHQ-9 scores were evaluated using Spearman R and Pearson R values.

Results: The model had an AUC of 0.81, Spearman R value of 0.62, and Pearson R value of 0.61. The model resulted in the generation of new ePHQ-9 scores for 2,215,662 (2.7x enrichment over 814,166 recorded PHQ-9 scores) encounters for 208,692 (1.2x enrichment over 174,897 patients with a PHQ-9 score) distinct patients.

Conclusion: At the individual patient level, use of the ML model could provide a more complete view of a patient’s depressive symptom severity and response to treatment over time. At the population level, application of the model to RWD sources could increase the number of patients and encounters available for research on depression treatment and outcomes.

Funding/financial disclosures: Not provided.

Machine Learning-supported Shapelet-classification of Event-related Potentials Yields Novel Biomarkers for MCI/AD

Authors: Michael Lagler,1 Georg Dorffner1,2

Affiliations: 1The Siesta Group, Vienna, Austria; 2Institute of Artificial Intelligence, Center for Medical Data Science, Medical University of Vienna, Vienna, Austria.

Background/Objective: Objective measures of brain activity in the cognitively loaded state are described as event-related potentials (ERPs) and have since been established as quantitative biomarkers for tracking disease conditions associated with cognitive deficiencies. However, standard ERP metrics (amplitude, latency) are very susceptible to low signal-to-noise-ratio typical to single subject recordings, and mitigation strategies, such as filtering or a priori definitions of time windows and amplitude ranges, impose unwanted constraints and subjective biases. Therefore, the aim of this study was to explore machine learning (ML)-supported waveform classification techniques as novel tools facilitating the discovery of ERP-based biomarkers for mild cognitive impairment (MCI) and Alzheimer’s disease (AD).

Design: We analyzed data from 20 patients with MCI/AD and 20 healthy controls, recorded with the standard 10–20 system while performing an auditory oddball task. Waveform classification was based on identifying ERP subsequences with contrasting presence among data classes, called shapelets. Supervised learning of shapelets optimized linear separation of ERP waveforms in the shapelet-transformed space.

Results: For ERPs from patients with MCI/AD, we found that shapelet classification significantly outperformed classification based on standard ERP metrics. Learned shapelets carried MCI/AD features of absent N200 and delayed P300 in target trials and increased P50 and P200 in standard trials.

Conclusion: The results of this study support the hypothesis that ML-based waveform classification techniques can provide biomarker extraction capabilities that are not only less biased and less constrained, but also offer sensitivity beyond what can be achieved with standard measures. We conclude that analytical approaches, such as shapelet classification, might serve as a promising framework facilitating objective biomarker extraction in MCI/AD.

Funding/financial disclosures: GD and ML are employees of The Siesta Group, a service provider for measuring electrophysiological and actigraphic signals in clinical trials. GD is also a shareholder of The Siesta Group.

NetraAI: Understanding Patient Populations Beyond Disease Labels for Derisking Clinical Trials with Large Language Models

Author: Joseph Geraci

Affiliations: CTO/CSO of NetraMark

Background/Objective: NetraAI, with its unique Attractor Artificial Intelligence (AI) algorithms, provides a deep dive into causal factors from extensive datasets. Combined with large language models (LLMs), these causal clusters are enriched by the vast medical literature, paving the way for insightful analyses of clinical scales. Our work showcases the fusion of hypothesis-generating AI and LLMs, aiming to refine clinical trials, particularly in schizophrenia, anxiety, and major depression. This innovative approach assists in identifying explainable patient subpopulations, offering clarity to clinical trialists.

Design: Data from demographic items, psychiatric scales, and safety measures in clinical trials were integrated using Attractor AI technology. Technology related to attention mechanisms helps the machine explore the vast combinatorial space of variables. These form hypotheses related to patient subpopulations in anxiety and schizophrenia.

Results: Schizophrenia data: Among 120 patients, our system identified 55 percent of placebo responders post-Bonferroni corrections. The model predicted a subtype of placebo responders with an accuracy of 86 percent.

Anxiety data: Of 332 patients, eight clinical scale items formed a causal cluster accounting for 25 percent of placebo responders at 74-percent accuracy. A noteworthy revelation was a variable that improved placebo response but detrimentally affected drug response.

Major depression data: Analyzing 172 patients with major depressive disorder (MDD), NetraAI illuminated factors dictating response versus nonresponse. This inaugural revelation demonstrates the extraction of causal features from intricate datasets, providing insights that are impactful for future heterogeneous psychiatric condition trials.

Conclusion: This research underscores the powerful synergy of machine learning (ML) and LLMs in dissecting patient population responses in clinical trials. Identifying causal variables ensures optimized participant selection, fortifying trial efficacy. Harnessing psychological factors effectively can enhance study outcomes, but care is paramount to prevent negative drug response implications.

Funding/financial disclosures: Not provided.

NeuroID: A Cutting-edge Modular Target Discovery Engine for Parkinson’s Disease

Authors: Clement Chatelain, Can Kayatekin, Franck Rapaport, Julia Bonner, Simon Dujardin, Jeremy Huang, Giorgio Gaglia, Michael Chao, Samuel Lessard, Charles Fulco, Hendrik Wesseling, Travis Ahn-Horst, Dongyu Liu, Hao He, Tejaswi Iyyanki, Zhaohui Du, Emanuele de Rinaldis, Shameer Khader, Rajaraman Krishnan

Affiliations: Sanofi US, Cambridge, MA.

Background/Objective: We developed and evaluated an advanced modular target discovery platform, the NeuroID engine, for prioritizing therapeutic targets Parkinson’s disease (PD).

Design: The NeuroID engine centralizes multiomics data from various sources: human genetics on PD risk and progression (up to 53,858 patients), brain-specific epigenetics, bulk transcriptomics (from 51 selected studies), single-cell ribonucleic acid sequencing (RNA-seq), clustered regularly interspaced short palindromic repeats (CRISPR) screens (5 studies), proteomics, pathway/network biology, animal models, and text mining. Data were acquired from collaborations with Open Targets, FinnGen, UK Biobank, and AMP-PD. A specific machine learning (ML) model was created to prioritize PD, trained using this vast integrated data repository, and benchmarked against a list of targets prioritized by the Michael J. Fox Foundation (MJFF).

Results: The NeuroID model demonstrated superior performance in predicting MJFF-prioritized PD targets over other target discovery systems, such as Open Targets. This heightened performance is the consequence of the comprehensive integration of various -omics types by the NeuroID system, quality of the data integrated, and innovative analytical methods.

Conclusion: The NeuroID engine represents a major advancement in data-driven target discovery for neurodegenerative diseases. With its proven ability to predict relevant therapeutic targets, we expect it to uncover novel therapeutic opportunities in the near future, marking a significant leap in the fight against PD.

Funding/financial disclosures: Not provided.

Quantifying the Processes and Events of Psychotherapy at Scale

Authors: Todd M. Solomon, PhD;1 Jamileh Jemison, MD;1 Alexander Deschamps, LMSW;1 Matus Hajduk, MSc;1Adam Kolar, MSc;1 Martin Majernik, MSc;1 Miguel Amável Pinheiro, PhD;1 Owen Muir, MD;2 Amanda Tinkelman, MD;2 Duncan J. Kimmel, MD;3 Daniel R. Karlin, MD, MA1,4

Affiliations: 1Mind Medicine (MindMed), Inc., New York, NY; 2Brooklyn Minds Psychiatry & Curated Mental Health, New York, NY; 3Albert Einstein College of Medicine, New York, NY; 4Department of Psychiatry, Tufts University School of Medicine, Boston, MA

Background/Objective: This study aims to demonstrate the feasibility of collecting recordings of telemedicine psychotherapy, relevant electronic health records (EHRs), and matched real-world data (RWD) to create an aligned, multimodal dataset. We examined possible ways to use this dataset to train machine learning (ML) models, intending to explore the creation of tools that could assist psychotherapists.

Design: This study was conducted through an outpatient, telemedicine-enabled clinic in New York City. Participants were recruited from the existing treatment population and were already undergoing psychotherapy. After participants provided informed consent, each subsequent psychotherapy session was recorded; however, a participant could request that any individual session not be recorded without impact on study participation. Only sessions that occurred via telehealth were eligible for recording.

This study also collected participants’ EHR data from the study clinic, as well as their deidentified RWD from aggregated records providers, using a tokenized deidentification process provided by a third-party organization.

Results: We successfully collected 34 psychotherapy session recordings from 19 participants across seven different providers, as well as EHR and other real-world health data from all participants. Preliminary ML analyses were applied to the data, and a further plan for data analysis is discussed.

Conclusion: Establishing this unique dataset is the first step to developing ML tools that can assist psychotherapists in their practice. This study demonstrates the feasibility of collecting more data of this nature, illustrates potential analyses that can be applied to the data and how they may help improve psychotherapy.

Funding/financial disclosures: TMS, JJ, AD, MH, AK, MM, MAP, and DRK are employed by Mind Medicine, Inc., the sponsor of this research. OW and AT were employed by Brooklyn Minds Psychiatry, the research site, during this study.

The Roadmap for Digital Endpoint Adoption

Author: Rohini Kumar

Affiliations: Principal Sensor Solutions Leader, Scientific Data Organization, Parexel International

Background/Objective: The aim of this study was to showcase the emerging trends with the ongoing digital revolution, including the use of big data and artificial intelligence (AI) for diagnostic algorithms and treatment optimization.

Design: Parexel presents a multi-stakeholder perspective from regulatory, industry and patient use case, and health technology assessment (HTA) and payers on the adoption of novel digital endpoints.

Results: Regulatory perspective: Digital endpoints are an emerging source of data. The regulatory considerations for digital health technology (DHT) use include verification, validation, and usability of the DHT; operationalization; and evaluation of endpoints data with risk considerations.

Industry and patient perspective: Patients are responding positively. Fifty-seven percent of patients confirmed a positive general experience with smart watches and mobile applications (apps), 85 percent would prefer a wearable to a diary given a choice, and 28 percent purchased a personal device to support their health and disease management. Patient concerns include data privacy and ease of set-up, and training and support should be provided.

HTA and payer perspective: Digital endpoints also provide continuous and frequent measurement of the treatment outcome. The introduction of digital endpoints with machine learning (ML) capabilities introduces additional precision into the process, which will create new dynamics to inform practice, value, and access.

Conclusion: Regulatory guidelines are being established in key markets, paving the way for increased adoption of wearables and digital sensors. The use of connected devices could allow researchers to evaluate novel endpoints that utilize continuous data, ML, and AI. These methods are positioned to transform how we conduct clinical trials and gain patient insights.

Funding/financial disclosures: Not provided.

Assessment Devices and Tools

At-home Sway Assessments for Patients with Multiple Sclerosis: Richer Data, Lower Patient Burden

Author: Brett Meyer

Affiliations: Senior Data Scientist, Medidata

Background/Objective: Assessments of postural sway to determine disease state and fall risk in persons with multiple sclerosis (MS) typically require patients to stand on force platforms in clinics. For people with limited mobility, visiting a clinical research site involves a high degree of patient burden and limits accessibility to clinical research. In pursuit of more accessible methods, researchers from the University of Vermont and Medidata together evaluated remote postural sway as a biomarker for balance impairment and fall risk prediction.

Design: In a sample of persons with MS, the research team compared postural sway features from free-living data collected through wearable sensors to those computed from a laboratory (lab) standing assessment, computed correlations to patient-reported measures (PRMs), and trained fall classification models to establish clinical significance. Patients completed in-lab assessments, several PRMs, and a 48-hour daily life monitoring period—immediately following the lab visit—during which they wore chest and thigh movement sensors.

Results: By applying a cluster-based approach for analyzing remote data, the research team strengthened associations with PRMs, increasing their strength above those observed in the lab. While sway features differed significantly between lab and remote data—in some cases suggesting patients have variable confidence between lab and home environments—the clustering techniques reduced noise to make remotely collected data as useful as lab-collected data for predicting fall risk.

Conclusion: Clustering techniques applied to data remotely collected through wearable sensors equip researchers to predict fall risk for persons with MS with similar confidence to lab-based postural sway assessments, with the implication of lowering patient burden for those with MS in future studies.

Funding/financial disclosures: Not provided.

Enrichment Based on Automated Speech Latency Improves Treatment Effect in a Clinical Trial

Authors: Joshua S. Siegel, Sasagu Tomioka, Ajay Ogirala, Steven T. Szabo, Seth C. Hopkins, Kenneth S. Koblan, Mark G. Opler, Brian Kirkpatrick, Alex S. Cohen

Background/Objective: Speech latency is an objective measure of psychomotor slowing, with face validity and empirical support. Turn latency is the pause that occurs between when one person speaks and another responds. We previously demonstrated that automated detection of turn latency from structured psychiatric interviews shows temporal stability, convergent validity, sensitivity to change, and generalization across sociolinguistically diverse countries. Here, a retrospective analysis was conducted on the utility of turn latency as a potential enrichment tool.

Design: Speech data was obtained from 274 subjects with bipolar I depression in a randomized, double-blind, six-week clinical trial of SEP-4199 (200mg or 400mg). Automated speech analysis was conducted on 1,369 Montgomery–Åsberg Depression Rating Scale (MADRS) recordings. Predicted MADRS scores were modeled based on turn latency for postrandomization sessions and applied to the screening data for classifying individuals: Class-0 (slow latency, predicted MADRS ≥20) and Class-1 (normal latency, predicted MADRS <20). Treatment response was compared between these groups.

Results: At Week 6, Class-0 (n=213, slow screening latency) showed significant separation in MADRS improvement between placebo and both active treatment arms. Class-1 (n=61, normal screening latency) showed larger MADRS improvements overall and no significant separation between placebo and treatment arms. Excluding Class-1 increased primary outcome effect size by 64 percent and 83 percent for the treatment arms, respectively (0.36 to 0.59 for 200mg, 0.35 to 0.64 for 400mg).

Conclusion: Turn latency is an objective measure that is available from standard clinical assessments, and it may assess the severity of symptoms more accurately and potentially screen out placebo responders.

Funding/financial disclosures: Not provided.

Initial Psychometric Evaluation of the Pediatric Short Positive and Negative Syndrome Scale Version in an Adult, Acutely Exacerbated Clinical Trial Population with Schizophrenia

Authors: DG Daniel,1 A Kott,1 J Busner,1 X Wang,1 J Langfus,2 EA Youngstrom,3 R Findling4

Affiliations: 1Signant Health; 2University of North Carolina at Chapel Hill; 3University of North Carolina at Chapel Hill & Helping Give Away Psychological Science, 501c3; 4Virginia Commonwealth University

Background/Objective: The Positive and Negative Syndrome Scale (PANSS) is the most frequently used instrument to measure severity of schizophrenia in clinical research. The scale is long, takes a lot of time to administer, and appears to have many item redundancies. Several attempts were conducted to shorten the instrument to reduce administrative burden but retain the validity and reliability of the original PANSS. In the current study, we assessed the performance of the recently developed PANSS10 for pediatric studies (Findling et al, 2023) in adult acute schizophrenia trials.

Design: Baseline PANSS data were pooled from 5,059 subjects recruited into 15 acute adult schizophrenia trials. Internal consistency was examined using average item correlations. Convergent validity of the PANSS10 with the full PANSS and Clinical Global Impression-Severity (CGI-S) was examined using Pearson and Spearman correlation coefficient. Bland-Altman plots were used to show patterns of agreement between the PANSS10 and full PANSS.

Results: The average interitem correlation for the PANSS10 was 0.09. The PANSS10 showed a strong correlation with the full PANSS (r=0.96, p<0.0001). The Spearman correlation between the PANSS10 and CGI-S was 0.46, (p<0.0001); between the full PANSS and CGI-S, the Spearman correlation was 0.52 (p<0.0001). The PANSS10 showed a slight tendency for higher scores, as indicated by the Bland-Altman plots; the average discrepancy was 0.12 points.

Conclusion: The 10-item version of the PANSS developed for a pediatric population shows promising psychometric qualities even in an adult population of acutely exacerbated clinical trial participants with schizophrenia.

Funding/financial disclosures: Not provided.

Multicenter Evaluation of the Dreem 3 System for the Assessment of Sleep in Patients with Disturbed Sleep

Authors: Silvia Frati Savietto,1 Antoine Guillot,1 Mason Harris,1 Jay Pathmanathan,1 Valérie Bertaina-Anglade,2 Geoffrey Viardot,2 Derek Hill,3 Pierrick Arnal,1 Jacob Donoghue1

Affiliations: 1Beacon Biosignals, Boston, MA; 2Biotrial Neurosciences, FR; 3Panoramic Digital Health, FR

Background/Objective: This study aimed to evaluate the performance and usability of the Dreem 3S (D3S) dry-electroencephalogram (EEG) device for automated sleep staging and characterization of sleep parameters.

Design: Two prospective studies included 60 subjects who underwent either one overnight, in-laboratory (in-lab), traditional polysomnography (PSG) while concomitantly wearing the D3S, or three nights at home with the D3S.

Results: Overall agreement between D3S and PSG scoring was 85.6 percent across sleep stages. Intraclass correlation (ICC) for total sleep time (TST), sleep efficiency (SE), latency to persistent sleep (LPS), and wake after sleep onset (WASO) exceeded 90 percent, indicating excellent agreement between D3S and PSG. ICC ranged from 65 to 86 percent for automated machine learning (ML) interpretation of time spent in N1, N2, N3, and rapid eye movement (REM), comparable or superior to other devices and individual human performance. Usability evaluation demonstrated safe and comfortable use of the device in the home setting, with a System Usability Scale (SUS) score of 68 or greater. Subjects were able to operate and record 2 to 3 nights of high-quality data without additional support. Furthermore, 96.6 percent of each record was deemed to be of sufficient EEG signal quality to enable manual expert review.

Conclusion: This data demonstrates the validity of D3S in providing EEG-based sleep-stage assessment, comparable to in-lab PSG. D3S was comfortably used by subjects at home over multiple nights without the need for professional setup. This will improve accessibility and enable broader use, including for longitudinal sleep studies in decentralized clinical trials (DCTs), which could provide insights that in-lab PSG would be too impractical or costly to identify.

Funding/financial disclosures: Beacon Biosignals is a commercial entity focused on analysis of time series neurophysiological data and the development of neurophysiological biomarkers.

New Shortened Pediatric PANSS 10-item Scale: Extension and Replication of Findings in the Paliperidone Adolescent Schizophrenia Clinical Trial Dataset

Authors: Joan Busner, PhD;1 Eric A. Youngstrom, PhD;2 Joshua Langfus, MA;3 David G. Daniel, MD;4 Robert L. Findling, MD5

Affiliations: 1Signant Health and Virginia Commonwealth University School of Medicine; 2University of North Carolina at Chapel Hill, Psychology Department, Chapel Hill, NC; 3University of North Carolina at Chapel Hill; 4Signant Health; 5Virginia Commonwealth University School of Medicine

Background/Objective: Pediatric studies of schizophrenia have relied on the 30-item Positive and Negative Syndrome Scale (PANSS) as a primary outcome measure. The scale was designed for adults. Our group developed and published in 20231 a psychometrically sound 10-item version using pediatric data from the National Institute of Mental Health (NIMH) schizophrenia study.2 A 20-item version was also developed. We wished to replicate and extend the findings in an independent, large, placebo-controlled trial.

Design: We applied the same psychometric and treatment sensitivity analyses of our earlier work to the international, placebo-controlled, adolescent schizophrenia paliperidone randomized clinical trial, accessed via the YODA secure data environment. Analyses included confirmatory factor analyses, graded response models, omega reliability coefficients, tests of convergent criterion validity, sensitivity to change, and Bland-Altman plots to evaluate score reproducibility.

Results. The 10- and 20-item versions were similar to the 30-item version for average interitem correlations and omega total reliabilities, with reliability above 0.80 across patient presentations from mild residual symptoms to severe pathology; correlations of 0.92 and 0.98 with the 30-item total; similar partial eta-squared values for time, treatment, and time x treatment; and similar correlations with Clinical Global Impression-Severity (CGI-S) and Children’s Global Assessment Scale (CGAS) ratings.

Conclusion. The 10- and 20-item PANSS short forms replicated strong reliability and validity in this large, international, positive, randomized controlled trial. The short forms demonstrated treatment sensitivity and convergent validity equivalent to that of the 30-item form, supporting their future use and offering the promise of substantial savings of rater and patient time and burden.

Funding/financial disclosures: These findings were presented at the American Society for Clinical Pathology (ASCP) Annual Meeting, June 2023, in Miami, FL. Drs. Busner and Daniel are employees of Signant Health; financial disclosures of other authors available upon request.

References:

  1. Findling RL, Youngstrom EA, Frazier JA, et al. An optimized version of the Positive and Negative Symptoms Scale (PANSS) for pediatric trials. J Am Acad Child Adolesc Psychiatry. 2023;62(4):427–434.
  2. Sikich L, Frazier JA, McClellan J, et al. Double-blind comparison of first- and second-generation antipsychotics in early-onset schizophrenia and schizo-affective disorder: findings from the treatment of early-onset schizophrenia spectrum disorders (TEOSS) study. Am J Psychiatry. 2008;165(11):1420–1431.

Ventilatory Response to Hypercapnia as a Model to Study Respiratory Drive

Authors: Lynn Webster, MD; Steven Hull MD

Affiliations: Dr. Vince Clinical Research

Background/Objective: Central nervous system (CNS) drugs can induce respiratory depression when used alone or in combination. Ventilatory response to hypercapnia (VRH) is a known assessment method but has not, to date, been used to detect early signs at clinical doses. We describe an experimental model to assess drug-induced respiratory depression to meet growing United States (US) Food and Drug Administration (FDA) requirements for approval of CNS drugs.

Design: Previous scientific literature suggests that change in minute ventilation (VE) is a clinically relevant early biomarker of respiratory depression, as assessed by stressing respiratory drive with hypercapnia. The VRH test measures dynamic changes in VE over time during administration of 7% carbon dioxide (CO2) through a facemask. This method mimics the clinical effect of drugs on respiratory drive as physiological mechanisms compensate for rising CO2 levels. Measurements include VE, respiratory rate, tidal volume, flow rate, and end-tidal CO2 (ETCO2; mmHg, continuously predose and at intervals postdose). The experimental endpoint of interest is maximum change (Emax) in VE.

Results: VRH, including the traditional endpoint of VE at ETCO2 of 55mmHg (VE55), has been studied and found to be sensitive to CNS drugs. A recent FDA-initiated, randomized, double-blind, crossover trial in healthy volunteers showed that paroxetine/oxycodone significantly decreased VE, compared to oxycodone alone. Collectively, results suggest that VRH provides a sensitive, relevant model.

Conclusion: Measuring VRH can allow for a safe and controlled evaluation of clinical doses of drugs that may depress or reverse respiration before harmful levels are reached. Properly performed studies may allow the results to be included in the FDA package insert.

Funding/financial disclosures: Publication funding was provided by Dr. Vince Clinical Research, which employs LW and SH. Disclosures unrelated to the current topic are available on request.

Biomarkers

Pharmacogenomic Insights in Psychiatric Care: Uncovering Novel Actionability, Allele-specific CYP2D6 Copy Number Variation, and Phenoconversion in 15,000 Patients

Authors: Jai Patel,1 Sarah Morris,1 Raul Torres,2 Brooke Rhead,2 Chris Vlangos,2 Lisa C. Brown,2 Hailey Lefkofsky,2 Muneer Ali,2 Francisco M. De La Vega,2 Kathleen C. Barnes,2 Anthony Zoghbi,3 Joe Stanton,2 Marcus A. Badgeley2

Affiliations: 1Department of Cancer Pharmacology & Pharmacogenomics, Levine Cancer Institute, Atrium Health, Charlotte, NC; 2Tempus Labs, Chicago, IL; 3Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX

Background/Objective: Pharmacogenomic testing has emerged as an aid in clinical decision making for psychiatric providers, but more data is needed regarding its utility in clinical practice and potential impact on patient care. In this retrospective review, we sought to determine the real-world prevalence of pharmacogenomic actionability in patients receiving psychiatric care.

Design: Potential actionability was based on the prevalence of CYP2C19 and CYP2D6 phenotypes, CYP2D6 allele-specific copy number variants (CNVs), CYP2D6 phenoconversion, the novel CYP2C-TG haplotype, and combined actionability from all sources in patients with available medication data.

Results: Across 15,000 patients, 65 percent had potentially actionable CYP2D6 and CYP2C19 phenotypes, and phenotype assignment was impacted by CYP2D6 allele-specific CNVs in two percent of patients. Of 4,114 patients with medication data, 42 percent had CYP2D6 phenoconversion from drug interactions and 20 percent carried a novel CYP2C haplotype potentially altering actionability. Eighty-seven percent of patients had some form of actionability from genetic findings and/or phenoconversion, and genetic variation detected via next-generation sequencing (NGS) led to phenotype reassignment in 22 percent of individuals overall (2% in CYP2D6 and 20% in CYP2C19).

Conclusion: Ultimately, pharmacogenomic testing using NGS identified potential actionability in most patients receiving psychiatric care. Early pharmacogenomic testing may provide actionable insights to aid clinicians in drug prescribing to optimize psychiatric care.

Funding/financial disclosures: Tempus Labs funded the sequencing and compute costs for this study. MA is a contracted physician with Amen Clinics, Inc. LCB is a consultant to Tempus Labs and Headlamp Health and is VP of Clinical Strategy for Sequence2Script.

Speech Biomarkers for Monitoring Neurological Symptoms Across Different Populations

Authors: Adonay S. Nunes, PhD;1 Ram Kinker Mishra, PhD;1 Ashkan Vaziri, PhD2

Affiliations: 1Senior Research Scientist, BioSensics LLC, Newton, MA; 2Founder and CEO, BioSensics LLC, Newton, MA

Background/Objective: Neurological disorders affect central and peripheral nervous systems, impairing motor, speech, and cognitive functions. Our objective is to develop BioDigit Speech, a digital speech assessment solution for evaluating speech in neurological conditions, such as progressive supranuclear palsy (PSP), Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).

Design: The rainbow passage reading task was administered to 59 older adults (41 with cognitive impairment and 18 cognitively intact), 11 patients with PSP, 10 with PD, and 11 with ALS. Speech was recorded and analyzed using BioDigit Speech.

Results: Participants with cognitive impairment showed less similarity with the text (similarity DTW: 0.44 vs. 0.73, p>0.001), reduced intelligibility (intelligibility DTW: 0.24 vs. 0.37, p=0.012), and more pauses (speech-to-pause ratio: 3.53 vs. 7.51, p=0.017), compared to those who were cognitively intact. The Montreal Cognitive Assessment (MoCA) score correlated significantly with similarity DTW (ρ = 0.53, p>0.001), ratio of extra words (ρ=0.53, p>0.001), speech-to-pause ratio (ρ= 0.38, p>0.003), and intelligibility DTW (ρ=0.33, p>0.01). Moreover, slower articulation rate was significantly lower in PSP versus PD (2.45 vs. 3.60 words/minute, p<0.001), with reduced intelligibility (intelligibility DTW: 0.26 vs. 0.53, p=0.017). Additionally, in ALS, lower bulbar function correlated with articulation rate (ρ=0.88, p<0.001) and intelligibility DTW (ρ=0.758, p<0.001) during passage reading.

Conclusion: Digital speech assessment can be a cost-effective solution for frequent and remote evaluation of neurological function. Results across disorders show speech sensitivity in distinguishing and capturing disease variability. Integrating speech assessments can benefit clinical trials with reliable remote patient monitoring.

Funding/financial disclosures: Research reported in this publication was supported in part by BioSensics, LLC, and the National Institute on Aging of the National Institutes of Health under Award Number R44AG080861. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Decentralized and Virtual Clinical Trials

Analytical Validation and Feasibility Assessment of a Smart Blood Pressure Monitor for Use in Decentralized Clinical Trials

Authors: Jasmin Imsirovic,1 Maíra Tristão Parra,2 David Wing,2 Katerina Placek,1 Ariel V. Dowling,1 Ryan Moran,2,3 Matthew Allison,3 Job Godino2

Affiliations: 1Data Sciences Institute, Takeda Pharmaceuticals, Inc., Cambridge, MA; 2Exercise and Physical Activity Resource Center, University of California San Diego, La Jolla, CA; 3Department of Medicine, University of California San Diego, La Jolla, CA

Background/Objective: Blood pressure (BP) is a vital sign used by clinicians to assess patient health and safety in clinical trials. As decentralized clinical trials (DCTs) reduce the number of clinic visits for patients, it is necessary to enable patients to accurately measure BP in the home environment using validated and patient friendly tools. Smart BP monitors are available to consumers but require validation and usability testing prior to implementation in DCTs. The aim of this study was to assess the analytical validation and usability of the Withings BPM Connect blood pressure monitor.

Design: Subjects used the monitors twice daily at home for a week to assess usability, while the accuracy of the Withings BPM Connect was compared to a reference device (Omron 5 Series) in 28 healthy volunteers (17 female, aged 12–65 years) during in-clinic testing. Statistical analyses included Bland-Altman plots, Lin’s concordance correlation coefficient, mean absolute percent error, and root mean square error.

Results: Both systolic and diastolic BP measurements demonstrated low bias and high accuracy relative to the reference device of -2.3mmHg (95% limits of agreement [LoA]: -17.8 –13.2) and -0.37mmHg (95% LoA: -9.7–9.0), respectively. The BPM Connect received an average of 70.1 points out of 100 on the System Usability Scale (SUS) from the at-home testing.

Conclusion: The Withings BPM Connect demonstrated acceptable clinical accuracy and agreement with a commonly used BP cuff and moderately high usability in a diverse population. These results indicate that the device may be fit-for-purpose in DCTs.

Funding/financial disclosures: Not provided.

Analytical Validation of Pediatric Digital Health Technologies for Use in Decentralized Clinical Trials

Authors: Katerina Placek, MS, PhD;1 David Wing, MS, CBDT, CCRC;2 Jasmin Imsirovic, PhD;1 Maira Tristao Parra, ScD, MS, MPH;2 Michael Higgins, MS;2 Ryan Moran, MD, MPH;3 Job Godino, PhD;2 Shoibal Datta, PhD;1 Ariel V. Dowling, PhD1

Affiliations: 1Digital Health Sciences, Takeda Pharmaceuticals, Inc., Cambridge, MA; 2Exercise and Physical Activity Resource Center, University of California San Diego, La Jolla, CA; 3University of California San Diego Health, San Diego, CA

Background/Objective: There are few United States (US) Food and Drug Administration (FDA)-approved digital health technologies (DHTs) for remote pediatric vital signs and actigraphy monitoring. Furthermore, there is limited knowledge of the accuracy under different physiological conditions and at-home usability of existing devices in pediatric populations. Our goal is to enable future decentralized clinical trials (DCTs) by evaluating the accuracy and usability of DHTs to collect remote vital signs and actigraphy data in a pediatric population for clinical research.

Design: We are conducting a fit-for-purpose observational study to evaluate the accuracy and usability of three medical-grade DHTs that measure vital signs and actigraphy in 20 children aged 2 to 12 years.

Analytical performance: Participants will undergo one day of in-laboratory (in-lab) measurements of vital signs and actigraphy under different age-appropriate physical activities to compare test DHT measurements to concurrent measurements from FDA-cleared reference devices.

Longitudinal usability: Test DHTs will be used at home over five days with remote study staff support. A System Usability Scale (SUS) and qualitative interview will be conducted at a follow-up in-lab visit to assess compliance and comfort.

Results (anticipated): Analysis of the root mean square error between concurrent paired measurements will indicate the accuracy of test DHT measurements. Mixed-effects models will elucidate the relationships between accuracy and age, physical activity, and skin tone.

Conclusion: Analytical validation is necessary to demonstrate the accuracy and usability of DHTs in a pediatric population due to the lack of existing evidence. Quantifying the performance of DHTs in pediatrics is necessary to support their future use in DCTs.

Funding/financial disclosures: This study was funded by Takeda Pharmaceutical Company, Ltd.

Analytical Validation of Withings Digital Health Technologies for Use in Decentralized Clinical Trials

Authors: Andrew Kaseman, MS;1 Jasmin Imsirovic, PhD;1 Ariel V. Dowling, PhD;1 Job Godino, PhD;2 Ryan Moran, MD, MPH3

Affiliations: 1Data Sciences Institute, Takeda Pharmaceuticals, Inc., Cambridge, MA; 2Exercise and Physical Activity Resource Center, University of California San Diego, La Jolla, CA; 3University of California San Diego Health, San Diego, CA

Background/Objective: Decentralization of clinical trials has created a need for the accurate measurement of vital sign data in the home environment. These measurements can be quantified using digital devices, but these devices must be validated for accuracy of the acquired data. The objective of this study was to establish an analytical validation process for measurement of vital signs using digital devices. This process will quantify the accuracy of the data, compared to accepted reference devices.

Design: Twenty-eight healthy subjects consented to health metric tracking. Withings devices were selected as the vital sign measurement devices because of their usability ratings. Data was measured concurrently by both Withings devices and clinically accepted reference devices. Accuracy was assessed by comparing measurements between devices. A statistical analysis plan was created based on a combination of International Organization for Standardization (ISO) standards, United States (US) Food and Drug Administration (FDA) guidance, and existing literature on medical devices.

Results: The Thermo thermometer demonstrated accuracy within FDA guidelines (root mean square error [RMSE]: 0.52°F). The Body+ weight scale was an accurate and precise scale (RMSE: 0.40kg). However, body composition measurements were less accurate (RMSE: 3.45kg). The Sleep Mat passive sleep monitor was accurate, compared to reference devices, for both heart rate (RMSE: 9.11bpm) and respiratory rate at rest (RMSE: 2.37 breaths/min). The ScanWatch smartwatch could accurately measure heart rate in patients at rest (RMSE: 4.07bpm); however, its accuracy suffered during exercise (RMSE: 29.59bpm). Caution should be used when measuring electrocardiogram signals (RMSE: 47.54ms). Blood oxygenation measurements, despite being FDA cleared, were inaccurate (RMSE: 3.63%).

Conclusion: The Withings digital devices provide accurate measurements of several vital signs, compared to gold standard reference devices. However, advanced measurements, such as body composition and electrocardiography, lack clinically sufficient accuracy.

Funding/financial disclosures: This study was funded by Takeda Pharmaceutical Company, Ltd.

Driving the Adoption of Decentralized Trials: DTRA’s Initial Initiative Deliverables

Authors: Amir Kalali, MD; Craig Lipset; Jane Myles; Paige Altrogge

Affiliations: Decentralized Trials & Research Alliance (DTRA)

Background/Objective: The objective was to share the progress to date on the cross-industry initiatives chartered and executed by DTRA.

Design: Twelve initiatives were chartered to define the roadmap to develop strategic solutions for teams. Working groups are established to work on the priority aligned strategic roadmap. Through initiative teams and CoLabs, DTRA works to publish resources, such as a glossary, an evidence of impact repository, patient journey maps, and more. These resources are made available to the research community at large to support education and adoption of decentralized clinical trials (DCTs).

Results: Tools, data, and resources are now available from all 12 of the initiative teams. These are accessible to the public for use in designing and executing DCTs or research studies.

Conclusion: By enabling a community of stakeholders to work together on our shared goals and mission, we are working to educate the research community to give patients the best experience possible while part of a clinical trial.

Funding/financial disclosures: DTRA is a 501c3 nonprofit organization.

Embedding the Patient Voice in Decentralized Clinical Trials

Authors: Keri McDonough,1 Michelle Ouellette2

Affiliations: 1Head, Patient Voice Consortium, Vice President, Medical and Scientific Strategy, Syneos Health; 2Associate Director, Patient Recruitment and Retention Management, Syneos Health

Background/Objective: Hybrid and decentralized clinical trials (DCTs) have been touted for their ability to make research participation easier and more inclusive without sacrificing study integrity. However, much of the DCT narrative has been driven by assumptions, rather than concrete data. To address this gap, Syneos Health sought to learn from recent clinical trial participants and seasoned advocates about their perspectives on when, where, and how remote care and monitoring technologies might improve the research experience for participants.

Design: Syneos Health used a mixed-method approach. A 50-question survey was deployed to patients who recently participated in an interventional clinical trial. Respondents (n=300) were asked to reflect on their satisfaction across DCT modalities. Syneos Health then held an advisory workshop with seasoned patient advocates to interpret survey findings; explore how age, race, and disease area affect preferences; and surface strategies for designing studies that align with real-world patient considerations and concerns. Advocates represented national and regional organizations working in pain, mental illness, psoriasis, rare diseases, and respiratory diseases.

Results: Seventy-four percent of survey respondents said a DCT option would make them more likely to participate in trials. Reduced travel burden and greater flexibility scheduling visits were the main reasons.

Conclusion: Syneos Health research validates a key assumption: DCT and digital health solutions will likely encourage participation across different demographics and disease types. As DCT strategies mature, it will be critical to ensure that population-specific insights are at the forefront of efforts to improve participant experiences.

Funding/financial disclosures: None to report.

Implementation of Home Infusions in a Multinational Preclinical Alzheimer’s Disease Study

Authors: Isabella Velona, Masters;1 Roy Yaari, MD;1 Karen C. Holdridge, MPH;1 Cheryl Ann Brown, RPh;1 Paula Cohen, BA;2 Elizabeth Shaffer-Bacareza, BS;3 Maria Arampatzidou, PhD;2 Nancy Lizzul, RN;4 Ellen Weiss, BA4

Affiliations: 1Eli Lilly and Company, Indianapolis, IN; 2Alzheimer’s Therapeutic Research Institute, University of Southern California Keck School of Medicine, San Diego, CA; 3Alzheimer’s Therapeutic Research Institute, University of Southern California, San Diego, CA; 4PCM Trials, Denver, CO

Background/Objective: The A4 Study was a Phase III clinical trial investigating solanezumab in preclinical Alzheimer’s disease (AD). The COVID-19 pandemic impacted the delivery of elective health services worldwide, and social distancing restrictions created challenges for clinical trial participants to continue monthly infusions. To retain A4 participants, decentralized clinical trial (DCT)methods were implemented, including deployment of mobile research nurses to conduct home visits.

Design: The A4 Study was a 4.5-year double-blind trial, followed by an optional four-year, open-label treatment period. The study launched in 2014, and 1,163 male and female patients between the ages of 65 and 85 years have been dosed. Home visits were not originally included in the study protocol but were implemented in 2020 to mitigate the impact of the COVID-19 pandemic on study conduct. PCM Trials offered home visits as an option to allow participants to continue to receive the investigational product. Mobile research nurses traveled to participant homes and administered the 30- to 60-minute intravenous (IV) infusions every four weeks.

Results: More than 1,400 home infusion visits were conducted in the A4 Study. A total of 124 participants were enrolled in home infusions (99 in the United States, 1 in Canada, and 24 in Australia) from 18 sites.

Conclusion: We demonstrated not only that home infusions could be implemented successfully and safely in this population during the pandemic, but also that continuing this model postpandemic successfully addressed challenges to retention. Considering the length of the study, infusion frequency, and age of the participants, home visits helped study completion and compliance.

Funding/financial disclosures: Not provided.

Learnings From the Execution of the First Interventional Decentralized Clinical Trial in Major Depressive Disorder: A Phase II Trial

Authors: Christopher Reist,1 Thuy Le Nguyen,2 Peide Li,2 Sigurd D. Suessmuth3

Affiliations: 1Science 37, Culver City, CA; 2Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT; 3Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany

Background/Objective: Decentralized clinical trials (DCTs) utilize digital innovations, namely telemedicine and smartphone applications (apps), to allow trial conduct at patients’ homes. Here, key learnings from an interventional DCT evaluating BI 1358894 in patients with major depressive disorder (MDD) are reported.

Design: This Phase II DCT was conducted through a collaboration between Boehringer Ingelheim and Science 37 (California, United States [US]), from a single (meta)site in the US. Patients were enrolled (June 2020–April 2022) through various social media and randomized to receive BI 1358894 or placebo. Patient feedback surveys were issued at the end of the study. A central review of clinical data and video recordings by a third-party vendor was established, and local laboratory patient service centers were set up to allow urgent patient access to clinical care. Trial data was captured directly through the Science 37 platform.

Results: In this first of its kind study, operational feasibility of the DCT model was demonstrated using the Science 37 platform. The protocol was successfully executed, and the platform provided an easy way for subjects to communicate with study staff, complete patient-reported outcome measures (PROMs), and schedule study visits. This translated into a completion rate of 97 percent, as well as high levels of subject satisfaction. A wide variety of traditional and digital recruitment strategies were employed. Despite over 80,000 potential subjects being reached over a vast geography, only 45 were randomized over a 22-month period. Therefore, it was decided to terminate the trial early.

Conclusion: A Phase II protocol was successfully executed in patients with MDD using the Science 37 platform to support a completely DCT; however, digital recruitment was unable to overcome the challenges of stringent eligibility criteria.

Funding/financial disclosures: This study was funded by Boehringer Ingelheim (1402-0014, NCT04423757). CR is an employee of Science 37. PL, TLN, and SDS are employees of Boehringer Ingelheim. SDS is a member of the faculty of medicine of the University Hospital of Ulm, Germany, but declares no conflict of interest.

When Words Speak Just as Loudly as Actions: Virtual Agent-based Remote Clinical Trial Endpoints Integrating What Patients Say with What They Do

Authors: Vikram Ramanarayanan, David Pautler, Lakshmi Arbatti, Abhishek Hosamath, Michael Neumann, Hardik Kothare, Oliver Roesler, Jackson Liscombe, Andrew Cornish, Doug Habberstad, Vanessa Richter, David Fox, David Suendermann-Oeft, Ira Shoulson

Affiliations: Modality.ai, Inc.

Background/Objective: We present a unified multimodal dialog platform for the remote assessment and monitoring of patients with applications to remote digital clinical trials. We show that combining patient reports (i.e., what they say) with objective biomarkers (i.e., how they say it and what they do) can greatly enhance the quality of telemedicine and improve the efficacy of siteless trials and digital therapeutic interventions.

Design: A virtual agent, Tina, engages participants in an immersive interaction comprising tasks that elicit speech, facial, motoric, and cognitive behaviors, objective biomarkers of which can be automatically computed from participant speech and video in near-real time. Furthermore, Tina encourages participants to describe, in their own words, their most bothersome problems and what makes them better or worse, through the Patient Report of Problems™ (PROP™) instrument, as well as other clinical survey instruments of interest.

Results: Multimodal analytics modules automatically extract features that capture information from acoustic (energy, timing, voice quality, spectral), facial (articulatory kinematics, range of motion, eye and facial movement), motoric (finger tapping kinematics), and textual (lexico-semantic, sentiment) domains during these tasks. We also classify verbatim PROP responses into multiple clinically relevant symptoms using a multilabel text classification deep neural network model trained on data collected from over 25,000 patients.

Conclusion: Combining objective audiovisual biomarkers with patient self-report of problems via conversational artificial intelligence and interpretable machine learning has significant potential to enhance the quality of telemedicine-based healthcare and improve the efficacy of siteless trials and digital therapeutic interventions.

Funding/financial disclosures: All authors are salaried and receive equity from Modality.ai, Inc.

Investigative Drug Compounds and Therapies

Baseline Mismatch Negativity Amplitude Predicts Direction and Magnitude of Ketamine Effect in Healthy Volunteers: A Disordinal Effect

Authors: KC Fadem,1 J Johannesen,2 B Farley,2 M Cecchi,1 L Ereshefsky,3,4,5 DH Mathalon6

Affiliations: 1Cognision, KY; 2Sage Therapeutics, MA; 3CenExel HRI, NJ; 4CenExel Research, CA; 5University of Texas Health Science Center at San Antonio, TX; 6University of California and VA Health Care System, San Francisco, CA

Background/Objective: Mismatch negativity (MMN) is a neurophysiological response linked to activity of N-methyl-D-aspartate (NMDA) receptors. However, effects of NMDA receptor blockade by ketamine appear bidirectional, producing either suppression or augmentation of MMN amplitude in different individuals. We evaluated the hypothesis that the direction and magnitude of ketamine’s effect is predicted by baseline MMN.

Design: MMN was assessed twice, first during placebo, then during ketamine, in healthy volunteers from three studies with a similar duration of deviant paradigms (KET1: n=8; KET2: n=19; KET3: n=25). Because baseline MMN may predict MMN change upon retest due to regression to the mean, we also compared the baseline MMN prediction of ketamine-induced change to its prediction of MMN change during a drug-free test-retest study (TR: n=36).

Results: In all groups, baseline MMN moderated the magnitude and direction of MMN change, with larger baselines predicting MMN decreases and smaller baselines predicting MMN increases. However, the slopes of this relationship differed significantly between groups (group x baseline MMN: p=0.003). Specifically, relative to the TR group slope (beta: -0.511), significantly steeper slopes were observed for KET2 (p<0.001) and KET3 (p=0.005), but not KET1 (p=0.189). The three ketamine group slopes did not differ (p=0.624), and their common slope was significant (beta: -0.746, p<0.001).

Conclusion: Ketamine produces a disordinal effect on MMN, inducing decreases in those with larger MMNs and increases in those with smaller MMNs that are distinct from regression to the mean. Whether this effect is specific to MMN and related to variation in clinical measures requires further study.

Funding/financial disclosures: This research was solely funded by the ERP Biomarker Qualification Consortium. List of the Consortium members is available at https://erpbiomarkers.org. KCF is an employee and shareholder of Cognision. JJ is an employee of Sage Therapeutics. BF is an employee and shareholder of Sage Therapeutics. MC is an employee of Cognision.

BI 1358894 in Patients with Major Depressive Disorder: Preliminary Results From an Interventional Decentralized Clinical Trial

Authors: Christopher Reist,1 Peide Li,2 Thuy Le Nguyen,2 Sigurd D. Suessmuth3

Affiliations: 1Science 37, Culver City, CA; 2Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT; 3Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany

Background/Objective: This study aimed to characterize the safety profile of BI 1358894 administered as an adjunct to standard-of-care antidepressants in patients with major depressive disorder (MDD) and inadequate response to first-line antidepressants.

Design: This Phase II, randomized, double-blind, placebo-controlled, parallel-group, decentralized clinical trial (DCT) enrolled patients aged 18 to 65 years with MDD (current depressive episode of ≥8 weeks–≤18 months), ongoing antidepressant monotherapy (≥8 weeks), and a Montgomery–Åsberg Depression Rating Scale (MADRS) total score of 22 or greater at screening. Eligible patients were randomized 1:1 to receive BI 1358894 or placebo daily for six weeks. Adverse events (AEs) were recorded. Suicidal behavior/ideation was monitored using the Columbia-Suicide Severity Rating Scale (C-SSRS). All assessments were home-based.

Results: A total of 131 patients were enrolled, 45 were randomized, and 43 were treated (BI 1358894, n=20; placebo, n=23). The mean (standard deviation [SD]) age was 42.2 (13.1) years, and 84 percent of patients were female. Efficacy was not evaluated due to early trial termination and insufficient statistical power. Suicidal ideation was more common in the active treatment group (C-SSRS baseline: BI 1358894, 15%; placebo, 4%). AEs were reported by 86 percent of patients (BI 1358894, 90%; placebo, 83%). Two BI 1358894-treated patients reported AEs resulting in discontinuation. Two placebo-treated patients experienced serious AEs. A severe AE (headache) was experienced by one BI 1358894-treated patient.

Conclusion: In this interventional DCT, adjunctive daily BI 1358894 treatment over six weeks was well-tolerated and demonstrated a favorable safety profile. Slow recruitment resulted in early trial termination, indicating that the recruitment process is critical for success.

Funding/financial disclosures: This study was funded by Boehringer Ingelheim (1402-0014, NCT04423757). CR is an employee of Science 37. PL, TLN, and SDS are employees of Boehringer Ingelheim. SDS is a member of the faculty of medicine of the University Hospital of Ulm, Germany, but declares no conflict of interest.

Comparative Study of Treatment Modalities for Cervical Pain: Real-world Evidence

Authors: Dr. Rakshita Putul,1 Dr. Dee Amanze2

Affiliations: 1Senior Clinical Coder, Clinical Trial Analytics & Strategic Insights, IQVIA; 2Director, Medical Coding, Clinical Trial Analytics & Strategic Insights, IQVIA

Background/Objective: This study compared the effectiveness of conservative therapy versus steroid injections in adult patients diagnosed with cervical pain.

Design: In this longitudinal study, IQVIA-deidentified, United States (US), patient-level claims data of 54.7 million patients diagnosed over a period of 10 years (2012–2022) were reviewed. Effectiveness of treatment modalities was based on the number of patients whose condition progressed to surgical interventions.

Results: Data analysis showed that 3.2 percent of the total patients diagnosed with cervical pain progressed to the stage requiring surgical intervention. Out of 2.11 million patients that were treated using only conservative therapy, four percent required surgical intervention. In the 17,000 patients treated using only steroid injections, a significantly higher number of patients (n=2,336; 13%) required surgical intervention.

The total population of cervical pain patients consisted of 62 percent female and 38 percent male patients. The disease was more prevalent in patients above 50 years of age. The most common comorbidities were lower back pain, joint pain, hypertension, and hyperlipidemia. The comorbidity profile was similar in both the conservative treatment and steroid injection groups.

Conclusion: A significantly higher number of patients (2.11 million) opting for only conservative therapy, compared to patients treated with only steroid therapy (17,000), indicates that conservative therapy remains the most popular first-line treatment option. Also, conservative therapy is considered a more effective treatment modality, based on the significantly smaller number of patients requiring surgical intervention. More studies are needed to fully document the benefits of conservative therapy in the treatment of cervical pain.

Funding/financial disclosures: Not provided.

Efficacy and Safety of Esmethadone (REL-1017) in Patients with Major Depressive Disorder and Inadequate Response to Standard Antidepressants: A Phase III Randomized Controlled Trial

Authors: M Fava, S Stahl, L Pani, S De Martin, C O’Gorman, C Guidetti, A Alimonti, S Comai, A Mattarei, F Folli, D Bushnell, S Traversa, CE Inturrisi, PL Manfredi,* M Pappagallo*^

*Drs. Pappagallo and Manfredi contributed equally; ^Presenting author

Background/Objective: The goal of this study was to evaluate the efficacy, safety, and tolerability of esmethadone (REL-1017) as adjunctive treatment of major depressive disorder (MDD).

Design: This Phase III, double-blind, placebo-controlled, randomized trial studied oral REL-1017 25mg or placebo for 28 days in patients with inadequate response to standard antidepressants. The primary efficacy endpoint was the change in the Montgomery–Åsberg Depression Rating Scale (MADRS) from baseline to Day 28. In the intent-to-treat (ITT) group, patients were randomized, irrespective of protocol deviations or discontinuation. In the per-protocol (PP) group, subjects completed treatment without major deviations affecting efficacy assessments. Prerandomization, clinicians from the Clinical Trial Network and Institute assessed prior antidepressant response and antidepressant tolerance/tachyphylaxis using the Antidepressant Treatment Response Questionnaire. MADRS score above 35 at Day 1 (baseline) was categorized as severe depression.

Results: N: number of subjects; R: REL-1017; P: placebo; CFB: MADRS change from baseline; MD: mean difference; p: p-value; ES: Cohen’s Effect Size

  • ITT—N: 227; R: 113; P: 114; CFB MD: 2.3; p=0.1537; ES: 0.21
  • PP—N: 198; R: 101; P: 97; CFB MD: 3.1; p=0.0510; ES: 0.29
  • PP female patients—N: 146; R: 74; P: 72; CFB MD: 3.8; p=0.0417; ES: 0.36
  • PP patients aged over 50 years—N: 88; R: 46; P: 42; CFB MD: 6.3; p=0.0043; ES: 0.64
  • PP MADRS score above 35—N: 98; R: 45; P: 53; CFB MD: 7.9; p=0.0015; ES: 0.68
  • PP AT—N: 79; R: 43; P: 36; CFB MD: 6.1; p=0.0101; ES: 0.62

Conclusion: Efficacy outcomes favored PP analyses. Favorable efficacy outcomes were observed in PP prespecified analyses of female patients and patients above the age of 50 years, as well as in post hoc analyses of MADRS score above 35 and AT. Esmethadone was safe and well tolerated.

Funding/financial disclosures: Not provided.

Efficacy and Safety of Iclepertin (BI 425809) in Patients with Schizophrenia: CONNEX, a Phase III Randomized Controlled Trial Program

Authors: Corey Reuteman-Fowler,1* Zuzana Blahova,2 Satoru Ikezawa,3 Stephen R. Marder,4 Peter Falkai,5 John H. Krystal6

*Presenting author

Affiliations: 1Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT; 2Boehringer Ingelheim RCV GmbH & Co. KG, Vienna, Austria; 3Graduate School of Arts and Sciences, The University of Tokyo, Komaba, Meguro-ku, Tokyo, Japan; 4Department of Psychiatry and Behavioral Sciences, David Geffen School of Medicine, Los Angeles, CA; 5Clinic of Psychiatry and Psychotherapy, Ludwig Maximilians University Munich, Munich, Germany; 6Department of Psychiatry, Yale University School of Medicine, New Haven, CT

Background/Objective: No effective pharmacological treatments are available for cognitive impairments in schizophrenia. Iclepertin (BI 425809), a glycine transporter-1 inhibitor, enhances N-methyl-D-aspartate (NMDA) receptor signaling by increasing synaptic levels of its co-agonist glycine. In a Phase II, proof-of-clinical-concept trial (NCT02832037), iclepertin was well tolerated and improved cognition in schizophrenia. The Phase III CONNEX program aims to confirm the efficacy and safety of iclepertin in improving cognition and functioning across a large cohort of patients with schizophrenia.

Design: The CONNEX program consists of three replicate randomized, double-blind, placebo-controlled, parallel trials in patients with schizophrenia (NCT04846868, NCT04846881, NCT04860830). A total of 586 patients per trial will be recruited across 41 countries and randomized 1:1 to receive daily iclepertin 10mg or placebo over 26 weeks. The primary efficacy endpoint is change from baseline (CfB) in overall composite T score of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery. Key secondary efficacy endpoints include CfB in total Schizophrenia Cognition Rating Scale score and CfB in the adjusted total time in the Virtual Reality Functional Capacity Assessment Tool. Long-term safety and tolerability data will be collected in an open-label safety extension study (CONNEX-X).

Results: The studies are currently recruiting (first participants enrolled August–September 2021), with completion expected in Q1 2025. Current study status, including screening failures and data collection experiences, are presented.

Conclusion: Most industry-sponsored studies testing compounds for cognitive deficits have failed to show proof-of-clinical-concept. If successful, the CONNEX program would provide evidence for iclepertin as the first efficacious medication addressing cognitive impairments in schizophrenia.

Funding/financial disclosures: These studies were funded by Boehringer Ingelheim (1346-0011, NCT04846868; 1346-0012, NCT04846881; 1346-0013, NCT04860830). CRF and ZB are employees of Boehringer Ingelheim. SI has received consultancy fees from Boehringer Ingelheim Pharma GmbH, Lundbeck, Takeda Pharma, and Sumitomo Dainippon Pharma. SRM has financial agreements with Boehringer Ingelheim Pharma GmbH, Merck, Biogen, and Sunovion. PF has received consultancy fees from Boehringer Ingelheim Pharma GmbH and is a member of the Boehringer Ingelheim Pharma advisory board. JHK is a co-founder of Freedom Biosciences, Inc.; has received consultancy fees from Aptinyx, Atai Life Sciences, AstraZeneca Pharmaceuticals, Biogen, Biomedisyn Corporation, Bionomics, Boehringer Ingelheim International, Cadent Therapeutics, Clexio Bioscience, COMPASS Pathways, Concert Pharmaceuticals, Epiodyne, EpiVario, Greenwich Biosciences, Heptares Therapeutics, Janssen, Jazz Pharmaceuticals, Otsuka America Pharmaceutical, Perception Neuroscience Holdings, Spring Care, Sunovion Pharmaceuticals, Takeda Industries, and Taisho Pharmaceutical, Co.; is a member of the advisory board of Biohaven Pharmaceuticals, BioXcel Therapeutics, Cadent Therapeutics, Cerevel Therapeutics, Delix Therapeutics, EpiVario, Eisai, Jazz Pharmaceuticals, Novartis, PsychoGenics, RBNC Therapeutics, Tempero Bio, and Terran Biosciences; and has investments in Biohaven Pharmaceuticals, Sage Pharmaceuticals, Spring Care, Biohaven Pharmaceuticals Medical Sciences, EpiVario, RBNC Therapeutics, Terran Biosciences, and Tempero Bio.

Efficacy of KarXT (Xanomeline–Trospium) in Schizophrenia: Pooled Results From the Randomized, Double-blind, Placebo-controlled EMERGENT Trials

Authors: Soumya Chaturvedi, MS, PhD;1 Inder Kaul, MD, MPH;1 Leslie Citrome, MD, MPH;2 Sharon Sawchak, RN;1 Judith Kando, PharmD;1 Andrew C. Miller, PhD;1 Steven M. Paul, MD;1 Stephen K. Brannan, MD1

Affiliations: 1Karuna Therapeutics, Boston, MA; 2New York Medical College, Valhalla, NY

Background/Objective: KarXT (xanomeline–trospium chloride) is a dual M1/M4 preferring muscarinic receptor agonist that lacks direct D2 dopamine receptor binding. The efficacy and safety of KarXT in schizophrenia was demonstrated in the five-week, randomized, double-blind, placebo-controlled, EMERGENT-1 (NCT03697252), EMERGENT-2 (NCT04659161), and EMERGENT-3 (NCT04738123) inpatient trials in people with schizophrenia experiencing acute psychosis.

Design: In each trial, the primary efficacy endpoint was change from baseline to Week 5 in Positive and Negative Syndrome Scale (PANSS) total score versus placebo. Additionally, changes from baseline to Week 5 in PANSS positive subscale, PANSS negative subscale, PANSS Marder negative factor, and Clinical Global Impression-Severity (CGI-S) scores were assessed. Data from the EMERGENT trials were pooled, and efficacy analyses were conducted in the modified intent-to-treat population, defined as all randomized participants who received one or more trial drug doses and had a baseline and one or greater postbaseline PANSS assessment.

Results: The pooled analyses included 640 participants (KarXT, n=314; placebo, n=326). Across trials, KarXT was associated with a significantly greater reduction in PANSS total score at Week 5, compared to placebo (KarXT: -19.4; placebo: -9.6; p<0.0001; Cohen’s d=0.65). At Week 5, KarXT was also associated with a significantly greater reduction than placebo in PANSS positive subscale (KarXT: -6.3; placebo: -3.1), PANSS negative subscale (KarXT: -3.0; placebo: -1.3), PANSS Marder negative factor (KarXT: -3.8; placebo: -1.8), and CGI-S scores (KarXT: -1.1; placebo: -0.5; all p<0.0001).

Conclusion: In pooled analyses from the EMERGENT trials, KarXT demonstrated statistically significant improvements across efficacy measures with consistent and robust effect sizes, and findings support the potential of KarXT to be first in a new class of medications to treat schizophrenia.

Funding/financial disclosures: This trial was sponsored by Karuna Therapeutics. SC is an employee and holds equity in Karuna Therapeutics.

KET01-02: Oral Prolonged-release Adjunctive KET01 Ketamine for Treatment-Resistant Depression. Results of a Randomized, Placebo-controlled, Double-blind, Phase II Trial

Authors: Martin Walter,1 Christine zu Eulenburg,2,3 Karin Schmid,4 Isabel Schwienbacher,2,5 Ani Damyanova,2 Evangelos Papanastasiou,2 Florian Holsboer,2 Hans Eriksson2

Affiliations: 1University Hospital Jena, Department of Psychiatry and Psychotherapy, Jena, Germany; 2HMNC Brain Health, Munich, Germany; 3University Medical Center Hamburg-Eppendorf, Germany; 4Develco Pharma Schweiz AG, Pratteln, Switzerland; 5Current affiliation: Boehringer Ingelheim Pharma, Ingelheim am Rhein, Germany

Background/Objective: Ketamine is a rapid-acting antidepressant associated with dissociative adverse effects. KET01 is an oral prolonged-release formulation of racemic ketamine with a low potential for dissociation.

Design: Outpatients (N=122) with treatment-resistant depression (TRD) were randomized to once-daily placebo (PBO), KET01 120mg, or KET01 240mg for three weeks. The first dose was administered under supervision; remaining doses were taken at home. Primary endpoint was mean change from baseline in the Montgomery–Åsberg Depression Rating Scale (MADRS) on Day 21 (mixed model for repeated measures).

Results: KET01 240mg/day dose demonstrated rapid improvements in MADRS at seven hours after first dosage (change from baseline: -7.65; Δ vs. PBO: -2.22, not significant), with statistically significant separation on Day 4 (change from baseline: -10.02; Δ vs. PBO: -3.66, p=0.020) and Day 7 (change from baseline: -12.21; Δ vs. PBO: -3.95, p=0.042). The improvements were sustained until Day 21 (change from baseline: -13.15; Δ vs. PBO: -1.82, not significant) and after four-week follow-up (change from baseline: -12.51; Δ vs. PBO: -3.35, not significant). KET01 was well tolerated, with treatment-emergent adverse events (TEAEs) reported by 47.5, 50.0, and 62.5 percent of patients in the PBO, KET01 120mg/day, and KET01 240mg/day groups, respectively. No differences in the mean Clinician-Administered Dissociative States Scale scores were observed between the groups at any time point. Transient elevations in mean plasma gamma-glutamyltransferase and alanine aminotransferase concentrations occurred from Week 2 for both KET01 groups.

Conclusion: This study demonstrated a rapid and clinically relevant reduction of depressive symptoms after treatment with KET01 240mg/day, with only minimal signs of dissociative symptoms.

Funding/financial disclosures: MW was the international coordinating investigator for the KET01-02 trial. CE, AD, EP, FH, and HE are employed by or consultants to HMNC Brain Health. KS is employed by Develco Pharma. IS was previously employed by HMNC Brain Health.

KET01-03: A Randomized, Placebo-controlled, Double-blind, Double-dummy, Crossover Phase I Trial to Assess the Tolerability, Safety, and Pharmacokinetics of Antidepressant Doses of Oral Ketamine Hydrochloride Prolonged Release Tablets (KET01) Compared to Intranasal Esketamine in Healthy Male Subjects

Authors: Hans Eriksson,1* Christine zu Eulenburg,1,2 Isabel Schwienbacher,1,3 Karin Schmid,4 Ani Damyanova,1 Lars Arvastson,1 Evangelos Papanastasiou1

*Presenting author

Affiliations: 1HMNC Brain Health, Munich, Germany; 2University Medical Center Hamburg-Eppendorf, Germany; 3Current affiliation: Boehringer Ingelheim Pharma, Ingelheim am Rhein, Germany; 4Develco Pharma Schweiz AG, Pratteln, Switzerland

Background/Objective: Subanesthetic doses of ketamine and esketamine exert rapid antidepressant effects. Acute side effects, such as dissociation and increase in blood pressure, can emerge after any route of administration and are related to peak plasma levels. Systemic or oral immediate-release administration of ketamine or esketamine lead to early Cmax values accompanied by dissociation and blood pressure changes. Administration of an oral prolonged-release formulation of ketamine results in relatively lower Cmax and relatively higher concentrations of the metabolite hydroxynorketamine (HNK), compared to after rapid systemic administration. HNK has shown efficacy in rodent models of depression.

The objective of the KET01-03 trial was to compare the tolerability and safety of single antidepressant doses of oral KET01 (240mg prolonged-release ketamine) and intranasal esketamine (SPRAVATO® 84mg; active comparator; the highest approved dose) and investigate the pharmacokinetics of ketamine and esketamine and their main metabolites.

Design: This was a randomized, placebo-controlled, double-blind, double-dummy, single-center, crossover trial in healthy male volunteers. After screening, two single-dose treatment periods were separated by a washout period of 14 to 28 days. The primary objective was to compare the maximum changes in the Clinician-Administered Dissociative States Scale (CADSS) score from baseline within the treatment period between the two treatments.

Results: The first subject was dosed on July 3, 2023, and the last visit took place on August 7, 2023. Twenty-five subjects received two doses. No serious adverse events (SAEs) were reported.

Conclusion: Twenty-five subjects completed the trial, and no SAEs were reported. Further evaluation is ongoing, and results will be presented.

Funding/financial disclosures: HE, CE, AD, LA, and EP are employed by or consultants to HMNC Brain Health. IS was formerly employed by HMNC Brain Health. KS is employed by Develco Pharma.

Lumateperone Treatment for Major Depressive Episodes with Mixed Features in Major Depressive Disorder and Bipolar I or Bipolar II Disorder

Authors: Suresh Durgam,1 Susan G. Kozauer,1 Willie R. Earley,1* Changzheng Chen,1 Jason Huo,1 Stephen M. Stahl,2 Roger S. McIntyre3,4

*Presenting author

Affiliations: 1Intra-Cellular Therapies, Inc., New York, NY; 2Department of Psychiatry, University of California, San Diego; La Jolla, CA; 3Department of Psychiatry, University of Toronto, Toronto, ON, Canada; 4Department of Pharmacology, University of Toronto, Toronto, ON, Canada

Background/Objective: Lumateperone is a United States (US) Food and Drug Administration (FDA)-approved antipsychotic to treat schizophrenia and depressive episodes associated with bipolar I or bipolar II disorder. This randomized, double-blind, placebo-controlled, multicenter trial (NCT04285515) investigated the efficacy and safety of lumateperone 42mg for the treatment of a major depressive episode (MDE) in patients with major depressive disorder (MDD) or bipolar depression with mixed features.

Design: Adults with Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5)-diagnosed MDD or bipolar I/ II disorder with mixed features experiencing an MDE (Montgomery–Åsberg Depression Rating Scale [MADRS] total score ≥24 and Clinical Global Impression-Severity [CGI-S] score ≥4) were randomized 1:1 to lumateperone 42mg or placebo. Primary and key secondary efficacy outcomes were changes from baseline to Day 43 in MADRS total score and CGI-S score, respectively. Safety was assessed.

Results: Of 385 treated patients (placebo, n=193; lumateperone, n=192), 344 (89.4%) completed the study. MADRS total score significantly improved with lumateperone 42mg, compared to placebo, in the combined MDD/bipolar depression population (mean change from baseline to Day 43 least squares mean difference [LSMD] vs. placebo: -5.7; 95% confidence interval [CI]: -7.60, -3.84; effect size: -0.64; p<0.0001), with similar significant improvements (p<0.0001) in individual MDD and bipolar depression populations. Significant improvements were also observed for CGI-S in the combined MDD/bipolar depression population (LSMD: -0.6; 95% CI: -0.81, -0.39; effect size: -0.59; p<0.0001) and individual MDD and bipolar depression populations. Lumateperone treatment was generally safe and well tolerated, and it was consistent with prior studies.

Conclusion: Lumateperone 42mg demonstrated robust efficacy over placebo in patients with MDD or bipolar depression with mixed features and was generally safe and well tolerated.

Funding/financial disclosures: SD, SGK, WRE, CC, and JH are full-time employees of Intra-Cellular Therapies, Inc. and may hold equity in the company. SMS has served as a consultant to Acadia, Alkermes, Allergan, AbbVie, Arbor Pharmaceuticals, Axovant, Axsome, Celgene, Concert, Clearview, EMD Serono, Eisai Pharmaceuticals, Ferring , Impel NeuroPharma, Intra-Cellular Therapies, Inc., Ironshore Pharmaceuticals, Janssen, Karuna, Lilly, Lundbeck, Merck, Otsuka, Pfizer, Relmada, Sage Therapeutics, Servier, Shire, Sunovion, Takeda, Taliaz, Teva, Tonix, Tris Pharma, and Viforpharma; is a board member of Genomind; has served on speakers bureaus for Acadia, Lundbeck, Otsuka, Perrigo, Servier, Sunovion, Takeda, Teva, and Vertex; and has received research and/or grant support from Acadia, Avanir, Braeburn Pharmaceuticals, Eli Lilly, Intra-Cellular Therapies, Inc., Ironshore, ISSWSH, Neurocrine, Otsuka, Shire, Sunovion, and TMS NeuroHealth Centers. RSM has received research grant support from CIHR/GACD/National Natural Science Foundation of China (NSFC); speaker/consultation fees from Lundbeck, Janssen, Alkermes, Neumora Therapeutics, Boehringer Ingelheim, Sage, Biogen, Mitsubishi Tanabe, Purdue, Pfizer, Otsuka, Takeda, Neurocrine, Sunovion, Bausch Health, Axsome, Novo Nordisk, Kris, Sanofi, Eisai, Intra-Cellular Therapies, Inc., NewBridge Pharmaceuticals, AbbVie, and Atai Life Sciences; and is a CEO of Braxia Scientific Corp.

Magnitude and Repeatability of Ketamine Effects on ERP and QEEG Biomarkers in a Double-blind, Randomized, Placebo-controlled, Crossover Study in Healthy Volunteers

Authors: M Cecchi,1 M Mahmoud-Zadeh,2 JM Uslaner,3 R Terry-Lorenzo,2 DG Smith,4 DA Ruhl,2 M Rotte,5 AL Reese,2 MC Quirk,6 P O’Donnell,6 J Mollon,7 C Missling,8 Y Matsuoka,9 MJ Marino,3 S Lee,3 D Klamer,8 J Johannesen,6 A Jeong,9 S Honda,10 B Farley,6 KC Fadem,1 J Doherty,6 EA Cohen,11 S Christensen,12 DL Buhl,6 M Adachi,10 L Ereshefsky,11,13,14 DP Walling,13 WZ Potter,15 DH Mathalon,16 DC Javitt17

Affiliations: 1Cognision, KY; 2Neurocrine Biosciences, CA; 3Merck & Co., Inc., Rahway, NJ; 4Alkermes, MA; 5Novartis, MA; 6Sage Therapeutics, MA; 7AbbVie Deutschland GmbH & Co. KG, Germany; 8Anavex Life Sciences Corp., NY; 9AbbVie, IL; 10Astellas Pharma, CA; 11CenExel HRI, NJ; 12Lundbeck, Denmark; 13CenExel Research, CA; 14University of Texas Health Science Center at San Antonio, TX; 15Independent Consultant, Philadelphia, PA; 16University of California and VA Health Care System, San Francisco, CA; 17Columbia University, NY

Background/Objective: We present results from a study sponsored by the ERP Biomarker Qualification Consortium (https://erpbiomarkers.org) that quantified the magnitude and reliability of ketamine-induced changes on event-related potential (ERP) and quantitative electroencephalogram (QEEG) measures in healthy volunteers (HVs).

Design: The study was a randomized, double-blind, placebo-controlled, three-arm, three-period crossover design (NCT04928703). Twenty-four HVs aged 21 to 45 years were administered ketamine intravenously in two of the periods and placebo in the remaining period in a counterbalanced order. The ketamine dose was a 0.23mg/kg bolus over one minute, followed by 0.58mg/kg per hour for 30 minutes, and 0.29mg/kg per hour for up to 29 minutes after that. ERP and EEG data were collected during the infusions. Each ERP/EEG testing session included four tests: active oddball, resting-state EEG, 40Hz auditory steady-state response (ASSR), and duration-deviant mismatch negativity.

Results: Ketamine effects on ERP and QEEG measures included an increase in N100 amplitude, N100 and P200 latency, and a decrease in P3b and P200 amplitude in the active oddball; a decrease in low-frequency power and an increase in gamma power and peak alpha frequency in the resting-state EEG; and an increase in 40Hz power in the 40Hz ASSR. Finally, reliability of the ketamine effects, as measured by intraclass correlation coefficient, was good-to-excellent for most of the measures collected.

Meaningful Behavioral Change as an Efficacy Outcome in a Clinical Trial of Istradefylline for Apathy in Parkinson’s Disease

Authors: Travis H. Turner, Christina Marsiscano, Sandra Wilson, Lilia Lovera, Federico Rodriguez-Porcel

Background/Objective: Apathy is a common, troublesome symptom in Parkinson’s disease (PD), associated with diminished quality of life for both the patient and care partner.1,2 Because apathy reduces engagement in physical and social activities, it may accelerate disease progression and cognitive decline.3 Prior studies suggest reduced apathy with istradefylline in PD;4 enhanced mesolimbic dopamine via adenosine A2A receptor antagonism is proposed as a mechanism.5 Functional measures of motivated behavior may prove more effective in measuring apathy and response to treatment than subjective rating scales.6 This article aimed to describe design and methodology for an ongoing study of istradefylline treatment on physical activity and other motivated behavior in PD.

Design: A sample of 32 patients with PD with motor fluctuations and clinically significant apathy will complete a 12-week open-label trial of istradefylline. Primary efficacy outcomes include the Physically Activity Scale for the Elderly (PASE)7 and Engagement in Meaningful Activities Survey (EMAS),8 completed via weekly telephone surveys. Change in PASE total score and EMAS will be evaluated using hierarchical linear modeling, controlling for improvements in motor functioning.

Results: Study enrollment will be completed in October 2023, with primary results reported in early 2024.

Conclusion: This study utilizes real-world measures of motivated behavior, the PASE and EMAS, to evaluate impact of istradefylline on apathy in PD. These measures provide clinically meaningful efficacy outcomes relevant to disease-modifying behavior. Preliminary results indicate favorable participant experience with the study protocol and intervention. Findings from this study will inform study design of larger controlled trials.

Funding/financial disclosures: Not provided.

References:

  1. van Reekum R, Stuss DT, Ostrander L. Apathy: why care? J Neuropsychiatry Clin Neurosci. 2005;17(1):7–19.
  2. Antonini A, Barone P, Marconi R, et al. (2012). The progression of non-motor symptoms in Parkinson’s disease and their contribution to motor disability and quality of life. J Neurol. 2012;259(12):2621–2631.
  3. Crotty GF, Schwarzschild MA. Chasing Protection in Parkinson’s disease: does exercise reduce risk and progression? Front Aging Neurosci. 2020;12:186.
  4. Nagayama H, Kano O, Murakami H, et al. Effect of istradefylline on mood disorders in Parkinson’s disease. J Neurol Sci. 2019;396:78–83.
  5. Chen JF, Choi DS, Cunha RA. Striatopallidal adenosine A2A receptor modulation of goal-directed behavior: homeostatic control with cognitive flexibility. Neuropharmacology. 2023;226:109421.
  6. Leentjens AF, Dujardin K, Marsh, L, et al. Apathy and anhedonia rating scales in Parkinson’s disease: critique and recommendations. Mov Disord. 2008;23(14):2004–2014.
  7. Washburn RA, Smith KW, Jette AM, Janney CA. The Physical Activity Scale for the Elderly (PASE): development and evaluation. J Clin Epidemiol. 1993;46(2):153–162.
  8. Goldberg B, Brintnell ES, Goldberg, J. The relationship between engagement in meaningful activities and quality of life in persons disabled by mental illness. Occup Ther Ment Health. 2002;18(2):17–44.

Minimal EPS Risk Observed with Muscarinic Agonist KarXT (Xanomeline–Trospium) Is Consistent with the Absence of Direct D2 Dopamine Receptor Affinity

Authors: Keisha Novak, PhD;2 Steven D. Targum;1 Carolyn Watson, PhD;2 Colin Sauder, PhD;2 Inder Kaul, MD, MPH;2 Andrew C. Miller, PhD;2 Amy Claxton, PhD;2 Steven M. Paul, MD;2 Stephen K. Brannan, MD2

Affiliations: 1Signant Health, Boston, MA, Stony Brook, NY; 2Karuna Therapeutics, Boston, MA

Background/Objective: Atypical antipsychotics can induce extrapyramidal symptoms (EPS), contributing to overall side effect burden. KarXT (xanomeline–trospium chloride) is an investigational therapy targeting muscarinic receptors and lacking D2 dopamine receptor binding that shows promise for treating schizophrenia without many of the side effects associated with current treatments. Here, we further characterize EPS rates in KarXT clinical trials.

Design: EMERGENT-1 (NCT03697252), EMERGENT-2 (NCT04659161), and EMERGENT-3 (NCT04738123) were five-week, randomized, double-blind, placebo-controlled, inpatient trials in people with schizophrenia. Treatment-emergent adverse events (TEAEs) associated with EPS from the safety populations, defined as all participants who received one or more doses of trial medication, were pooled. Additionally, EPS were assessed by examining changes from baseline to Week 5 on the Simpson-Angus Scale, Barnes Akathisia Rating Scale, and Abnormal Involuntary Movement Scale.

Results: EPS AEs were observed in 3.2 percent of patients in the KarXT group (n=340) versus 0.9 percent in the placebo group (n=343). The most commonly reported TEAE was akathisia (KarXT: 2.4%; placebo: 0.9%). Overall rates of akathisia TEAEs deemed related to trial drug were low (KarXT: 0.6%; placebo: 0.3%). All reported TEAEs were mild to moderate in severity. KarXT was not associated with clinically meaningful changes from baseline to Week 5 on scales assessing EPS.

Conclusion: The incidence of TEAEs associated with EPS with KarXT treatment was low and not associated with increased scores on EPS scales across five weeks of treatment. These results, combined with the robust efficacy of KarXT in trials to date, suggest that KarXT’s novel mechanism of action may provide therapeutic benefit in the absence of EPS frequently associated with currently available antipsychotics.

Funding/financial disclosures: This trial was sponsored by Karuna Therapeutics. KN is an employee and holds equity in Karuna Therapeutics.

No Indication of Abuse Potential or Withdrawal with Esmethadone (REL-1017): Results from Two Phase III Randomized Controlled Trials in Patients with Major Depressive Disorder

Authors: M Shram,* M Pappagallo,*^ J Henningfield, C Gorodetzky, S De Martin, F Vocci, F Sapienza, T Kosten, D Bushnell, C Guidetti, C O’Gorman, F Folli, S Traversa, CE Inturrisi, PL Manfredi

*Drs. Shram and Pappagallo contributed equally; ^Presenting author

Affiliations: MP is affiliated with Relmada Therapeutics.

Background/Objective: Esmethadone (REL-1017) is an N-methyl-D-aspartate (NMDA) receptor uncompetitive antagonist. We evaluated the abuse potential and dependence of REL-1017 in two Phase III trials of patients with major depressive disorder (MDD).

Design: Studies-301 and -303 were 28-day, outpatient, Phase III, randomized, double-blind, placebo-controlled trials of once daily oral REL-1017 25mg (Day 1 loading dose: 75mg) in patients with MDD. We performed a safety analysis of all adverse events (AEs) and collected narratives for AEs potentially related to abuse. We assessed “drug liking,” “drug high,” and “desire to take the drug again” with a 0- to 100-point visual analogue scale (VAS). We used The Misuse, Abuse, and Diversion Drug Event Reporting System (MADDERS®) to assess potentially abuse-related events. We assessed withdrawal after abrupt treatment discontinuation with the Physician Withdrawal Checklist (PWC), Clinical Opiate Withdrawal Scale (COWS), and Subjective Opiate Withdrawal Scale (SOWS).

Results: Among the 459 patients receiving any study drug, AEs were predominantly mild or moderate and transient. AEs potentially related to abuse were not correlated to other measures of abuse potential and did not differ among groups. There were no differences in VAS scores and no indication of abuse on the MADDERS®. Among 354 patients who participated in the safety withdrawal assessment, change from baseline on the PWC, COWS, and SOWS were not clinically meaningful and did not differ between groups.

Conclusion: In two contemporary, Phase III, double blind, placebo-controlled, MDD studies of REL-1017, there were no indications of meaningful abuse potential or dependence.

Funding/financial disclosures: Not provided.

Pharmaceutical Pipeline of BI 1358894: Clinical Evidence for an Emerging Drug for the Treatment of Mental Health Conditions

Authors: Brittney Starling,1 James Cronican,1 Stefan Just,2 Lauren Liss,3 Irina Adamczyk,3* Sigurd D. Suessmuth,3 Jennifer Dwyer1

*Presenting author

Affiliations: 1Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT; 2Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach an der Riss, Germany; 3Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany

Background/Objective: Amygdala hyperreactivity is thought to be a major contributor to anxiety and mood disorders, with associations to both posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Inhibition of transient receptor potential canonical (TRPC) 4/5 ion channels, which are highly expressed in human and rodent amygdalae, may reduce anxiety and stress-related symptoms by reducing amygdala hyperreactivity. Here, we provide an overview of early studies into BI 1358894, a small molecule inhibitor of TRPC4/5 ion channels, which may provide a novel mechanism of attenuating amygdala hyperreactivity to treat symptoms in disorders such as PTSD and MDD.

Design: Five Phase I studies were performed in healthy male volunteers. The pharmacodynamic effects of BI 1358894 versus placebo were assessed following cholecystokinin tetrapeptide (CCK-4) administration to induce panic symptoms in healthy volunteers. Functional magnetic resonance imaging (fMRI) was used to investigate the effects of BI 1358894 on amygdala reactivity in patients with MDD during exposure to negative emotional faces and scenes.

Results: Across the clinical studies, BI 1358894 200mg or less was generally well tolerated. Compared to placebo, BI 1358894 reduced the physiological and psychological response to CCK-4, measured by the Panic Symptom Scale and levels of stress biomarkers (adrenocorticotropic hormone and serum cortisol), indicating target engagement. A fMRI study in patients with MDD demonstrated that BI 1358894 attenuated activity in the amygdala in response to negative emotional faces and scenes.

Conclusion: Ongoing Phase II trials will determine the potential of BI 1358894 in the treatment of PTSD and MDD.

Funding/financial disclosures: This study was funded by Boehringer Ingelheim (1402-0001, NCT03210272; 1402-0002, NCT03754959; 1402-0003, NCT03854578; 1402-0005, NCT03904576; 1402-0008, NCT03875001). BS, JC, and JD are employees of Boehringer Ingelheim Pharmaceuticals, Inc. SJ, LL, IA, and SDS are employees of Boehringer Ingelheim International GmbH.

Potential Impact of KarXT on Negative Symptoms in Acute Schizophrenia: An Analysis of Pooled Data from 3 Trials

Authors: William P. Horan,1 Amy Claxton,1 Steven D. Targum,2 Inder Kaul,1 Sharon Sawchak,1 Andrew C. Miller,1 Steven M. Paul,1 Stephen K. Brannan1

Affiliations: 1Karuna Therapeutics, Boston, MA; 2Signant Health, Boston, MA

Background/Objective: KarXT, an M1/M4 preferring central muscarinic receptor agonist, has shown efficacy in the treatment of Positive and Negative Syndrome Scale (PANSS) total and positive symptoms in acute schizophrenia across three Phase II/III trials. It is possible that KarXT may also have a direct treatment benefit for negative symptoms (NS) that is not secondary to positive symptom improvements. Post hoc analyses explored the possible efficacy of KarXT in a subgroup of participants with moderate/severe NS and no predominance of positive symptoms.

Design: Data were pooled from one Phase II (NCT03697252) and two Phase III (NCT04659161, NCT04738123) trials of KarXT in acute inpatients with schizophrenia that used identical, five-week, randomized, double-blind, placebo-controlled designs. Previously established criteria were used to identify a subset of participants with prominent NS.

Results: Among the 10 percent of participants in the pooled sample who met criteria for prominent NS (n=64/640), there was a significantly larger PANSS-NS improvement in those treated with KarXT (n=29) than placebo (n=35; estimate: -4.71, standard error [SE]: 1.16, p<0.0001; Cohen’s d=1.18). Further, the KarXT effect remained statistically significant after accounting for changes in positive symptoms, depression/anxiety, disorganization, or hostility.

Conclusion: In the prominent NS subgroup, KarXT was associated with a large, significant improvement in NS that persisted after accounting for changes in positive and other symptoms. While these exploratory findings must be interpreted with caution, they are consistent with the possibility that KarXT directly impacts NS in acutely psychotic individuals and supports further investigation in stable outpatients.

Funding/financial disclosures: This trial was sponsored by Karuna Therapeutics. WPH is an employee and holds equity in Karuna Therapeutics.

Preclinical In Vitro and In Vivo Characterization of a Spray Dried Loxapine Nasal Powder

Authors: Paul Shields,1 Irene Rossi,2 Philip J. Kuehl,3 Julie D. Suman4

Affiliations: 1Enteris Biopharma, Inc., Boonton, NJ; 2Nanopharm, Cwmbran, United Kingdom; 3Lovelace Biomedical, Albuquerque, NM; 4Aptar Pharma, Congers, NY

Background/Objective: Loxapine succinate, an antipsychotic used for acute agitation, is currently administered by intramuscular injection or inhalation (Adasuve®). A boxed warning for bronchospasm when administered via inhalation limits use to inpatient settings. An intranasal dry powder formulation was developed to eliminate respiratory adverse events (AEs) and facilitate outpatient treatment. The objective of this study was to identify a lead intranasal formulation by in vitro characterization and pharmacokinetic analysis in nonhuman primates (NHPs).

Design: Spray dried nasal powder consisting of loxapine, hydroxy propyl methyl cellulose (HPMC), and mannitol was manufactured and filled in a unit dose powder device. Assay, impurities, water content, emitted dose, particle size of bulk powder, and impactor aerodynamic characterization were performed. An intravenous (IV) formulation, neat spray dried intranasal loxapine, and the lead formulation were administered to NHPs (all 3mg doses). Plasma loxapine was quantified for four hours postdose.

Results: The lead spray dried powder presented no impurities, 100.6 percent assay, and 2.08 percent water content. Median bulk particle size was 24.39µm. Ninety-five percent of the loaded dose was emitted from the device with an impactor size mass of just 0.2 percent w/w. Average area under the curve (AUC) was 232, 147, and 204ng/mL*hr, respectively for the IV, neat, and lead formulations. Average Cmax and Tmax were 364, 76, 140ng/mL and 2.7, 39.9, and 8.8min, respectively.

Conclusion: In vitro analysis indicated a stable lead formulation with ideal properties for intranasal delivery. The lead formulation had comparable AUC four hours postdose to the IV route following intranasal delivery in NHPs, indicating suitability for further development.

Funding/financial disclosures: Not provided.

Proposed Mechanism of Tianeptine, a Plastogen Antidepressant in Phase II Development in the United States

Authors: Gregory M. Sullivan, Bruce L. Daugherty, David T. Hsu, Darryl C. Rideout, Sina Bavari, Jennifer Cho, Herbert Harris, Siobhan Fogarty, Seth Lederman

Affiliations: Tonix Pharmaceuticals, Inc.

Background/Objective: Tianeptine’s antidepressant mechanism has remained elusive over three decades of use. Tianeptine sodium 12.5mg (Stablon®) three times per day is approved outside the United States (US) and has comparable efficacy to tricyclic antidepressants and selective serotonin reuptake inhibitors (SSRIs) and improved tolerability. Tianeptine hemioxalate is a novel salt form in Phase II development as a once-daily formulation. We discovered tianeptine and its (S)-isomer mimic polyunsaturated fatty acids, such as eicosapentaenoic acid (EPA), in activating peroxisome proliferator-activated receptor (PPAR)-β/δ and PPAR-γ, and these activities may account for its ability to induce or restore neuroplasticity.

Design: Racemic tianeptine was separated into stereoisomers by chromatography. Absolute configuration was confirmed by X-ray crystallography. PPAR and μ-opioid receptor (MOR) assays were performed using reporter constructs in transfected cells. Neurite network dynamics were tested in induced pluripotent stem cells (iPSC)-derived glutaminergic neurons in culture.

Results: Tianeptine and its (S)-isomer activate PPAR-β/δ and restore neuroplasticity in neuronal culture. (S)-tianeptine is free of MOR activity. In contrast, (R)-tianeptine is a MOR agonist and lacks the ability to activate PPAR-β/δ or induce neuroplasticity.

Conclusion: (S)-tianeptine’s selective activation of PPAR-β/δ and PPAR-γ in neurons and supporting glia might be a more direct mechanism to restore neuroplasticity, compared to current monoaminergic transporter and receptor targeted therapies, which act in the synapse. These findings run counter to the proposal that the weak μ-opioid agonist activity of racemic tianeptine is central to its antidepressant effects. The new proposed mechanism that tianeptine acts as a plastogen by activating PPAR-β/δ, with both neuronal and glial activity, is consistent with its clinical effects in treating depression and promoting cognition in Alzheimer’s disease and bipolar disorder.

Funding/financial disclosures: Developmental studies were funded in total by Tonix Pharmaceuticals, Inc. The authors are employees of Tonix Pharmaceuticals Holding Corp., the parent company of Tonix Pharmaceuticals, Inc., and hold stock and/or stock options in the company.

Safety and Tolerability of KarXT (Xanomeline–Trospium): Pooled Results From the Randomized, Double-blind, Placebo-controlled EMERGENT Trials

Authors: Tejendra Ramesh Patel, PharmD;1 Stephen K. Brannan, MD;1 Andrew J. Cutler, MD;2 Sharon Sawchak, RN;1 Judith Kando, PharmD;1 Andrew C. Miller, PhD;1 Amy Claxton, PhD;1 Steven M. Paul, MD;1 Inder Kaul, MD, MPH1

Affiliations: 1Karuna Therapeutics, Boston, MA; 2SUNY Upstate Medical University, Lakewood Ranch, FL

Background/Objective: KarXT (xanomeline–trospium chloride) is a dual M1/M4 preferring muscarinic receptor agonist that lacks direct D2 dopamine receptor binding. The efficacy and safety of KarXT in schizophrenia was demonstrated in five-week, randomized, double-blind, placebo-controlled, EMERGENT-1 (NCT03697252), EMERGENT-2 (NCT04659161), and EMERGENT-3 (NCT04738123) inpatient trials in people with schizophrenia experiencing acute psychosis.

Design: In each trial, safety was assessed by a variety of methods, including monitoring for spontaneous adverse events (AEs) after administration of the first dose of the trial drug until the time of discharge on Day 35. The monitoring included a determination regarding severity and likelihood of being treatment-related. Data from the EMERGENT trials were pooled, and all safety analyses were conducted in the safety population, defined as all participants who received one or more doses of the trial drug.

Results: Across the EMERGENT trials, 51.8 percent of patients in the KarXT group (n=340), compared to 29.4 percent of those in the placebo group (n=343), reported one or more treatment-related AEs (TRAEs). The most common TRAEs, occurring in five percent or more of participants receiving KarXT and at a rate at least twice that observed in placebo, were nausea (17.1% vs. 3.2%), constipation (15.0% vs. 5.2%), dyspepsia (11.5% vs. 2.3%), vomiting (10.9% vs. 0.9%), and dry mouth (5.0% vs. 1.5%). The most common TRAEs in the KarXT group were all mild or moderate in intensity.

Conclusion: In pooled analyses from the EMERGENT trials, KarXT was generally well tolerated in people with schizophrenia experiencing acute psychosis, and findings support the potential of KarXT to be first in a new class of medications to treat schizophrenia.

Funding/financial disclosures: This trial was sponsored by Karuna Therapeutics. TRP is an employee and holds equity in Karuna Therapeutics.

The Impact of KarXT on Cognitive Impairment in Acute Schizophrenia: Replication in Pooled Data From Phase III Trials

Authors: Ian S. Ramsay,1 William Horan,1 Colin Sauder,1 Philip D. Harvey,2 Andrew C. Miller,1 Steven M. Paul,1 Stephen K. Brannan1

Affiliations: 1Karuna Therapeutics, Boston, MA; 2University of Miami Miller School of Medicine, Miami, FL

Background/Objective: KarXT is an M1/M4 preferring central muscarinic receptor agonist based on xanomeline, which has been shown to improve cognition in psychiatric populations. The Phase II EMERGENT-1 (NCT03697252) trial demonstrated that KarXT monotherapy improved cognition in a subgroup of inpatients with acute schizophrenia and clinically significant cognitive impairment. We sought to replicate this finding using pooled data from two Phase III trials.

Design: The EMERGENT-2 (NCT04659161) and EMERGENT-3 (NCT04738123) studies were randomized, double-blind, placebo-controlled, five-week inpatient trials of KarXT monotherapy in participants with schizophrenia experiencing acute psychosis. Cognition was assessed at baseline, Week 3, and Week 5 using the Cambridge Neuropsychological Test Automated Battery (CANTAB) computerized battery. Using pooled data from both trials, mixed model for repeated measures (MMRM) compared change from baseline between KarXT and placebo in the full sample and in individuals performing over one standard deviation (SD) below healthy comparison norms on the CANTAB at baseline. Linear regression assessed the relation between change in cognition and Positive and Negative Syndrome Scale (PANSS) scores.

Results: There was no significant treatment effect for KarXT (n=131) versus placebo (n=141) in the full sample. However, in the impaired subgroup, participants taking KarXT (n=69) again showed significantly greater improvement in cognition compared to placebo (n=65; least squares mean difference [LSMD]±standard error [SE]: 0.29±0.10; p<0.01; d=0.52). Change in cognition did not significantly relate to improvement in PANSS scores (p>0.12).

Conclusion: These findings replicate a KarXT benefit for cognition in a subgroup of participants with acute schizophrenia and clinically significant cognitive impairment. The cognitive improvement was not attributable to changes in clinical symptoms. Further evaluation of KarXT’s potential for cognitive enhancement in stable outpatients is warranted.

Funding/financial disclosures: This research was funded by Karuna Therapeutics. ISR is an employee and holds equity in Karuna Therapeutics.

Valbenazine Effects on the Dopamine System in Humans, as Measured by [11C]-PHNO and [18F]-DOPA Positron Emission Tomography (PET)

Authors: Ryan Terry-Lorenzo,1 Daniel Albrecht,1 Satjit Brar,1 Graham Searle,2 Frans Van Den Berg,2 Eugenii A. Rabiner,2 Oliver Howes,3 Dietrich Haubenberger1

Affiliations: 1Neurocrine Biosciences, Inc., San Diego, CA; 2Invicro, London, UK; 3Kings College, London, UK

Background/Objective: Valbenazine, a selective vesicular monoamine transporter 2 inhibitor, reduces dopamine neurotransmission by disrupting its uptake into presynaptic vesicles. This is believed to underlie valbenazine’s efficacy in treating tardive dyskinesia and chorea associated with Huntington disease. This study investigated valbenazine-induced changes in synaptic dopamine and dopamine synthesis capacity using positron emission tomography (PET).

Design: PET imaging was conducted in healthy human volunteers, each studied before and 6 to 8 hours after the administration of valbenazine (40–160mg). [18F]-dihydroxyphenylalanine (DOPA), a radiolabeled L-DOPA analog, was used to measure dopamine synthesis capacity, while [11C]-4-propyl-9-hydroxynaphthoxazine (PHNO), a radiolabeled D2/D3 agonist, measured synaptic dopamine, with increases in [11C]-PHNO nondisplaceable binding potential (ΔBPND) corresponding to decreased synaptic dopamine. Mean plasma concentrations (Cave: average concentration during PET scan) of [+]-α-dihydrotetrabenazine (HTBZ; valbenazine’s active metabolite) were matched with change from baseline in [11C]-PHNO BPND and with [18F]-DOPA influx rate constant.

Results: In participants with baseline and postvalbenazine scans ([11C]-PHNO, n=12; [18F]-DOPA, n=14), plasma [+]-α-HTBZ Cave was 10 to 60ng/mL. Eleven participants displayed valbenazine-induced, dose-dependent increases in [11C]-PHNO ΔBPND (2–44%). Higher valbenazine doses resulted in greater [+]-α-HTBZ exposure and greater ΔBPND, revealing a monotonic exposure-response relationship. For [18F]-DOPA, there were no significant differences between baseline and postvalbenazine scans and no significant associations between [18F]-DOPA endpoints and [+]-α-HTBZ exposure.

Conclusion: At therapeutic valbenazine doses, increased [11C]-PHNO ΔBPND indicated biologically meaningful decreases in synaptic dopamine. No clear effect of valbenazine was observed with [18F]-DOPA endpoints. Together, these results suggest that valbenazine’s primary mechanism is the reduction of synaptic dopamine without measurable alteration in dopamine synthesis capacity.

Funding/financial disclosures: RTL, DA, SB, and DH are employees and own stock of Neurocrine Biosciences, Inc. GS, FvdB, and EAR are employees of Invicro, which was contracted by Neurocrine Biosciences, Inc. OH is a part-time employee of H Lundbeck A/s; has received research funding and/or participated in advisory/speaker meetings organized by Angellini, Autifony, Biogen, Boehringer-Ingelheim, Eli Lilly, Heptares, Global Medical Education, Invicro, Jansenn, Lundbeck, Neurocrine, Otsuka, Sunovion, Recordati, Roche, and Viatris/Mylan; and has a patent for the use of dopaminergic imaging.

Treatment Devices and Tools

Formation of a Working Alliance and Efficacy of a Digital Therapeutic to Treat Experiential Negative Symptoms of Schizophrenia

Authors: Abhishek Pratap, PhD;1 Cornelia Dorner-Ciossek, PhD;2 Cassandra Snipes, PhD;3 Eehwa Ung, PhD;3 Brendan D. Hare, PhD;1,3 Alankar Gupta, MD, MBA;3 Shaheen E. Lakhan, MD, PhD, FAAN3

Affiliations: 1Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT; 2Boehringer Ingelheim International GmbH, Ingelheim am Rhein, Germany; 3Click Therapeutics, Inc., New York, NY

Background/Objective: The aim of this study was to explore whether patients with schizophrenia could form and maintain a patient-therapeutic alliance (known as a digital working alliance [DWA]) with a beta version of CT-155, a prescription digital therapeutic (PDT) in development (Part 1), and assess impact of use on experiential negative symptoms (ENS; Part 2).

Design: Two exploratory, single-arm, multicenter studies were conducted in adults with ENS of schizophrenia who had on-demand access to the PDT. Part 1: DWA and engagement were assessed weekly via mobile Agnew Relationship Measures (mARM) for three weeks. Part 2: Engagement with the PDT was measured, and ENS were assessed at baseline and seven weeks using Clinical Assessment Interview for Negative Symptoms Motivation and Pleasure Scale (CAINS-MAP). Safety was also assessed.

Results: Parts 1 and 2 enrolled 49 and 50 patients, respectively; 46 and 43 patients, respectively, completed the studies. In part 1, a positive DWA was established between patients and the PDT at Week 1 (mean [standard deviation; SD] mARM: 5.15 [0.7]) and maintained over three weeks (5.16 [0.8]). Patients completed a median of 15 of 18 (83%) core therapeutic lessons over three weeks (Part 1), and 18 of 21 (76%) therapeutic lessons over seven weeks (Part 2). ENS reduced significantly (p=0.004) after seven weeks (mean [SD] CAINS-MAP scores, baseline: 20.2 [8.6]; Week 7: 16.8 [7.8]; n=43). Three nonserious and nontreatment-related adverse events were reported.

Conclusion: Patients formed and maintained an effective DWA with a beta version of CT-155 over three weeks. Use of this PDT significantly improved ENS of schizophrenia. These findings and positive safety profile support advancing CT-155 into late-phase clinical development.

Funding/financial disclosures: This study was funded by Boehringer Ingelheim and Click Therapeutics. CS, EU, AG, and SEL are employees of Click Therapeutics, Inc. BDH was an employee of Click Therapeutics at the time of the study and is currently an employee of Boehringer Ingelheim Pharmaceuticals, Inc. CDC is an employee of Boehringer Ingelheim International GmbH.

Is Brain Photobiomodulation Therapy Safe and Effective in Treating Sportspeople with Acute Concussion? First Results of a Pilot Clinical Trial (RECOVERY study)

Authors: Jean-François Chermann,1 Philippe Malafosse,2 Guillaume Champleboux,3 Julie Bisiaux,4 Sara Guillemin,4 Meriem Benmerad,4 Patrice Cristofini,3 Guillaume Blivet,3 Jacques Touchon5

Affiliations: 1Georges Pompidou European Hospital, Paris, France; 2Private practitioner, Montpellier, France; 3REGEnLIFE, Paris, France; 4RCTs, Lyon, France; 5University of Montpellier, Montpellier, France

Background/Objective: The purpose of this pilot trial was to evaluate the safety of a noninvasive neurostimulation device (RGn550) using brain photobiomodulation (PBM) therapy and explore its efficacy in acute concussion (AC) by comparing two treatment parameters, 5 and 10Hz pulse frequencies. The primary objective was to evaluate the incidence of adverse device effects (ADEs), while secondary objectives related to the evolution of AC symptoms and patient recovery.

Design: This was a prospective, comparative, randomized, single-blinded, monocentric, clinical trial involving two parallel groups, both consisting of RGn550 treatment (5 or 10Hz). Fifty adult sportspeople with AC were included less than 72 hours after a concussive shock that occurred during their sport practice. They were randomized in a 1:1 ratio (stratification based on sex and concussion history), treated for 20 minutes at inclusion visit (Day 0 [D0]) and seven days after D0 (D7), and followed up for 52 days.

Results: Twenty-six patients (52%) were treated at 5Hz and 24 (48%) at 10Hz. Forty-nine patients (98%) completed the trial. At inclusion, patients were 25.0±5.1 years old on average, and 88 percent were male. The proportion of patients who had at least one ADE was 38.5 percent (n=10; 95% confidence interval [CI]: 20.2–59.4) in the 5Hz group and 41.7 percent (n=10; 95% CI: 22.1–63.4) in the 10Hz group. All ADEs were mild; none were serious. The most common ADEs were somnolence (28%) and discomfort (18%).

Conclusion: No difference in ADE incidence was evidenced between the two treatment parameters. Overall, the RGn550 device using brain PBM therapy is well tolerated.

Funding/financial disclosures: JFC and PM are investigators. JFC is a medical expert for REGEnLIFE. PM is a medical expert for REGEnLIFE, a consultant for Eye Motion, and owns equity in Kinvent. GC is an employee of REGEnLIFE. JB, SG, and MB are employees of RCTs, the contract research organization that conducted the trial on behalf of REGEnLIFE SAS. PC is CEO of REGEnLIFE and owns stock options. GB is an employee of REGEnLIFE and owns equity. JT is a consultant for REGEnLIFE, Medesis Pharma, and Ariana Pharmaceuticals. REGEnLIFE funded the trial.

Photobiomodulation Reduces Sensory-motor Deficits in a Mouse Model of Multiple Sclerosis by Dampening Inflammation and Promoting Neuroprotection

Authors: Vincent Escarrat,1,2,3 Guillaume Blivet,3 Jacques Touchon,3,4 Patrice Cristofini,3 Rémi Bos,1* Franck Debarbieux1,2,5*

*Co-corresponding authors

Affiliations: 1Institut des Neurosciences de la Timone (INT), Aix-Marseille University and CNRS UMR7289, Marseille, France.; 2Centre Européen de Recherche en Imagerie Médicale (CERIMED), Aix-Marseille Université, Marseille, France; 3REGEnLIFE, Paris, France; 4University of Montpellier, Montpellier, France; 5Institut Universitaire de France (IUF), Paris, France

Background/Objective: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease whose cause remains unknown and which has no satisfactory cure. We have set up a unique mouse model of MS, suitable for intravital microscopy, to evaluate the benefits of photobiomodulation (PBM) therapy with a noninvasive preclinical device (RGn535). Neuronal and inflammatory cell densities were dynamically monitored in situ in the spinal cord of the same animals during the time course of the disease, and these were correlated with their observed sensorimotor deficits.

Design: Dorsal glass windows were implanted on adult multifluorescent mice to allow repeated and simultaneous imaging of their spinal axons and their resident and infiltrated inflammatory cells. Three weeks later, mice were autoimmunized against the myelin oligodendrocyte glycoprotein (MOG) myelin peptide to trigger experimental autoimmune encephalomyelitis (EAE) as a model of MS. Sensorimotor deficits were monitored using rotarod and open-field behavioral tests and were correlated to spinal cell densities after EAE induction. From the first sensorimotor deficits, dorsoventral PBM treatment was applied daily for six minutes by using the RGn535 device.

Results: Densities of infiltrated inflammatory cells were found to be predictive of axonal degeneration and functional sensorimotor deficits. Their infiltration was significantly reduced by daily PBM treatment, which dampened neurodegeneration and improved sensorimotor function in EAE mice, compared to untreated mice. Importantly, daily PBM treatment did not alter sensorimotor function in wildtype mice.

Conclusion: RGn535 is a noninvasive and efficient device to manage inflammatory epochs in a preclinical model of MS. This therapeutic strategy represents an innovative and complementary tool for the symptomatic treatment of patients with MS.

Financial/funding disclosures: VE is an employee of REGEnLIFE. GB is an employee of REGEnLIFE and owns equity. PC is CEO of REGEnLIFE and owns stock options. JT is a consultant for REGEnLIFE, Medesis Pharma and Ariana Pharmaceuticals. Institut des Neurosciences de la Timone and REGEnLIFE funded the study.

Trial Methodology

A Comparison of Subject Demographic Information for Nonpsychedelic and Psychedelic Clinical Trials

Authors: Courtney Talbert; Rishi Kakar, MD

Affiliations: Segal Trials

Background/Objective: Psychedelic research poses unique questions related to participant recruitment and selection. This poster aimed to review the study populations for two studies conducted at Segal Trials’ Center for Psychedelic Research and compare them to two other nonpsychedelic studies with similar indications.

Design: Subject demographic information was collected from two psychedelic studies, MMED008 for generalized anxiety disorder and PSIL201 for major depressive disorder (MDD), and two matching nonpsychedelic studies, BNC210.012 for social anxiety disorder and 217-MDD-301 for MDD. All data captured came from subjects of Segal Trials. The focus of this research was on educational attainment, occupational status, and sex.

Results: Demographic analysis of the subjects randomized as of August 1, 2023, revealed that the majority of subjects who signed an informed consent form for MMED008 had obtained, at minimum, a bachelor’s degree (73.07%) and were currently employed (84.6%), whereas 36.36 percent of subjects screened for BNC210.013 had obtained an equivalent degree. A demographic analysis of participants in PSIL201 showed that the majority had obtained a college degree (68%) and were currently employed (72%), compared to participants in 217-MDD-301, most of whom had not obtained a college degree (72.41%) and were not employed (62%). All four studies screened more female than male individuals.

Conclusion: With psychedelic clinical trials on the rise, it is critical to reconsider how these studies are recruited, which starts with the patient population. Study sites can use this information to make adjustments to their operations, such as holding weekend and evening hours.

Funding/financial disclosures: None to report.

A Model for Demonstrating Cognitive-related Safety in Clinical Trials: The Importance of Using a Sensitive Cognitive Tool

Authors: Gary G. Kay, PhD;1 Heather G. Belanger, PhD1,2

Affiliations: 1Cognitive Research Corporation (CRC), St. Petersburg, FL; 2University of South Florida, Tampa, FL

Background/Objective: Blood alcohol content (BAC) of 0.05 percent is commonly used as a benchmark for demonstration of driving impairment. This is based on epidemiological data demonstrating an increased risk of automobile crashes at this BAC. Using data from two different studies, we demonstrate the importance of using a cognitive test in clinical trials that has similar sensitivity to detect relevant impairment.

Design: The first study dosed 18 individuals with alcohol or placebo. CogScreen subtests were administered at baseline and descending alcohol levels (0.10%, 0.07%, and 0.04% BAC). The second study was a randomized, placebo-controlled trial conducted in 36 participants. In this study, cyclobenzaprine 10mg, a sedating skeletal muscle relaxant with an effect on driving comparable to 0.10 percent BAC, served as the positive control. Three CogScreen subtests and two Cambridge Neuropsychological Test Automated Battery (CANTAB) subtests were administered at baseline and again at one-hour postdose over three days of dosing.

Results: In the first study, CogScreen demonstrated dose-related sensitivity to BAC. In the second study, reaction time variability on the CogScreen DSST was significantly increased by cyclobenzaprine (0.105 seconds least squares mean difference, p=0.008). No effects were observed for cyclobenzaprine on CANTAB subtests.

Conclusion: CogScreen was shown to be sensitive to the effects of both alcohol and cyclobenzaprine. Calibration of test results relative to alcohol might be a useful model for evaluating sensitivity of cognitive tests to central nervous system depressant effects.

Funding/financial disclosures: GK is owner of CogScreen and an employee/shareholder in CRC. HB is an employee of CRC.

Accessing the Walgreens Community of Pharmacies and Patients for Clinical Research: A One-year Retrospective Assessment

Authors: Adam Samson, Jim Carroll

Affiliations: Walgreens RWE Clinical Trials

Background/Objective: The aim of this study was to demonstrate how Walgreens Real World Evidence (RWE) Clinical Trials access for the Walgreens community of pharmacies and patients is changing the clinical research landscape.

Design: A retrospective assessment of Walgreens built out of its Clinical Trial Solutions business over the past year was established, showcasing study recruitment performance during the past 12-month period, while illustrating how Walgreens real-world data (RWD), digital outreach, point-of-care consultations, and automation capabilities were deployed. Several projects were highlighted to demonstrate rapid start-up timelines, scaling to large-volume patient outreach, recruitment diversity metrics, value of the trusted pharmacist-patient relationship, and overall portfolio performance relative to sponsor targets.

Results: Walgreens engaged with a large volume of patients in the community, conducted pharmacist-patient consultations, and generated recruitment referrals and randomizations, while demonstrating scalable engagement capabilities within compressed start-up timelines, as well as high-touch approaches. Metrics illustrate ways in which Walgreens is having a positive impact on the clinical research landscape for patients and sponsors.

Conclusion: During the past year, Walgreens RWE Clinical Trials established a new clinical trial solutions business that delivered value to sponsors, while also advancing its mission of making clinical research more accessible to diverse patients within the community.

Funding/financial disclosures: Walgreens covered all funding for this poster.

An Examination of Alternative Subject Recruitment Strategies in CNS trials

Authors: Joel Keller,1 Andria Chastain,1 Steven D. Targum2

Background/Objective: Recruitment of appropriate subjects for clinical trials is a challenging and expensive process. We conducted a systematic assessment of the effectiveness of three alternative recruitment strategies.

Design: Recruitment records from 2019 to 2022 collected by Evolution Research Group, LLC examined three different recruitment strategies: 1) traditional site-based methods (database review, community outreach, social media, digital advertising); 2) professional vendor recruitment methods (digital advertising, newsprint, direct mail, radio/ TV spots, billboards); and 3) sponsor-based campaigns that focused primarily on digital advertising. Recruitment effectiveness was defined as the percentage of subjects who proceeded toward randomization, and the cost to randomization per subject. Diagnostic categories included mood disorders, schizophrenia, posttraumatic stress disorder (PTSD), attention deficit hyperactivity disorder (ADHD), and generalized anxiety disorder (GAD).

Results: Only 2,908 of 55,722 identified individuals (5.2%) were prescreened for study participation. Traditional, site-based enrollment strategies identified significantly more potential study subjects and achieved greater recruitment effectiveness than either professional vendor programs or sponsor campaigns. Site-based enrollment strategies prescreened nearly six-times more potential subjects than either external vendor or sponsor referrals and ultimately randomized 451 of 2,315 prescreened individuals (19.5%), in contrast to 36 of 393 individuals referred by external vendors (9.2%) and 29 of 200 potential participants (14.5%) identified by sponsor campaigns (X2=26.1; df=2; p<0.0001). Where records were available, it was determined that the cost to randomization per subject was less for the site-based strategies than external vendors.

Conclusion: This preliminary exploration of recruitment data suggests that traditional, site-based methods of subject recruitment have retained value for recruitment effectiveness.

Funding/financial disclosures: JK and AC are employees of Evolution Research Group (ERG). ST is an employee of Signant Health and a consultant to ERG.

Assessing CNS Clinician Mastery and Effectiveness of Rater Training

Authors: Brian McGowan, PhD; Joel Selzer, MBA

Affiliations: Presenters are employed by ArcheMedX, Inc.

Background/Objective: The aim of this study was to determine the educational needs of central nervous system (CNS) clinicians across treatment areas.

Design: This study conducted an updated and enhanced analysis of learning data to determine the mastery of CNS clinician learners. Expanded data includes behavioral and assessment data across more than 300,000 on-demand learning sessions. Pre- and postassessment data were collected for all educational activities mapped to CNS-related clinical areas, such as Alzheimer’s disease (AD), migraine, major depressive disorder (MDD), multiple sclerosis (MS), and pain management. Analyses were performed at the activity-, learning objective-, and question-specific level to fully characterize the mastery of CNS clinicians. Preassessment data demonstrated the baseline knowledge, competence, and confidence of clinicians. Matched comparisons of pre- and postassessment data demonstrated the impact of training.

Results: The 2023 analyses revealed that the CNS clinician capability gap identified in 2022 remains. Less than 1 in 7 clinicians demonstrated baseline mastery across a range of CNS-related topics and competencies. Data consistently show more that than 80 percent of clinicians lack the clinical mastery to effectively formulate a differential diagnosis, develop individualized treatment plans, or consistently apply scales prior to participating in additional training. Assessing the ability of clinicians to understand and apply CNS-related measurements and assessments, the data revealed that only 7.6 percent of clinicians demonstrated the necessary mastery in applying scales. After completing training powered by Ready, these same clinicians demonstrated a 7.5-fold increase in their clinical mastery.

Conclusion: These data reinforce the significant training needs among CNS treating clinicians. The lack of effective training delays patient enrollment, increases clinical trial costs, and generates poor clinical trial data. Identifying and understanding training gaps is a critical step in planning for study startup, ensuring consistent application of scales and assessments, and achieving trial milestones and endpoints.

Funding/financial disclosures: Data was provided by ArcheMedX, Inc.

Assisted Cascade Testing through Outreach and Navigation (The ACT ON Trial): Clinical Assistance for Accessing Testing for Relatives of Individuals with Hereditary Germline Cancer Mutations

Authors: Emily Epstein; Melissa K. Frey, MD

Affiliations: Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY

Background/Objective: Cascade genetic testing is the process of extending genetic testing to family members of individuals with identified pathogenic germline mutations. Successful cascade testing of at-risk relatives (ARRs) improves cancer-related morbidity and mortality through cancer screening and prevention strategies. The current standard for cascade testing is patient-mediated, whereby patients are advised to contact and encourage their ARRs to undergo counseling and testing. However, recent data indicate that nearly one-third of ARRs remain uninformed of their hereditary risk, and of those informed, less then 50 percent complete genetic testing. Here, we aim to address this issue by providing navigator-mediated assistance to receive cascade testing. We hypothesize that this intervention will be more effective at facilitating genetic testing among ARRs as compared to the 36-percent success rate of standard patient-mediated cascade testing.

Design: This single-arm study evaluates the efficacy of a multicomponent facilitated cascade testing intervention. Navigators work closely with individuals diagnosed with pathogenic germline variants to identify and then contact their ARRs to provide education and guidance on accessing genetic testing. Follow-up surveys are collected at six- and 12-months following patient and ARR consent.

Results: Currently, preliminary results are not sufficient to provide statistically significant data.

Conclusion: Our ongoing study will compare the percentage of successfully contacted ARRs through the Cascade Family Navigation Program to the 36-percent success rate of standard patient-mediated cascade testing (primary outcome measure). We will also collect and analyze demographic, behavioral, and social factors from patients and ARRs (secondary outcome measures).

Funding/financial disclosures: None to report.

Assure Clinical Trials Quality While Ensuring Efficiency: Automatic Data Classification and Quality Protocol Adherence of Medical Imaging Data

Authors: Óscar Peña-Nogales, Evie Neylon, Marc Ramos, Tommy Boshkovski, Paulo Rodrigues, Vesna Prčkovska, Kire Trivodaliev

Affiliations: QMENTA, Inc., Boston, MA

Background/Objective: Imaging biomarkers can be derived from multiple medical imaging modalities and are helpful for assessing the safety and effectiveness of clinical trials. However, the diversity of medical image modalities creates complexity for archival systems. Furthermore, acquisitions must be in compliance with the imaging charter to ensure the trial’s quality. Thus, we propose an automatic data classification and quality protocol adherence (QPA) approach for medical imaging data named Smart-Uploader.

Design: The Smart-Uploader is integrated within a centralized, cloud-based platform for medical image data management and analysis. Upon data acquisition and upload, the Smart-Uploader automatically deidentifies the data and extracts the meta-information. Next, a combination of a meta-information-based deterministic heuristics and convolutional neural network is employed to classify the provided data. Finally, based on a set of rules predefined in the imaging charter the Smart-Uploader evaluates the compliance of the data to the imaging protocol.

Results: The Smart-Uploader can classify more than 25 imaging modalities. Furthermore, the QPA assesses the meta-information by applying 50 rules to output a pass/fail summary. An across-vendors comparison is performed avoiding human error. In a Phase II trial with 100 patients and 13 sites with varying MR units. Burden reduction in data collection was 83 percent, with increased site responsiveness and engagement, resulting in a collection of 95 percent of data planned.

Conclusion: The proposed solution for automatic medical image data classification and protocol adherence facilitates data management and identification of protocol deviations, which increases the quality of imaging endpoints and efficiency in clinical trials and generates time-savings.

Funding/financial disclosures: The presenters are employed and own stocks or hold options of QMENTA.

Bipolar Disorder: Patient-centered Experiences

Authors: Dan Brenner, Steve Wimmer

Affiliations: 1nHealth, Orlando, FL

Background/Objective: This abstract describes a Phase II, interventional, 20-site psychiatric study evaluating a novel intervention for a novel patient population in those with treatment-resistant bipolar depression with subacute suicidal ideation defined by bipolar depression (Montgomery–Åsberg Depression Rating Scale [MADRS] ≥30) and subacute suicidal ideation (Columbia Suicide Severity Rating Scale [C-SSRS] 3 or 4, no hospitalization).

Design: Given the first-of-its-kind nature of the patient population (those positive for suicidal ideation), both patient materials and the enrollment process were highly scrutinized by 1nHealth and the sponsor to focus on patient safety and clear expectations. 1nHealth deployed licensed mental health practitioners to conduct secondary phone screenings; two-thirds of patients were contacted within an hour of qualification. Integrated scheduling and close monitoring of sites ensured patients were shepherded to the next step with care.

Results: Twelve weeks from recruitment going live, enrollment rates doubled from the prior 12 weeks, despite 1nHealth being the third recruitment vendor on the study. 1nHealth tracked key metrics to identify high-performing supersites, which represented only four percent of the total population available across all sites, yet were able to contribute to 50 percent of the consented patients over the first 12 weeks postlaunch.

Conclusion: Patient-centric pacing and a well-executed chatbot flow emerged as vital components, emphasizing the importance of tailored experiences. Strategic advertisement deployment, aligned with nursing staff availability, showcased the significance of timing. Seamless hand-offs via a shared platform demonstrated the value of a cohesive approach. Priority communication, along with multiple touchpoints, fostered an environment for successful outreach attempts and ultimately meaningful down funnel enrollment contribution.

Funding/financial disclosures: None to report.

Bringing Our Patients Voice into Clinical Trials at Regeneron

Authors: Joseph Im, Roland Barge

Background/Objective: We aimed to bring our patients’ voices into clinical trials through user experience research (UXR) and design thinking to influence the collaborative development of innovative digital health technologies (DHTs), thus improving the clinical trial journey for our patients.

Design: This study integrated UXR into DHT development and operational strategy by building empathy and understanding of our patients’ lived experiences and employing design thinking to improve those experiences. Evidence feasibility, impact, and subsequent benefits of UXR-based implementations to DHTs or operational processes.

Results: Persona work for Black cultural needs identified that a majority of Black individuals were aware of clinical trials via the internet or their doctor, but did not trust the pharmaceutical industry for clear, reliable information. There was variation on site and for patient acceptance of each DHT, likely due to the familiarity of the technology and the perceived impacts on their lives. DHT patient devices tended to focus on the technology implementation and analytical validation, and as such are not always designed with acceptance and usability in mind.

Conclusion: UXR uses omnichannel feedback, collaborative device codesign, and iterative design thinking processes to build empathy and understanding, which helps define our patients’ needs, motivations, and behaviors for incorporation into our clinical trials. UXR can help identify and implement key DHT solutions that are functional, inclusive, and usable, meet the needs of patients, and improve the clinical trial experience.

Funding/financial disclosures: Not provided.

Building Resiliency into the Management of CNS Clinical Trials: Mitigating Challenges in the COVID-19/Post-COVID-19 Era

Author: David Krefetz, DO, MBA; Samara Debouk-Ktesh, BSc; Zelma Gandy-Don Sing, PhD; Talar Hopyan, PhD; Patrick Keenan, MD; Leslie Moldauer, MD, MBA; Andy Moniz, MS; Alexandria Wise, PhD

Affiliations: Syneos Health

Background/Objective: Since March 2020, there have been multiple forces disrupting the operations of global clinical trials. Examples include the effects of the worldwide response to COVID-19, the Russia/Ukraine conflict, site consolidation and staffing issues, and a generational change in the expectations of study participants. While some recent clinical trial failures have been attributed to these forces, during the same period, there have been successful large global trials with positive results. It is important to determine how the challenges facing these successful trials during this span of years were successfully mitigated and managed to provide learning for future clinical development programs.

Design: The authors will examine several recent clinical development programs with positive results, looking at the challenges that presented and the management efforts that led to successful mitigation of those challenges.

Results: The challenges of each individual program will be presented, along with the specific strategies used to both prevent and manage these challenges.

Conclusion: Challenges to clinical trials since the start of the COVID-19 pandemic can be successfully managed. The authors will identify strategies for resilience in the conduct of central nervous system clinical trials. Recommendations for the future conduct of trials will be made.

Funding/financial disclosures: All presenters are full-time employees of Syneos Health. DK, ZG-DS, TH, LM, AM, and AW are shareholders of Syneos Health.

Collaborative Development and Validation of an Enhanced Seizure eDiary for Clinical Trials

Authors: Chris Brady,1 Shelly Steele,1 Lindsey Christy,1 Michael Cioffi,1 Amee Patel,1 Dorothee Schoemaker,1 Lydia Hatfield,1 Bree DiVentura,2 Meryl Lozano,2 Jacqueline French2

Affiliations: 1Full-time employees of WCG. 2Epilepsy Study Consortium, Inc.

Background/Objective: This study aimed to create an innovative seizure electronic diary (eDiary) using lessons learned from prior studies to enhance data quality and user friendliness for patients, caregivers, and investigators.

Design: The eDiary’s initial specifications were shaped through collaborative sessions between a team of industry and technological experts and the Epilepsy Study Consortium, Inc. (ESCI) Working Group, consisting of epilepsy clinical trial experts and pharmaceutical representatives. Input from the Working Group guided the creation of initial eDiary mockups, followed by iterative feedback cycles. Focus sessions with patients with epilepsy provided insights into eDiary functionality. ESCI clinicians and the Working Group tested the eDiary, leading to further iterative refinements. Post-initial development, semistructured interviews were conducted with 10 patients and 10 patient caregivers. Cognitive debriefing and usability testing was conducted in alignment with regulatory focus on patient input and patient-reported outcome (PRO) best practices. Cognitive debriefing evaluated the eDiary’s clarity and user comprehension. Usability testing assessed ease of user interaction.

Results: Patients found the eDiary instructions and content relevant. Cognitive debriefing results included 21 suggested minor modifications. Eighteen were implemented, two will be addressed in training, and the remaining one was preferential. Usability testing results included six suggested minor modifications. Three will be addressed in training, and three were preferential.

Conclusion: Collaborative efforts were successful in creating a seizure eDiary optimized for clinical trials. The qualitative research provided supportive evidence of the content validity of the seizure eDiary to capture information about subjects’ seizure experiences to evaluate the efficacy of an investigational product in clinical trials.

Funding/financial disclosures: SS, LC, MC, AP, DS, LH, and CB have none to report. BD and ML are employees of the Epilepsy Study Consortium, Inc. Within the past year, the Epilepsy Study Consortium has received funding for research support, meeting support and services provided from the following companies: Agrithera, Inc., Alterity Therapeutics Limited, Anavex, Angelini Pharma S.p.A., Arvelle Therapeutics, Autifony Therapeutics Limited, Baergic Bio, Inc., Beacon Biosignals, Inc., BiocodexTherapeutics, Inc., Biogen, Biohaven Pharmaceuticals, BioMarin Pharmaceutical, Inc., Bloom Science, Inc., BridgeBio Pharma, Bright Minds Biosciences, Inc., Camp4 Therapeutics Corporation, Cerebral Therapeutics, Cerevel, Coda Biotherapeutics, Cognizance Biomarkers, Crossject, Eisai, Eliem, Empatica, Encoded Therapeutics, Engage Therapeutics, Engrail, Epalex, Epihunter, Epitel Inc., Epygenix Therapeutics, Equilibre BioPharmaceuticals, Genentech, Inc., Greenwich Biosciences, Grin Therapeutics, GW Pharma, Janssen Pharmaceutica, Jazz Pharmaceuticals, Knopp Biosciences, Korro Bio, Inc., Lipocine, LivaNova, Longboard Pharmaceuticals, Lou Lou Foundation, Lundbeck, Marinus, Modulight.bio, NeuCyte, Inc., Neumirna Therapeutics, Neurelis, Neurocrine, Neuroelectrics USA Corporation, Neuronetics, Inc., NeuroPro Therapeutics, NxGen Medicine, Inc., Ono Pharmaceutical Co., Otsuka Pharmaceutical Development, Ovid Therapeutics ,Inc., Paladin Labs, Inc., Passage Bio, Pfizer, Praxis, Pre-Ev, Precisis GmbH, PTC Therapeutics, PureTech LYT Inc, Rafa Laboratories, Ltd., Rapport Therapeutics, Inc., Receptor Holdings Inc., Sage Therapeutics, Inc., SK Life Sciences, Stoke, Supernus, Takeda, Third Rock Ventures LLC, UCB Inc., Ventus Therapeutics, Vida Ventures Management, Xenon Pharmaceuticals, and Zogenix. JF consults for Agrithera, Inc., Alterity Therapeutics Limited, Anavex, Angelini Pharma S.p.A., Arvelle Therapeutics, Autifony Therapeutics Limited, Baergic Bio, Inc., Beacon Biosignals, Inc., Biogen, Biohaven Pharmaceuticals, BioMarin Pharmaceutical, Inc., Bloom Science, Inc., BridgeBio Pharma, Bright Minds Biosciences, Inc., Camp4 Therapeutics Corporation, Cerebral Therapeutics, Cerevel, Coda Biotherapeutics, Cognizance Biomarkers, Crossject, Eisai, Eliem Therapeutics, Encoded Therapeutics, Engage Therapeutics, Engrail, Epalex, Epihunter, Epitel, Inc., Equilibre BioPharmaceuticals, Genentech, Inc., Greenwich Biosciences, Grin Therapeutics, GW Pharma, Janssen Pharmaceutica, Jazz Pharmaceuticals, Knopp Biosciences, Korro Bio, Inc., Lipocine, LivaNova, Longboard Pharmaceuticals, Lundbeck, Marinus, Modulight.bio, NeuCyte, Inc., Neumirna Therapeutics, Neurelis, Neurocrine, Neuroelectrics USA Corporation, Neuronetics, Inc., NeuroPro Therapeutics, NxGen Medicine, Inc., Ono Pharmaceutical Co., Otsuka Pharmaceutical Development, Ovid Therapeutics, Inc., Paladin Labs, Inc., Passage Bio, Pfizer, Praxis, PureTech LYT, Inc., Rafa Laboratories Ltd., Rapport Therapeutics, Inc., Receptor Holdings Inc., Sage Therapeutics, Inc., SK Life Sciences, Stoke, Supernus, Takeda, Third Rock Ventures LLC, UCB, Inc., Ventus Therapeutics, Vida Ventures Management, Xenon Pharmaceuticals, and Zogenix. All consulting is done on behalf of the Epilepsy Study Consortium, and fees are paid to the consortium. NYU receives salary support from the consortium. JF has also received research support from the Epilepsy Study Consortium (funded by Andrews Foundation, Eisai, Engage, Lundbeck, Pfizer, SK Life Science, Sunovion, UCB, Vogelstein Foundation) Epilepsy Study Consortium/Epilepsy Foundation (funded by UCB), GW/FACES, and NINDS; is on the editorial boards of Lancet Neurology and Neurology Today; is Chief Medical/Innovation Officer for the Epilepsy Foundation; and has received travel/meal reimbursement related to research, advisory meetings, or presentation of results at scientific meetings from the Epilepsy Study Consortium, the Epilepsy Foundation, Angelini Pharma S.p.A., Biohaven Pharmaceuticals, Cerebral Therapeutics, Neurelis, Neurocrine, Praxis, Rapport, Stoke, Takeda, and Xenon.

Ecological Momentary Assessments (EMAs) as Outcome Measures: Convergence with Gold Standard Primary Outcomes

Authors: Dan DeBonis,1 Charles Nemeroff,2 Phil Harvey3

Affiliations: 1EMA Wellness, Boston, MA; 2Dell Medical School The University of Texas at Austin, Austin, TX; 3University of Miami Miller School of Medicine, Miami, FL

Background/Objective: Early phase central nervous system (CNS) studies are often underpowered for statistical significance on gold standard clinician-reported outcomes (ClinROs). An alternative, cost-efficient strategy is dense sampling with ecological momentary assessments (EMAs), which increases power and allows for regular assessments between clinic visits. EMAs provide highly accurate measures of symptom severity that can be collected in real time. EMAs have shown convergence with primary endpoints in negative symptoms (p<0.001, 16-item Negative Symptom Assessment [NSA-16] change) and depression (p<0.001, Hamilton Depression Rating Scale [HAM-D] change). Adherence rates to at least one daily EMA was over 70 percent in both studies.

Design: Data presented is from an open-label treatment major depressive disorder (MDD) study of 13 participants, featuring sampling of daily EMA active and passive assessments. Hamilton Anxiety Rating Scale (HAM-A), Montgomery–Åsberg Depression Rating Scale (MADRS), and Clinical Global Impressions-Severity (CGI-S) were assessed weekly at eight timepoints. Twice daily EMAs (BYOD application) assessed functioning, activities, and mood for eight weeks, using modified HAMD-6 and GAD-7. Actigraphy measured steps.

Results: A total of 658 EMA assessments were completed by 13 participants, with a high daily adherence rate above 70 percent. Concurrent correlations (paired sample t-tests) of MADRS and EMAs ranged from 0.53 (Day 29) to 0.83 (Day 15). Effect sizes of change (baseline to Week 6, paired sample t-tests) were significant (p<0.01) for MADRS, HAM-A, and EMA mood assessments.

EMA results anticipated future clinical ratings. Lagged correlation of Week 6 MADRS and prior week EMA assessment was 0.78. Lagged correlation of EMA measuring productive activities predicted subsequent MADRS score changes.

Conclusion: The convergence of EMAs with ClinROs confirm the pattern of correlation in multiple therapeutic areas and symptom clusters.

Funding/financial disclosures: Not provided.

Enterprise-wide Initiatives for Increasing Diversity, Equity, and Inclusion at Sponsor Pharmaceutical Companies

Authors: Stacey Versavel, Elyse Skenderian, Jack Homsher, Ken DiPietro, Janna Muhlhausen, Raymond Sanchez

Affiliations: Cerevel Therapeutics, Cambridge, MA

Background/Objective: Diversity, equity, and inclusion (DEI) describes programs, guidelines, and policies that encourage the representation and participation of diverse populations of people. Developing a diverse workforce is designed to ensure different perspectives and ideas when making decisions, which will in turn drive the best discussions, ideas, and outcomes.

Design: Cerevel Therapeutics is a pharmaceutical company committed to developing a diverse workforce, with corresponding corporate goals. Cross-functional initiatives to encourage employees to embrace DEI values include training on building an inclusive workplace. The Women’s Leadership Program and Employee Resource Groups offer opportunities to network and attract diverse talent, fostering mentoring, and career development. Cerevel also focuses on building equity and opportunity through its supplier diversity efforts. By also incorporating strategies to improve diverse representation in clinical trials, Cerevel is facilitating inclusion of real-world patient populations and access to investigational pharmacotherapies.

Results: Company-wide initiatives have been successful, with recruitment of a diverse community of new hires, including diversity of race and gender. Current employees also completed DEI workshops. Almost all new spend commitments were allocated to suppliers with active DEI programs and commitments. A guidebook to address potential barriers to participation of diverse populations in clinical trials was also developed to reflect the commitment to patient advocacy efforts.

Conclusion: Cerevel seeks to be on the forefront by leveraging the United States (US) Food and Drug Administration’s (FDA’s) draft guidance for industry and enacting enterprise-wide initiatives that represent a culture invested in DEI. A Cerevel core value is mosaic vision, a belief that the company culture will be leveraged through the breadth and diversity of the strengths brought and created for colleagues to be their authentic selves while making a positive impact in industry.

Funding/financial disclosures: Not provided.

Evolving a Psychedelic Facilitator Training Program to Support a Multisite, Global Clinical Trial

Authors: Alex Kelman, Melissa Field, Ingmar Gorman, Allison House-Gecewicz, Robert Mino, Doug Drysdale, Aaron Bartlone, Amir Inamdar

Affiliations: Cybin, Inc. and Fluence

Background/Objective: As psychedelic drug development programs advance into pivotal trials, it is critical to ensure that facilitator/therapist training programs are scalable to support these multisite, global studies. The aim of this poster is to provide blueprints on the evolution of the EMBARK Training Program to EMBARK Clinical Trials (EMBARKCT). EMBARKCT leverages the core elements of the original program and adapts the pedagogy to address scalability challenges.

Design: This poster outlines the core components of the EMBARK model and original EMBARK Training Program to give the audience a conceptual understanding of the original pedagogical elements that were adapted.

Results: EMBARKCT addresses scalability challenges of the original training program, which included ongoing competency assessment/certification during trial conduct and undue time burden for facilitators who have already received similar and extensive psychedelic facilitation trainings. To address the first challenge, the EMBARKCT model includes training elements to be delivered by an experienced training organization, embedding both qualification and certification into the training prior to study start. To address the second challenge, training assets are streamlined to reduce the time burden on previously trained facilitators, while retaining necessary EMBARK pedagogical elements. The adapted training program will be presented in depth and highlight key strategies for the EMBARKCT scalable training model. This adapted approach allows for certification to happen during training, as opposed to during mandatory supervision during the trial.

Conclusion: EMBARKCT will allow for streamlined, scalable pedagogy without sacrificing necessary elements of a robust training program. Other sponsors may benefit from considering similar adaptations to streamline their programs.

Funding/financial disclosures: AK, AH-G, RM, DD, AB, and AI receive financial compensation as employees of Cybin, Inc. MF receives compensation as a consultant of Cybin, Inc. IG receives financial compensation as an employee of Fluence.

Examining Subjects with Extremely Low PANSS Scores in Acute Schizophrenia Clinical Trials

Authors: Alan Kott, Xingmei Wang, David Daniel

Affiliations: All authors are employees of Signant Health.

Background/Objective: In the current post hoc analysis of acute schizophrenia trials, we assessed the frequency of occurrence of extremely low Positive and Negative Symptom Scale (PANSS) total scores and investigated whether subjects reaching this level of improvement differ from the other subjects.

Design: Data were extracted from 19 double-blind, placebo-controlled, schizophrenia clinical trials. Subjects with PANSS total score below 40 points were flagged. For PANSS and Marder Factor scores, we tested whether these subjects differed at screening and baseline, compared to the nonflagged raters, using GLM models.

Results: PANSS scores below 40 were identified in 231 of 50,120 PANSS assessments (0.4%), affecting a total of 114 of 7,154 subjects (1.6%). In the flagged group, the PANSS score was significantly lower at screening and baseline, by 5.5 and 6 points, respectively. The Positive and Hostility factors did not differ at screening and baseline. The Negative factor was significantly lower at screening and baseline, by 2.0 and 2.1 points, respectively. Slightly smaller but still significant differences were observed in the Disorganized factor (1.6 and 1.8 points) and Anxiety-depression factor (1.4 and 1.0 points) at both screening and baseline, respectively.

Conclusion: Subjects with a total PANSS score of 40 or less postbaseline exhibited significant differences in symptom severity at the time of randomization. The differences were most pronounced in the Negative, Disorganized, and Anxiety-depression factors, raising concerns about whether these subjects are diagnosed correctly or potentially represent a meaningfully different phenotype of schizophrenia.

Funding/financial disclosures: None to disclose.

Global Raters’ Work Stress and Task Burnout: An Empirical Exploration of Our Primary Endpoint Evaluators

Authors: Elan A. Cohen,1 Judith Montero,2 Vera M. Grindell,3 Katarzyna Wyka,4 Howard A. Hassman,1 David P. Walling,3 Cassie L. Blanchard,1 Mark G. Opler,5 David Mischoulon,6 Larry Ereshefsky2,7

Affiliations: 1CenExel Hassman Research Institute; 2CenExel Clinical Research; 3CenExel Collaborative Neuroscience Network; 4The City University of New York, Graduate School of Public Health and Health Policy; 5WCG, Inc. and The PANSS Institute; 6Massachusetts General Hospital, Harvard Medical School; 7Retired Professor, The University of Texas

Background/Objective: Psychometric raters are responsible for generating critical findings for clinical trials, including primary efficacy data. After conducting a thorough review of the literature, however, no study could be located examining work stress, burnout, and various rater tasks, which may contribute to compromised productivity and reduced data quality. A global survey was conducted to learn more about burnout and stress among global raters.

Design: A 39-item Site Rater Stressors Survey (SRSS) was sent to obtain demographics and perceptions of rater job stress, burnout, and work impact. Three rater training and surveillance companies in our industry emailed the SRSS link to raters who have participated in previous clinical trials. Raters were informed about the purpose of the survey, how their contacts were obtained, the voluntariness and anonymity of participation, and the 10-minute duration of completion.

Results: The SRSS was completed by 529 global raters (from the United States, Europe, South America, Japan, etc.). The most commonly reported stressor was dealing with technology, followed by scoring training videos for certification, which was also judged as significantly more distressing than other rater tasks. A notable proportion of raters (n=174; 33%) reported moderate or higher levels of current burnout, with 178 (34%) reporting such distress causing at least moderate interference in their personal life.

Conclusion: Given that a substantial number of global raters reported job stress and burnout, in addition to an analysis of the evaluated stressors, recommendations will be provided regarding how different sectors of the industry can work to reduce rater overload.

Funding/financial disclosures: None to report.

Hybridized Approach to Transcription of Speech Significantly Reduces Processing Time While Preserving the Accuracy of Human Transcription

Authors: Rachel Kindellan, Rachel N. Newsome, Jordan Ponn, Aaron Rambhajan, Sasha Sirotkin, William Simpson, Celia Fidalgo

Affiliations: Cambridge Cognition

Background/Objective: The aim of this study was to investigate the speed and accuracy of manual, semi-automated, and fully automated transcription of clinical speech samples to determine the suitability of each method by speech type for use in speech-based biomarkers.

Design: Eight speech samples (speech type: open-ended speech [n=4], fluency tasks [n=4]) were randomly selected from an internal data set and transcribed three ways (transcription method): manual, semi-automated (human-reviewed, automatically generated transcript), and automated (automatic speech recognition [ASR] without human review). We analyzed the speed (ratio of time worked on an audio sample to the audio sample duration) and accuracy, calculated via word error rate (WER).

Results: In general, semi-automated transcription was significantly faster than manual transcription [F(1,54)=8.39, p=0.005], while manual and semi-automated transcription were significantly more accurate than ASR [F(2,60)=4.51, p=0.02]. However, speed and accuracy depended on the type of speech sample. Semi-automated transcription for open-ended speech samples yielded significant gains in speed with comparable accuracy to manual transcription. However, semi-automated transcription of fluency tasks was significantly slower than manual transcription, owing to the high volume of errors (low accuracy) produced by the first pass of ASR.

Conclusion: These results support the use of semi-automated transcription to significantly enhance transcription speed without a loss of accuracy for open-ended speech tasks.

Funding/financial disclosures: All authors are employees of Cambridge Cognition, LLC.

Implementation of Continuous Respiratory Monitoring During Postanesthesia Recovery in a Clinical Trial

Authors: Jasmin Imsirovic,1 Ariel V. Dowling,1 Andrew Kaseman,1 Marta Karas,1 Max Tolkoff,1 Danielle Sullivan,1 Mateusz Piksa,2 Rebecca Wu3

Affiliations: 1Data Sciences Institute, Takeda Pharmaceuticals, Inc., Cambridge, MA; 2Clinical Science, Neuroscience, Takeda Pharmaceuticals International AG, Glattpark-Opfikon, Switzerland; 3Clinical Science, Neuroscience, Takeda Pharmaceuticals, Inc., Cambridge, MA

Background/Objective: Objective monitoring during the post-anesthesia recovery period following surgery is crucial to identify respiratory depression in patients with obstructive sleep apnea (OSA). Continuous signals, such as respiratory rate and blood oxygen saturation, are commonly used for this purpose. However, these measurements may contain artifacts that could result in false alarms. The goal was to develop a standardized process to collect, review, and analyze continuous respiratory data during post-anesthesia recovery in an interventional drug development clinical trial. We aimed to minimize artifacts and identify only true respiratory events through high quality data collection and expert adjudication of events.

Design: A hospital-grade respiratory monitor was used to collect capnography and pulse oximetry signals. Study specific manuals and trainings were created to standardize the data collection process, and respiratory signals were checked in real-time by trained staff. Following upload from sites, data were reviewed programmatically and manually to assess quality and identify potential issues. Finally, an adjudication committee scored individual events that met the criteria for respiratory depression and identified artifacts.

Results: Each module in the process underwent iterative building and testing, leading to successful user acceptance testing and transmission of live data. This process is currently implemented in an ongoing clinical trial, expanding to 19 sites across the United States (US).

Conclusion: Using a combination of methods for data collection, review, and analysis, we established a continuous respiratory monitoring process that adheres to good clinical practice and can impartially reject artifacts. Our approach enabled high quality data collection in the study.

Funding/financial disclosures: Not provided.

In Alzheimer’s Disease Study Recruitment, Scheduling Lag Impacts Prescreen Attendance, Cancellations, and No-show Rates

Authors: Yu-Jay Huoh, PhD; Brenda Martinez; Jennifer Mitolo, PsyD; Kristen Jade Sanchez; Elizabeth Sosa, PhD; Ralph Lee

Affiliations: Irvine Clinical Research

Background/Objective: In this study, we examined the impact of the number of days between when a prescreening appointment was created and the actual scheduled date (i.e., scheduling lag) on key recruitment metrics —attendance, cancellation, and no-show rates—in potential Alzheimer’s disease (AD) study participants.

Design: Between January and August 2023, 2,322 potential study participants with AD were scheduled for prescreening appointments. These potential participants were recruited through advertisements on Facebook, Instagram, and Google. After a brief phone screen for basic eligibility criteria, in-person prescreening appointments were scheduled. Reminder messages were sent in the days leading up to the appointment.

Results: The prescreening appointments were scheduled anywhere from same day up to 21 days in the future. Mean scheduling lag was 10.5 days (median: 9 days, standard deviation [SD]: 5.9 days). Scheduling lag had a conclusively significant impact on nearly every performance metric, including attend rate (β=-0.034, p<0.00001), cancellation rate (β=0.035, p<0.0001), and no-show rate (β=0.038, p<0.00001). This was driven by sharp performance improvements for appointments scheduled within 5 to 7 days.

Conclusion: Research sites are increasingly relying on advertising to recruit trial participants for traditionally difficult-to-recruit-for conditions, such as AD. Because of this shift, sites need to monitor how cost effective these campaigns are. A key driver for successful recruitment is attendance rate (and a reduction in cancellations/no-shows), and sites can improve this by decreasing scheduling lag to less than seven days.

Funding/financial disclosures: All presenters are employees of Irvine Clinical Research, an independent central nervous system (CNS) research site that conducts industry-sponsored pharmaceutical trials.

Innovative Imaging Platform Technology’s Impact on Reading Center Workflow Efficiencies in Global Oncology Clinical Trials: EXCELSIOR™ and the STAR Project

Authors: Seokyeong (Gene) Kim, PharmD, Clinical Scientist; Catherine Chintala, Project Manager, Oncology

Affiliations: MERIT CRO, Inc.

Background/Objective: The aim of this study was to examine how an integrated, comprehensive, cloud-based imaging platform could address challenges in oncology clinical trials, including lack of visibility and transparency, limited access to data and images, and missing statuses of subjects and timepoints.

Design: The System Test and Review (STAR) pilot study was implemented in MERIT’s EXCELSIOR imaging platform to enable a randomized solid tumor trial using RECIST 1.1 reading criteria. A pool of radiologists in three regions (United States, Europe, and China) read sample scans according to a blinded, two-reader, sequential locked timepoint read paradigm. This 2+1 paradigm automatically randomized each independent reader (Reader 1, Reader 2, and Adjudicator), so reads were allocated evenly. The reader pool was chosen to reflect common international study designs and test the system from multiple locations, as well as accessing different network servers.

Results: The EXCELSIOR platform enhanced real-time tracking of image workflow, processing, and read status; increased visibility and transparency across reader locations; and kept study milestones on track. It enabled readers and team members to work collaboratively from multiple global locations and provided 100-percent access to data and images on-demand. MERIT’s geodispersed servers and backup systems ensured 99.9-percent uptime and helped overcome the challenge of keeping patient data within country, as required for China and as per data privacy regulations.

Conclusion: EXCELSIOR resulted in reader workflow efficiencies in the STAR project by increasing data transparency, maintaining study milestones, and providing greater access to images and data. It also supported and improved worldwide collaboration among readers and other stakeholders.

Funding/financial disclosures: SK and CC are both employed at MERIT CRO, Inc.

Integration of Genetic Screening to Accelerate Clinical Trial Success

Authors: Ashley Cannon, Sean Sigmon

Affiliations: InformedDNA, St. Petersburg, FL

Background/Objective: Clinical trials employing preselection biomarkers have higher success rates. Clinical operations often benefit from genetic experts who can select appropriate genetic tests, identify relevant testing laboratories, and interpret genetic test results for trials with genetic eligibility criteria. Here, we describe the integration of genetic prescreening for a clinical trial to ensure genetic eligibility criteria is met.

Design: Genetic counseling and screening services were integrated into a recruiting and prescreening funnel for a clinical trial targeting a rare neuromuscular disease sponsored by a leading biopharmaceutical company. A patient identification services group functioned as an outsourced clinical research coordinator (CRC). Individuals that met basic criteria, including a clinical diagnosis of the rare disease, were referred to InformedDNA for genetic services.

During a telehealth appointment, genetic counselors provided disease education, reviewed any previous genetic testing reports, ordered genetic testing as needed, disclosed test results and implications, discussed the clinical trial, and referred individuals that met genetic eligibility criteria to clinical trial sites.

Results: The CRC recruited 377 individuals and referred 216 to InformedDNA. InformedDNA completed 205 genetic counseling appointments. A total of 164 individuals had previous genetic testing; 16 required updated clinical genetic testing. Genetic testing was ordered for 36 individuals without previous testing. Fifteen individuals did not meet genetic eligibility criteria, one of whom received a genetic diagnosis for a different rare neuromuscular disease. A total of 179 individuals (96% of individuals that met genetic eligibility criteria) elected to be referred to a clinical trial site.

Conclusion: Screening patients for clinical trials with a genetic eligibility component is complicated. Genetic experts can efficiently be integrated into the screening workflow to order and review genetic tests. Individuals who receive genetic prescreening are engaged and trial-ready.

Funding/financial disclosures: The presenters are full-time employees of InformedDNA.

Know Where Your Subjects Have Been: Use of a Subject Registry at Prescreen in a Large Site Network

Authors: CB Steinmetz,1 TM Shiovitz,1,2 BL Steinmiller,1 LC Trout1

Affiliations: 1Cenexel – CTSdatabase, LLC, Sherman Oaks, CA; 2Cenexel – California Neuroscience Research, Sherman Oaks, CA

Background/Objective: This study aimed to identify and examine the use of a subject registry on the identification of duplicate, professional, or otherwise inappropriate subjects at the prescreening visit for CenExel, the largest therapeutically focused site network.

Design: We looked at pooled study data for all subjects that prescreened at a site within the CenExel site network from January to July 2023. The number of matches (i.e., subjects who presented to a unique site) found within 30 or 90 days was collected. Matches between “sister sites” (i.e., those where prescreening might take place at more than one location) were not included as matches in the analysis. The subject registry used was CTSdatabase, one of several commercially available subject databases.

Results: Of 9,268 CenExel network subjects prescreened using CTSdatabase from January to July 2023, 202 unique site matches (2.2%) were found for these subjects within 30 days of the prescreening visit, and 525 unique site matches (5.7%) were found for these subjects within 90 days of the prescreening visit.

Conclusion: Use of the CTSdatabase subject registry during the prescreening process can eliminate duplicate and professional subjects from a large site network before they are ever screened for a study. This enhances subject quality and may provide significant cost savings (in the form of screen-failures) to sponsors as well.

Funding/financial disclosures: Not provided.

Leveraging Subject Matter Experts for Exceptional Quality Control in a Multicenter Clinical Trial

Author: Rachel Rangel, AuD; Clinical Operations

Affiliations: Employee of Curavit Clinical Research

Background/Objective: A regenerative medicine startup engaged Curavit Clinical Research to design and execute a unique quality control and endpoint adjudication process for their pivotal Phase II trial for adults with sensorineural hearing loss.

Design: The study was designed to enroll 142 participants at 28 sites across the United States (US). Curavit devised a solution to allow subject matter experts (audiologists) to complete fully remote reviews of the study sessions for quality assurance. The subject matter experts performed extensive data review, including source data verification, on an ongoing basis with a level of precision and scrutiny only attainable by someone with their expertise.

Results: In this study, we developed a smartphone-based technology solution to record study visits; performed quality control, independent scoring, and adjudication of 100 percent of recorded assessments; detected issues in 81 percent of the 932 study visits; provided tailored feedback to study staff to improve protocol adherence so errors could be corrected as soon as they were discovered, resulting in a notable decrease in the frequency and severity of errors as the study progressed; and identified errors in data collection and data entry that were not detected by automatic checks or by traditional clinical research associates. Curavit’s rigorous quality control allowed the sponsor to have high confidence in the validity of the study results.

Conclusion: The audience will learn the value of utilizing subject matter experts to greatly improve data quality and study efficiency. They will learn techniques for incorporating subject matter experts into each phase of study planning and execution.

Funding/financial disclosures: None to report.

Marijuana Use Among Potential Major Depressive Disorder (MDD) Clinical Trial Participants

Authors: M Evans, S Nicholas, H Zandi, S Ellickson, K Blodgett, S Desjardins, D Domilici, V Photos

Affiliations: Adams Clinical

Background/Objective: Clinical trials for major depressive disorder (MDD) often exclude individuals who use marijuana, and yet studies suggest marijuana use might be more common among those with MDD. The goal of this study was to assess rates of marijuana use among the MDD trial-seeking population and examine the relationship between marijuana use and trial eligibility and screening.

Design: Prospective participants were recruited by social media advertising. After completing a phone screening interview, potentially eligible subjects were scheduled for an in-person prescreening appointment, at which they underwent a urine drug screen and were assessed for trial eligibility. Analyses focused on comparing trial eligibility and screening among participants who tested positive for cannabinoids only (THC+) and those who tested negative for cannabinoids and all illicit substances.

Results: A total of 24.7 percent of subjects were THC+ at their prescreening visit. Subjects who were THC+ were significantly less likely to ultimately screen for an industry-sponsored trial (β=-0.10, p<0.001), even among those who were initially found eligible at prescreening (β=-0.11, p=0.004). The overall relationship between trial eligibility and marijuana use was trending, with subjects who were THC+ at prescreening less likely to be eligible for a trial, but did not reach statistical significance.

Conclusion: Our results suggest that marijuana use is common among potential MDD clinical trial participants, yet marijuana users are less likely to participate in trials. Restrictions on marijuana use should be carefully considered in MDD trial design.

Funding/financial disclosures: The authors report no conflicts of interest for this work; all are current employees of Adams Clinical, an independent central nervous system (CNS) research site that conducts self- and industry-sponsored pharmaceutical trials.

Optimized Preclinical Brain Mapping Quantification of Single Cells with a Novel Genetic Tag

Authors: Eric R. Szelenyi,1,2* Jovana S. Navarrete,1,2 Alex Murry,1,2 Yizhe Zhang,1,2 Kasey S. Givern,3 Lauren Kuo,1,4 Bryce Bowler,2 Marcella M. Cline,1,4 Barbara Juarez,1,5,6 Larry Zweifel,1,5,6 Sam A. Golden1,2

*Presenting author

Affiliations: 1University of Washington Center of Excellence in Neurobiology of Addiction, Pain, and Emotion (NAPE), Seattle, WA; 2University of Washington, Department of Biological Structure, Seattle, WA; 3University of Washington, Department of Anesthesiology and Pain Medicine; 4University of Washington Undergraduate Program in Biochemistry; 5University of Washington, Department of Psychiatry and Behavioral Sciences, Seattle, WA; 6University of Washington, Department of Pharmacology, Seattle, WA

Background/Objective: Recent advancements in high-throughput volumetric fluorescent microscopy provide the means to deconstruct whole-brain anatomy and function at the direct level of single cells. However, current approaches used to genetically label single cells suffer from extensive signal artifact that greatly interferes with automated image segmentation algorithms used in brain mapping.

Design: A novel genetic approach to enhance single cell discrimination of genetically labeled brain cells was explored, in which attempts were made to diminish extranuclear signal artifact by rerouting it to the nucleolar subcompartment of the nucleus through a polyarginine-based mechanism. Our strategy parameterized configurations of nuclear localization signal (NLS) tag type and polyarginine linker length combinations to achieve optimal tag efficacy. The top candidate was thoroughly characterized and benchmarked in vivo.

Results: A successful configuration rendered nuclear restriction and was termed arginine-rich NLS, or Argi-NLS. Argi-NLS does not harm brain cells and is thus suitable for single cell quantification across experimental designs. It is functionally modular when tagged across spectrally separate fluorescent proteins and possesses universal activity across divergent cell classes. Crucially, it improves two- and three-dimensional image segmentation of single cells by enhancing machine learning compatibility and increasing the detection of labeled cells by 100 percent across the entire brain.

Conclusion: Argi-NLS is a novel genetic tag engineered for its application in optimal cell and circuit mapping experiments in the rodent brain. The precision enabled by Argi-NLS strongly positions its utility in single cell volumetric assays used for preclinical central nervous system (CNS) drug development, as well as spatial biology-focused biotech and researchers as a whole.

Funding/financial disclosures: None to report.

Precision Matters: An Analysis of How Various Scores Behave When Measuring Change Over Time; Factors that Inform Score Selection for the Best Results

Authors: J. Lynsey Psimas, PhD; Paul Williams, PsyD

Affiliations: Pearson Clinical Assessments

Background/Objective: We explored the impact of selecting raw scores, standard scores, age equivalents, and growth scale values (GSVs) to identify the most precise metric to measure change. Through a case study approach, we aimed to highlight the importance of carefully selecting metrics for data analysis and demonstrate the effect on interpretation.

Design: Through simulated case studies, we demonstrated the implication of score selection.

Results: Raw scores are widely used in research. While useful, raw scores do not include interval scaling and come with a single group-based SEM. Standard scores can be misleading because of population change that is typically more rapid than for very low functioning children. Age equivalents are often used to track change but have a few limitations, such as the lack of SEMs to determine statistically significant differences. Inaccuracies occur at the extreme where these children typically fall. Finally, age equivalents are bound to the normative age range, making out-of-level testing impossible. GSVs contain interval scaling and conditional SEMs, allowing researchers to measure outside of the developmental age range, unlike age equivalents and standard scores.

Conclusion: The key messages are that GSVs, along with raw scores, increase the effective range of a given measurement. GSVs provide score-specific SEMs, which are more precise than group-based SEMs when deriving confidence intervals and statistically significant change. GSVs support out-of-level testing because they can be used at any chronological age. Lastly, the interval nature of GSVs removes that little bit of noise, improving our measurement precision.

Funding/financial disclosures: The presenters are paid employees of Pearson Clinical Assessment and part of the Pharma Research Services department.

Proposal for Standardization of Clinical Outcome Assessment Strategies for Early-stage Drug Development Trials

Authors: K Bishop,1 S Zaragoza Domingo,2 J Alonso,3 M Ferrer,3 M De Gracia,4 P Annas,5 F Butlen-Ducuing,6 P Balabanov,6 C Edgar,7 J Harrison,8 B Horan,9 J Kottner,10 MT Acosta,11 AK Berger,5 JM Haro12

Affiliations: 1Global Pharma Consultancy, LLC, PA; 2Health Services Research Group, IMIM Hospital del Mar Medical Research Institute and CIBERESP, Spain; 3Universitat de Girona, Facultat Psicologia, Girona, Spain; 4Neuropsychological Research Organization s.l,(Neuropsynchro), Barcelona, Spain; 5Lundbeck A/S, R&D, Copenhagen, Denmark; 6Office of Therapies for Neurological and Psychiatric Disorders, Human Medicines Division, EMA; 7Cogstate, UK; 8Metis Cognition, Ltd., Kilmington Common, UK; Alzheimer’s Center, VUmc, Amsterdam, The Netherlands; and Institute of Psychiatry, Psychology and Neuroscience, King’s College London, UK; 9VeraSci, US; 10Charité-Universitätsmedizin, Berlin, Germany; 11Undiagnosed Disease Program, Principal Investigator ADHD Genetic Study Gene Therapy Program -GM1, National Human Genome Research Institute, National Institutes of Health, US; 12Research, Innovation and Teaching Unit, Parc Sanitari Sant Joan de Déu, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, Barcelona, Spain

Background/Objective: The role that clinical outcome assessments (COAs) play in the high percentage of neuroscience clinical trial failures has received considerable attention. Efficacy studies are of particular concern, in which a key issue is whether the COAs can be considered fit for purpose. Psychometric properties of many of the commonly used COAs are insufficient. To address this issue, an ECNP task group was formed to improve and standardize the process for endpoint and COA selection in the earliest stages of drug development.

Results: A guidance document for COA selection in neuroscience drug development was created to provide recommendations for efficacy and safety of new treatments, including a full description of minimum standards for the selection of Core Outcomes Set (COS) projects, detailing seven basic steps:

  1. Identifying the disease model and background
  2. Defining the scope of use for the COS
  3. Stakeholder involvement
  4. Determining “what to measure”
  5. Determining “how to measure” outcomes (i.e., qualities of the instruments)
  6. Making final generic recommendations for COS measurement
  7. Conclusions and future steps for innovation

An overview of the risks involved when any of the steps are not adequately addressed will be provided.

Conclusion: This guidance document is intended for drug developers, independent researchers, and those concerned with promoting standardization of the COA selection process. It is recommended to be used early and throughout the drug development path, producing a Drug Development COAs Selection Plan, and it is especially important for trials of conditions where no legacy instruments are available.

Funding/financial disclosures: None to report.

Psilocybin Therapy for Treatment-resistant Depression: Prediction of Clinical Outcome by Natural Language Processing

Authors: Gregory Ryslik

Background/Objective: Therapeutic administration of psychedelic drugs has shown significant potential in historical accounts and recent clinical trials in the treatment of depression and other mood disorders. A recent randomized, double-blind, Phase IIb study demonstrated the safety and efficacy of COMP360, COMPASS Pathways’ proprietary synthetic formulation of psilocybin, in participants with treatment-resistant depression (TRD). While promising, the treatment works for a portion of the population, and early prediction of outcome is a key objective.

Design: Transcripts were made from audio recordings of the psychological support session between the participant and therapist one-day post-COMP360 administration. A zero-shot machine learning classifier based on the BART large language model was used to compute two-dimensional sentiment (valence and arousal) for the participant and therapist from the transcript. These scores, combined with the Emotional Breakthrough Index (EBI) and treatment arm, were used to predict treatment outcome, as measured by Montgomery–Åsberg Depression Rating Scale (MADRS) scores. Code and data are available at https://github.com/compasspathways/Sentiment2D.

Results: Two multinomial logistic regression models were fit to predict responder status at Week 3 and through Week 12. Cross-validation of these models resulted in 85 and 88 percent accuracy, respectively, and area of the curve (AUC) values of 88 and 85 percent, respectively.

Conclusion: A machine learning algorithm using natural language processing and EBI accurately predicts long-term patient response, allowing rapid prognostication of personalized response to psilocybin treatment and insight into therapeutic model optimization. Further research is required to understand if language data from earlier stages in the therapeutic process hold similar predictive power.

Funding/financial disclosures: Not provided.

Quantifying Diversity, Equity, and Inclusion in Clinical Trials

Authors: Gabriela Farrell,1 Amelia Whitehouse2

Affiliations: 1Trial Operations Lead, HealthMatch; 2Product Lead, HealthMatch

Background/Objective: The objective of this work was to improve diversity, equity, and inclusion (DEI) outcomes in clinical trials across the industry. We aim to do so by creating new data that helps industry engage with the expectations of and perspectives on clinical trials from patients of diverse racial/ethnic backgrounds.

Design: Previous work in this area has focused on analysis of data (e.g., race/ethnicity of study participants) that has been incidentally collected in the course of normal research; while useful to monitor performance, it does not generally provide insight on the specific reasons for the underrepresentation of particular groups in clinical trials, nor the underlying dynamics that exist across these groups.

HealthMatch has direct relationships with over 850,000 patients in the United States (US), all with a direct intent to engage in clinical trials. HealthMatch developed a survey to understand how its patients think about and engage with clinical trials, exploring:

  • interactions with the health system;
  • expectations from clinical trials; and
  • drivers and disruptors of engagement with the trial process.

Results: Responses to the survey were attributed to HealthMatch patient profiles, enabling analysis by personal and medical datapoints/groupings. A total of 7,903 HealthMatch patients returned complete responses to the survey within the research timeframe.

Conclusion: People are people. There are a number of drivers and disruptors of engagement with clinical trials that are generally consistent across all racial/ethnic groups. Drivers includes access to care, medicine, and treatments; access to doctors and information; and altruism. Disruptors include travel time, distance, and proximity; compensation; conflicts; and representation.

Reaching different groups requires real understanding. Diversity is bigger than recruitment—addressing the greatest challenges of minority groups requires meaningful engagement over time. Patients are partners in changing the future of medicine. Patients are willing to engage with industry if asked and will continue to do so; 87 percent of responses indicated a willingness to engage in further research.

Funding/financial disclosures: This work has been undertaken by HealthMatch.io in the course of commercial operations. The presenters are employees of HealthMatch. To discuss this work and/or its inclusion in the CNS Poster Exhibition, contact Manuri Gunawardena (CEO, HealthMatch) or Tate Stubbs (COO, HealthMatch). More information on this work is available at heathmatch.io/dei-report.

Recruitment in Rare. Myth Debunked

Authors: Marcella Debidda, PhD; Matt Lafleur

Affiliations: BioNews, Inc.

Background/Objective: Recruiting patients affected by rare diseases is hard. In response to a need voiced by our audience (1 million rare patients and their care circles in over 60 communities), we launched a “virtual meeting ground” to connect them to ongoing sponsored clinical trials. Our hypothesis was that leveraging the trusted relationship with our audience and bringing clinical trial opportunities where patients already consume healthcare information would simplify and speed up recruitment.

Design: Idiopathic pulmonary fibrosis (IPF), sarcoidosis (SAR), and Sjogren’s disease (SJO) were the rare disease communities we selected, based on level of engagement, number of patients in our audience, and number of trials recruiting patients per clinicaltrials.gov. We executed recruitment campaigns for five clinical trials in those diseases, with both pragmatic and nonpragmatic study designs, as well as traditional and decentralized/hybrid models.

Results: For the three IPF trials, the referrals generated in our 8-to-16-week recruitment campaigns converted into 42 enrolled (trial 1), 35 randomized (trial 2), and 33 referred (trial 3, ongoing) patients. For the trial on SAR in African American individuals, 47 patients were enrolled. For the SJO trial, 11 patients were randomized.

Conclusion: We keep witnessing the paradox of rare patients desperately looking for trials and pharmaceutical companies not finding patients. In part, it is because we operate in an industry where the interaction with patients is often transactional and confined to the recruitment phase of clinical trials. We demonstrated that when we engage continuously, operate on an existing foundation of trust, and bring trial opportunities where patients consume healthcare information, recruitment is a lot faster.

Funding/financial disclosures: Authors/presenters both are employees of BioNews, Inc.

Site Network+Central Recruitment=200% Enrollment Speed

Authors: Dan Brenner, Steve Wimmer

Affiliations: 1nHealth, Orlando, FL,

Background/Objective: A Phase II study was conducted to assess the safety and immunogenicity of the sponsor’s investigational vaccine, compared to an approved vaccine, for the prevention of herpes zoster in adults aged 50 years and older. The sponsor previously filled Phase II in 2022 with 1nHealth running recruitment and was required to enroll an additional 180 patients for a 2023 Phase II extension focusing on selected Alliance for Multispecialty Research (AMR) sites in the United States (US).

Design: 1nHealth utilized multiple social media platforms (Facebook and Instagram) in a campaign that leveraged previous findings and honored the multicohort age strata of the study, making patients the center of the message rather than the study itself. Collaboration between the sponsor and AMR site network led to a high-performing campaign that leveraged efficient prescreener prequalification of responding participants, chatbot flows to ensure participants were interested and qualified, and utilization of SMS messaging by site personnel to fast-track first appointments.

Results: From recruitment launch to full enrollment, 180 participants enrolled in six weeks across seven study sites, which was quicker than the 12 weeks that were allotted. Because the combination of messaging, expectation setting, and fast site-level follow-up were well coordinated and integrated, 11 percent of the total prequalified participants consented into the study from the central recruitment campaign.

Conclusion: The successful completion of enrollment in half the expected time can be attributed to the seamless integration of messaging, clear expectation setting, and effective site-level collaboration. This well-coordinated approach highlights the significance of aligning communication and process elements in a strategic manner to achieve accelerated results.

Funding/financial disclosures: None to report.

The First Validated New Patient-centric Data Capture Innovation Since Paper on Smartphones Delivers High Compliance in Clinical Trials and Real-world Studies

Authors: Bruce Hellman, Chief Patient Officer

Affiliations: SAFIRA Clinical Research, uMotif

Background/Objective: While the use of patient-reported outcome measures (PROMs) in research grows and user interface design evolves, new PROMs use standard scale types, such as Numeric Rating Scale (NRS), Verbal Response Scale (VRS), and Visual Analog Scale (VAS), in paper-based original designs. This research validated a modern design for the VRS, testing it against the standard VRS-design of the EuroQol-5 Dimension-5 Level (EQ-5D-5L; health-related quality of life measure) to encourage instrument developers to use modern design approaches supported by new technology.

Design: A randomized equivalence study with 55 participants in two groups and a crossover design using the standard EQ-5D-5L VRS versus the new VRS design was conducted. Participants received a short training on both VRS versions. A period with an active distraction task between the applications was observed, and the intraclass correlation coefficient (ICC) for the EQ-5D-5L was calculated to show measurement equivalence between the two VRS versions. Participants also completed the identical EQ-5D-5L vertical scale.

Results: Participants reported no difficulty with the new petal-like (Motif) VRS widget; all successfully completed both VRS versions. The ICC of 0.875 and the lower bound 95-percent confidence interval (CI) of 0.796 are strong indications that these two representations of the VRS are equivalent.

Conclusion: Existing and new PROMs use a limited number of well-established scale types, developed for paper and migrated to electronic platforms almost unchanged. However, it is possible to develop modern graphical user interfaces of existing standard scale types without changing psychometric PROM properties. The Motif VRS can replace the standard VRS design in existing and new PROMs.

Funding/financial disclosures: None to report.

Trial and Error: Supporting Age Diversity in Clinical Trials

Authors: Emma Thorp,1 Esther McNamara2

Affiliations: 1RBW Consulting; 2International Longevity Centre UK

Background/Objective: Most drugs are used by people aged over 60 years, yet trial participants are often younger. The Trial and Error report identifies barriers to age diversity in clinical trials. Older people tend to be underrepresented in clinical trial cohorts, particularly in trials studying medicines that are intended for all adults, not just older adults. We also know that polypharmacy and increased risk of adverse events (AEs) are often associated with older people. The report provides stakeholders with evidence-based recommendations, which will enable all stakeholders to support the participation of more older people in trials.

Design: A roundtable discussion and one-on-one interviews with a range of expert stakeholders were conducted. Expert stakeholders included pharmaceutical professionals; regulators; academic researchers and clinicians from pharmacology, geriatrics, public health, and sociology; contract research organizations; patient advocacy professionals; healthcare technology professionals; and other associated professionals. The findings from these discussions were synthesized into a report.

Results: Ageism in clinical trials is increasingly understood to require action and intervention. We found that the barriers to age diversity vary by stakeholder and may vary by country. The report makes recommendations that are specific to each stakeholder group.

Conclusion: To achieve age parity in trials and properly evidence the safety and efficacy of medicines, all stakeholders must go over and above what is currently required of them. This requires regulatory change, increased investment, more dialogue between regulators and trial designers, and expansion of our understanding of diversity and inclusion to prioritize age and its intersections with other characteristics.

Funding/financial disclosures: The International Longevity Centre UK were able to author and deliver this report thanks to the support of RBW Consulting.

Use and Preferences for Digital Health Technology Accessibility and Communication Features

Authors: Kelly Dumais,1 Sarah Gary,1 Tony Otero,1 Jessica Emerson,1 Bryan McDowell2

Affiliations: 1Clario, Philadelphia, PA; 2Clario, Geneva, Switzerland

Background/Objective: Providing various communication options and accessibility features via digital health technologies may provide greater inclusivity and usability in clinical trials, but familiarity and preferences for these features are poorly understood. We investigated preferences for communication and accessibility features that could enhance usability and engagement in clinical trials.

Design: Participants completed an electronic communication questionnaire asking about frequency of use and preference for common communication methods with friends/family and healthcare professionals.

Results: Fifty-five participants completed the questionnaire. When communicating with friends/family, 69.6 percent of participants most preferred using WhatsApp, followed by phone call (21.4%). Respondents at least somewhat often communicated with friends/family via text messages (94.5%), speech-to-text messages (40.0%), voice memos (50.9%), or video messages (29.1%). When communicating with healthcare professionals, 72.7 percent of participants most preferred phone call, followed by email (20.0%). If in a clinical trial, 80.0 percent of respondents most preferred communicating with physicians via text messages. To report symptoms in a clinical trial, respondents most preferred phone/video call to physicians (50.9%) and touch screen on a device/smartphone (47.3%). Respondents were interested in having the device read the questions/answers aloud (36.4%) and answering questions verbally (41.8%). The majority of participants (72.7%) most preferred to use their own smartphone.

Conclusion: Participants strongly preferred text messaging with friends/family, while preferring phone calls when communicating with physicians. For reporting symptoms in a clinical trial while at home, participants were split between phone/video call and using smartphone touchscreens, suggesting preference for both independent reporting as well as live communication with their physician, which may reflect the rising use of telehealth.

Funding/financial disclosures: Funding provided by Clario. All authors are employees of Clario.

Using Aggregated Site Features Computed with the MPsQ to Allow a Better Monitoring of Sites in Clinical Trials

Authors: Arthur Ooghe, Samuel Branders, Jérôme Paul, Dominique Demolle, Alvaro Pereira

Affiliations: Cognivia, Mont-Saint-Guibert, Belgium

Background/Objective: The Multi-Dimensional Psychological Questionnaire (MPsQ) is an assessment characterizing the profile of subjects participating in a randomized controlled trial (RCT) to predict their behaviors in the study (e.g., placebo response, adherence). This analysis aimed to determine whether individual responses collected through the MPsQ could serve for characterizing clinical sites in RCTs. The objective is to enhance study data comprehension by profiling clinical sites.

Design: Historical data from five diverse RCTs across varying medical indications (chronic pain, degenerative disease, and ophthalmology) were employed. Analysis was restricted to clinical sites with a minimum of 10 subjects, resulting in a dataset comprising 1,164 subjects distributed across 56 clinical sites. For this first analysis, two site scores were aggregated using the subjects’ answers to the MPsQ—namely, subjects’ expectations of improvement and interaction with clinical sites.

Results: The analysis showed significant correlations between subject scores and the scores of their associated sites, 36 percent (95% confidence interval [CI]: 0.31, 0.40) for Expectations and 20 percent (95% CI: 0.13, 0.27) for Interactions. Leveraging the two aggregated site scores also allowed for characterization of other site characteristics with, for example, the explanation of approximately 31 percent of the variance in drop-out rates across individual sites.

Conclusion: This analysis underscores the potential of MPsQ features to effectively profile clinical sites in RCTs. These profiles, reflective of intrinsic site attributes, demonstrably impact subject behaviors. Moreover, these profiles can explain disparities in subject behaviors across different sites. Characterizing the sites could improve the post hoc data understanding and conduct of studies through relevant feedback.

Funding/financial disclosures: All presenters are employees of Cognivia. The MPsQ is a proprietary questionnaire of Cognivia.

Utilizing Experienced Research Networks to Conduct Global Clinical Trials in Difficult-to-Access Populations for Drug Development in Psychiatry

Authors: Adam Simmons,1 Christina Arevalo,2 Patricia Marcy,3 Priya Matneja,3 John Kane,3 Inge Winter-van Rossum,4 Erika van Hell,4 René Kahn,5

Affiliations: 1Premier Research; 2Alkermes; 3Vanguard Research Group; 4UMC Utrecht, Clinical Trial Center; 5Icahn School of Medicine at Mount Sinai

Background/Objective: This study aimed to determine if site networks established for publicly funded research could be utilized to conduct industry sponsored clinical trials in difficult-to-access populations.

Design: Patients with psychiatric disorders who are early in illness have traditionally been difficult to recruit into industry-funded trials. The UMC Utrecht Clinical Trial Center (CTC) was established to coordinate a large multicenter trial in patients with first-episode schizophrenia. Similarly, the Vanguard Research Group (VRG) was established to conduct a National Institute of Mental Health (NIMH)-funded study in patients following an initial episode of schizophrenia.

To conduct a global Phase III study of an investigational drug in patients recently diagnosis with schizophrenia, schizophreniform, or bipolar I disorder (NCT03187769), a global contract research organization (CRO), in collaboration with the CTC and VRG network project leadership, was utilized to identify sites with access to the population while ensuring overall quality and adherence to good clinical practice (GCP) standards.

Results: Thirty-one of the 73 activated global sites were from VRG (15) and CTC (16) research networks. Activated VRG/CTC sites were composed of academic medical centers and community mental health clinics. Additional global sites were selected from the CRO/sponsor. Within the United States (US), 34.1 percent of enrollment came from VRG sites (71/208 subjects). All enrollment in Central and Western Europe and Israel came from CTC sites (59 subjects). Additional global enrollment regions included Republic of Korea, Ukraine, and Russia (161 subjects).

Conclusion: This model may allow for expansion of drug development to be conducted in hard-to-access populations by reducing investigator burden while still enabling GCP-level quality required for industry-funded research.

Funding/financial disclosures: AS is an employee of Premier Research and former employee and stockholder of Alkermes. CA is a currently employee of Alkermes and may own stock in the company. JK has received honoraria from or been a consultant to Alkermes, Boehringer-Ingelheim, Click Therapeutics, Dainippon Sumitomo, H. Lundbeck, HLS, Intracellular Therapies, Janssen Pharmaceuticals, Karuna, LB Pharma, Merck, Minerva, Neurocrine, Newron, Novartis, NW PharaTech, Otsuka, Roche, Saladax, Sunovion and Teva; and is a shareholder of Cerevel, HealthRhythms, LB Pharma, Medincell, Sage Pharma, and The Vanguard Research Group. RK, Icahn School of Medicine, reports consulting fees from Alkermes, Sunovion, Gedeon-Richter, and Otsuka. WWF reports consultant fees from Angelini, Richter, Recordati, Lundbeck, Otsuka, Teva, Boehringer-Ingelheim, Pierre Fabre, Janssen, Sunovion, DainipponSumitomo, Takeda, and Pfizer; speaker fees from Janssen, Lundbeck, Otsuka, Richter, and Recordati; and grants from Janssen, Lundbeck, and Otsuka. P. Marcy, P. Matneja, IWvR, and EvH have no disclosures to report.

Virtual RRMS Patients for Clinical Trial Design: Emulating Heterogenous Treatment Responses

Authors: Fianne Sips,1 Chiara Nicolò,2 Niccolò Totis,1 Marc-Antonio Bisotti,2 Roberta Bursi2

Affiliations: 1InSilicoTrials Technologies BV, ’s-Hertogenbosch, The Netherlands; 2InSilicoTrials Technologies SpA, Trieste, Italy

Background/Objective: Clinical trial design in relapsing remitting multiple sclerosis (RRMS) can be challenging due to the often slow and unpredictable disease progression and great heterogeneity of both disease courses and treatment responses. To support RRMS trial design, we have launched MS TreatSim, a virtual patient (VP) generator that can simulate realistically heterogeneous RRMS disease courses. The simulator is also able to treat its VPs with several commonly prescribed treatment options. Here, we aim to characterize how MS TreatSim’s VPs emulate heterogeneity in treatment responses.

Design: Fifty VPs were generated with MS TreatSim, a cloud-based VP simulator based on an agent-based, individualizable model of RRMS (mstreat.insiliconeuro.com). The 50 VPs were each virtually treated with either interferon β-1a, teriflunomide, or natalizumab for 260 weeks. The outcomes for the different treatment protocols were then compared with disease activity in the same VPs without treatment.

Results: With treatment, relapse rates in the VP population fell from 0.33±0.29 (mean±standard deviation [SD]) to 0.10 or lower, while the continuous disease activity variable, oligodendrocytes damage, was found to decrease by 57 (interferon β-1a), 80 (teriflunomide), and 72 percent (natalizumab). VPs’ heterogeneous treatment responses were further analyzed following stratification of VPs by treatment response.

Conclusion: MS TreatSim generates VPs with heterogeneous disease courses and treatment responses. The VP generator can be used to support trial design by simulating individual VP responses to placebo treatment and several commonly prescribed treatment options and can be extended to include novel treatment options.

Funding/financial disclosures: All authors are employees of InSilicoTrials Technologies

What Does Rater Training, Surveillance, and Intervention Really Do?

Authors: Katrina Patrick, Cristian Sirbu, Cynthia McNamara, Jenicka Engler

Affiliations: Cronos Clinical Consulting Services, Inc., an IQVIA Business

Background/Objective: Rater drift is the phenomenon where raters become less reliable and consistent over time, which can introduce more variability and error into study data. However, little has been published on rater drift and how best to mitigate it. We examined if rater surveillance and intervention could reduce the number or severity of data inconsistencies observed.

Design: Seven studies where Cronos provided rater surveillance and/or intervention were included for analysis. Two studies had raters who were generally more novice than is typical (<3 years of experience with the scale). The other five studies had experienced site raters, with three or more years of experience with the scale. We looked at preprogrammed quality flags (representing data anomalies) for the first five and the last five Montgomery–Åsberg Depression Rating Scale (MADRS) assessments for each rater as a proxy for data quality.

Results: The novice raters (n=33) showed worse quality at study start (mean: 3.78, standard deviation [SD]: 1.35 flags per assessment) than experienced site raters (n=385, mean: 1.05, SD: 0.77 flags per assessment). The novice raters demonstrated performance improvement over the course of the study (mean: 2.87, SD: 1.37), while the experienced raters demonstrated continued quality (mean: 0.91, SD: 0.73; FTime x Experience (1, 416)=16.03; p<0.001; ηp2=0.04).

Conclusion: Rater oversite and intervention programs may be helpful in preventing rater drift in experienced raters. It may improve the performance of novice raters by supporting them over the course of a study to ensure adequate data quality beyond rater training alone.

Funding/financial disclosures: All authors report no conflicts of interest for this work. All are current employees of Cronos Clinical Consulting Services, Inc., an IQVIA Business. Cronos does provide rater training, rater oversight, and rater intervention services.

Wearables and Mobile Applications (apps)

Advancing Patient-centric Therapies: A Novel Framework for Developing Sensor-based Digital Health Technologies as Clinical Outcome Assessments in Amyotrophic Lateral Sclerosis

Authors: Sylvain Zorman,1 Rakesh Pilkar,1 Cory J. Holdom,2 Shyuan T Ngo,2,3 Frederik J. Steyn,3,4 Christine Guo1

Affiliations: 1ActiGraph, LLC, Pensacola, FL; 2Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Australia; 3Department of Neurology, Royal Brisbane and Women’s Hospital, Australia; 4School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Australia

Background/Objective: Amyotrophic lateral sclerosis (ALS) is characterized by progressive muscle weakness and wasting due to the degeneration of motor neurons. Despite significant research progress, translating insights into impactful therapies remains elusive. This predicament is exacerbated by the inadequacy of current clinical outcome assessments (COAs) in capturing disease progression. Assessing daily functioning, a critical facet of therapy efficacy, proves intricate using conventional COAs. Wearables offer an innovative avenue for continuous data collection during daily activities, supplying evidence. Wearables-derived COAs possess unique attributes due to their high dimensionality and temporal precision. This work aimed to establish a framework for novel wearables-derived COAs, addressing this emerging paradigm.

Design: Our framework consists of three key pillars: 1) selection of a fit-for-purpose wearable, 2) establishing a connection between digital health technology (DHT)-derived metrics and health-related outcomes, and 3) formulating an appropriate regulatory strategy.

Results: Utilizing data from patients with ALS, we showcased the path toward creating innovative wearables-based COAs to support drug development. Based on literature review and preliminary findings, we identified promising metrics and constructed a conceptual model for ALS. Furthermore, we outlined a regulatory strategy for United States (US) Food and Drug Administration (FDA) endorsement within the context of ALS drug development.

Conclusion: Implementing this framework promises to expedite the integration of novel COAs, facilitating the arrival of new ALS therapies to market. Wearable devices are set to revolutionize drug development by enabling continuous data collection during daily routines and providing proof of intervention benefits. The proposed framework paves the way for novel COAs, ushering in more efficient, patient-centric drug development approaches.

Funding/financial disclosures: Not provided.

Elevating Engagement and Study Excellence: Harnessing Mobile App Technology for Women’s Health and Fertility Tracking

Author: Greg Christie

Affiliations: Chief Product Officer, StudyKIK

Background/Objective: This presentation aimed to highlight the impactful implementation of patient-facing technologies, specifically mobile applications (apps), to enhance participant engagement. It illustrated how sponsors and research sites can leverage these tools to enhance participant engagement and reinforce support in clinical trials.

Design: In a Phase II trial dedicated to validating a novel fertility test, the sponsor embraced innovation by integrating an electronic diary (eDiary) tool into a custom mobile app. This facilitated the capture of authentic patient data outcomes using photo and video diaries, addressing nuanced data interpretation. The inclusion of videos alongside photos recognized the limitations of images in conveying subtleties.

Engaging StudyKIK to lead the app’s development, a functional prototype was created within eight weeks. The app featured a tailored interface for the unique patient demographic, including specialized features, such as documenting sample collection and test results. User experience was thoughtfully designed, incorporating push notifications for reminders and clear instructions for daily tasks. Real-time activity logs shared with research sites maintained awareness of patient engagement. The app’s unique photo and video reporting capabilities facilitated documentation of patient results and sample IDs, aiding assessment of the fertility test’s performance. Integrated video conferencing for televisits and patient-recorded results further empowered participants.

Across five research sites and 262 subjects, the app was seamlessly integrated into the study, with personalized reminders enhancing compliance.

Results: The integration of the mobile app yielded remarkable results, contributing to successful trial achievements. Full enrollment was achieved, and 98.8 percent of participants completed app onboarding. There was 100-percent participant engagement through the app. A total of 8,242 activities were completed via the app.

Conclusion: In conclusion, the app significantly boosted engagement, streamlined tasks, captured genuine patient data, and improved data collection. It lessened site burden, broadened trial reach, and enhanced participant experience while ensuring data accuracy by managing complex tasks and reducing errors.

Funding/financial disclosures: Employed by StudyKIK.

Leveraging Sleep Reports Derived from Wrist-worn Wearable Data to Quantify Inclusion/Exclusion Criteria in Clinical Trials

Authors: Kenzie Carlson, MPH;1 Zoe Swain;2 Francesco Onorati, PhD;3 Krista Russell, MSHI;1 Alice Cai, MD;4 Ariel V. Dowling, PhD1

Affiliations: 1Digital Health Sciences, Takeda Pharmaceuticals, Inc., Cambridge, MA; 2Empatica Inc., Cambridge, MA; 3Quantitative Sciences, Takeda Pharmaceuticals, Inc., Cambridge, MA; 4Clinical Science, Takeda Pharmaceuticals, Inc., Cambridge, MA

Background/Objective: Self-reported data for inclusion/exclusion criteria in clinical trials has been shown to present investigators with challenges.1,2 Wearables can provide continuous monitoring, allowing for collection of objective, near real-time data.3 Using this data to quantify sleep can enable more precise screening for inclusion and exclusion in clinical trials.4 We created an overnight (8pm–8am) sleep report based on wrist-worn wearable data for participants with disordered sleep in a clinical trial. We sought to quantify the following exclusion criterion during screening: the participant practiced an unusually late bedtime during the screening period prior to the defined trial baseline.

Design: We used the Empatica EmbracePlus, which uses three-axis accelerometer data to quantify sleep. Data were analyzed using Empatica’s proprietary algorithm to generate sleep reports quantifying “average time in bed start time,” “average time in bed stop time,” “average length of sleep,” and other sleep-related metrics. The report presents data in a visual format showing longitudinal patterns and provides guidance for trial-specific cutoff values.

Results: We were able to develop a custom sleep report using a wrist-worn wearable to quantify sleep more objectively and potentially identify participants that should be excluded from the trial based on nighttime sleep patterns. However, we encountered challenges implementing these sleep reports and need to further refine the report to more precisely visualize highly fragmented sleep associated with diagnosed sleep disorders.

Conclusion: Sleep reports derived from wrist-worn wearable data present opportunities for objectively quantifying inclusion/exclusion criteria in clinical trials.

Funding/financial disclosures: This study was funded by Takeda Pharmaceutical Company, Ltd.

References:

  1. Stone AA, Shiffman S. Capturing momentary, self-report data: a proposal for reporting guidelines. Ann Behav Med. 2002;24(3):236–243.
  2. Paulhus DL, Vazire S. The self-report method. In: Robins RW, Fraley RC, Krueger RF, eds. Handbook of Research Methods in Personality Psychology. Guilford Press; 2007:224–239.
  3. Bonato P. Wearable sensors and systems. IEEE Eng Med Biol. 2010;29(3):25–36.
  4. Coravos A, Goldsack JC, Karlin DR, et al. Fast Facts: Digital Medicine-Measurement. S. Karger Publishers; 2020.

Multimodal Remote Monitoring of ALS Using Wearable Sensors and Digital Assessments

Authors: Ram Kinker Mishra,1 Adonay S. Nunes,1 Jose Casado,1 James Lim,1 Ashkan Vaziri,1 Andrew Geronimo,2 Zachary Simmons2

Affiliations: 1BioSensics, LLC, Newton, MA; 2Department of Neurosurgery, Penn State College of Medicine, PA

Background/Objective: Multimodal evaluations of neurological symptoms and disease progression play a crucial role in improving patient care and preparing for clinical trials. Our objective is to develop a multimodal technological solution called BioDigit Home to monitor the progression of amyotrophic lateral sclerosis (ALS) remotely. The platform will employ wearable sensors and digital assessments for speech, handwriting, and pattern-tracing skills.

Design: Individuals diagnosed with ALS were enrolled for up to 12 months of remote monitoring. They wore a PAMSys™ pendant and two wrist sensors for a week to measure daily physical activity and goal-directed movements. Every two weeks, assessments of digital speech, handwriting, and pattern tracing skills were conducted via the BioDigit Home tablet from BioSensics, LLC.

Results: A total of nine participants (average age: 64.4±7.2 years, 4 female) were included in the study. The sensor measurements exhibited significant correlations with the gross motor and upper motor subdomain scores of the Revised ALS Functional Rating Scale (ALSFRS-R). The speech metrics demonstrated meaningful-to-moderate correlations with bulbar and respiratory distress subdomain scores of the ALSFRS-R. On average, participants showed excellent adherence in wearing the sensors, completing 91.9 percent (range: 53.8–100%) of assigned speech tasks, and 88 percent of participants successfully completed handwriting and pattern-tracing tasks.

Conclusion: Our initial findings demonstrate the viability of the multimodal telemonitoring approach for remote monitoring of ALS symptoms and mobility. Patient enrollment and data gathering are still in progress, and we will share updated outcomes during the upcoming meeting.

Funding/financial disclosures: This research is supported in part by BioSensics, LLC.