Researchers Identify Speech Latency as a Key Biomarker for Predicting Treatment Response in Patients with Schizophrenia

Researchers have identified a promising new speech biomarker that could significantly enrich clinical trials by reducing sample size requirements and enhancing statistical outcomes. By using speech latency, participants who are likely to show a high placebo response can be identified and excluded. The study in Biological Psychiatry, published by Elsevier, showed that when these participants were removed from the main analysis, the treatment-placebo effect increased dramatically, by as much as two to three times the original results.

Speech latency is an objective measure of verbal response time derived from standard clinical assessments. It is sensitive to cognitive, social, and motivational factors and can be measured using recordings of psychiatric interviews. The single, interpretable speech biomarker identified in this study was extracted from screening interviews with 406 participants with schizophrenia from three countries representing eight languages in a Phase 3 study of antipsychotic drug brilaroxazine (RP5063).

“Our study has important implications for reducing clinical trial costs and burden,” says lead investigator Alex S. Cohen, PhD, Department of Psychology and Center for Computation and Technology, Louisiana State University, Baton Rouge, LA, and Quantic Innovations, Inc., Benton, AR. “Using patient characteristics like speech biomarkers can help identify patients who are most likely to benefit from the medication being tested. Because these measures are objective and easy to collect, they could make trials more reliable and help reduce the risk of failure.”

Clinical trials for neuropsychiatric drugs are essential for evaluating efficacy and safety of novel treatments yet can fail when the participants chosen are too different from each other, or when it is hard to determine who will respond to the treatment.

Enrichment strategies to decrease heterogeneity, reduce confounding psychiatric conditions, and identify participants likely to demonstrate a true pharmacological response rather than a placebo effect can successfully improve clinical trial outcomes, reduce associated costs, and help bring effective treatments to patients faster.

Among the many potential speech biomarkers related to schizophrenia, speech latency was chosen because it is tied to social communication, motivation, and cognition. It is conceptually and empirically tied to psychomotor slowing, whereby a longer pause suggests a disruption in the neural circuits responsible for translating thought into speech.

Co-investigator Laxminarayan Bhat, PhD, President and CEO, Reviva Pharmaceuticals, Cupertino, CA, explains, “These vocal biomarker findings reinforce brilaroxazine’s potential to address major unmet needs as a next-generation treatment for schizophrenia by confirming its broad-spectrum efficacy across core symptom domains, including negative symptoms, and corroborating our Phase 3 clinician-assessed outcomes.”

By enriching the sample using speech-latency ratio, statistical significance was achieved with approximately half the sample size, with much larger effects in key symptom and functional domains. These effects were particularly notable in total, positive, and negative symptoms, of which 80%, 73%, and 57% of patients, respectively, showed a statistically significant improvement.

Dr. Cohen comments, “We were surprised by how pervasive the improvements were for the vocal biomarker-enriched sample. Improved treatment-placebo separation was observed for negative symptoms, the primary endpoint and nearly every secondary endpoint.”

Beyond its clinical accuracy, the study highlights a shift toward interpretable AI. While modern digital phenotyping often relies on “black box” algorithms, the researchers found that the most striking aspect of speech latency is the transparency and simplicity of the measure itself.

Co-investigator Mark Opler, PhD, MPH, Chief Research Officer, Clario, Philadelphia, PA, notes, “While the process of discovering it, validating it, and learning to analyze it correctly was very complicated and involved a collaboration between multiple organizations over many years, the core construct is not complex. While there is clearly a role for multimodal, AI-driven methods in digital phenotyping, the field should also strive for clear, interpretable measures.”

This study demonstrates that speech latency analysis is useful for evaluating clinical trial results. Given that speech latencies can be automatically and quickly computed, they could help inform participant screening. However, the authors caution that speech latencies should not be used as an endpoint. Understanding when and why speech latencies improve and optimizing measures of their sensitivity are important.

John Krystal, MD, Editor of Biological Psychiatry, concludes, “While the neurobiology of speech latency in schizophrenia is not yet well understood, this research marks significant progress in shedding light on this issue. By identifying these specific biomarkers, we can better predict treatment response and, ultimately, improve patient outcomes.”

Notes for editors

The article is "A Single, Interpretable Vocal Biomarker for Enriching Antipsychotic Clinical Trials,” by Alex S. Cohen, PhD, Brian Kirkpatrick, MD, MSPH, Mark Opler, PhD, MPH, Kazunori Tatsumi, MA, Seema Bhat, MS, and Laxminarayan Bhat, PhD (https://doi.org/10.1016/j.biopsych.2025.11.025). It is published online in Biological Psychiatry, published by Elsevier.

The article is openly available for 60 days at https://www.biologicalpsychiatryjournal.com/article/S0006-3223(25)01676-2/fulltext.

Full text of the study and additional information are also available to credentialed journalists upon request; please contact Rhiannon Bugno at [email protected]. Journalists wishing to interview the authors should contact Alex S. Cohen, PhD, at [email protected].

This project reflects a collaboration by Reviva Pharmaceuticals, Inc., Quantic Innovations, Inc., Clario Inc., Louisiana State University, and the Psychiatric Research Institute at the University of Arkansas for Medical Sciences.

Trial Registration: Safety and Efficacy of Brilaroxazine (RP5063) in Schizophrenia (RECOVER); NCT05184335; https://www.clinicaltrials.gov/study/NCT05184335

The authors’ affiliations and disclosures of financial relationships and conflicts of interest are available in the article.

John H. Krystal, MD, is Chairman of the Department of Psychiatry at the Yale University School of Medicine, Chief of Psychiatry at Yale-New Haven Hospital, and a research psychiatrist at the VA Connecticut Healthcare System. His disclosures of financial relationships and conflicts of interest are available here.

About Biological Psychiatry

Biological Psychiatry is the official journal of the Society of Biological Psychiatry, whose purpose is to promote excellence in scientific research and education in fields that investigate the nature, causes, mechanisms, and treatments of disorders of thought, emotion, or behavior. In accord with this mission, this peer-reviewed, rapid-publication, international journal publishes both basic and clinical contributions from all disciplines and research areas relevant to the pathophysiology and treatment of major psychiatric disorders.

The journal publishes novel results of original research which represent an important new lead or significant impact on the field, particularly those addressing genetic and environmental risk factors, neural circuitry and neurochemistry, and important new therapeutic approaches. Reviews and commentaries that focus on topics of current research and interest are also encouraged.

Biological Psychiatry is one of the most selective and highly cited journals in the field of psychiatric neuroscience. It is ranked 9^th out of 156 Psychiatry titles and 17^th out of 271 Neurosciences titles in Journal Citation Reports^TM, published by Clarivate. The 2024 Impact Factor score for Biological Psychiatry is 9.0.www.sobp.org/journal

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