How Objective Sleep Biomarkers Improve Clinical Development and Clinical Assessment in Depression

For teams developing a therapy for major depressive disorder (MDD), sleep physiology is one of the most powerful objective measures and predictive biomarkers. But clinical development and commercial strategy teams are still underutilizing sleep, missing valuable insights into patient selection, treatment response, and the real-world evidence that influences how drugs are prescribed and positioned post-approval. This webinar explores how objective sleep endpoints and biomarkers can strengthen clinical development and commercial planning in depression, and why they warrant earlier consideration in trial strategy.

Impaired sleep is a cardinal symptom of MDD, increasing the burden of other depressive symptoms. And depression, as well as its standard of care treatments, can significantly change sleep architecture. This bidirectional relationship makes sleep a uniquely sensitive lens for interrogating and improving MDD and treatment-resistant depression, with implications that start at early-phase trials and extend through commercial launch.

Many current depression trials measure sleep through patient-reported outcomes such as the Pittsburgh Sleep Quality Index (PSQI) or Insomnia Severity Index (ISI), which can be useful for characterizing patients’ perceptions of sleep improvements, but can be uncorrelated with patients’ underlying physiology and are susceptible to measurement instability, expectation and bias effects, data integrity gaps, and interpretation challenges. This webinar explores the power of objective, quantitative sleep physiology data as endpoints and biomarkers, including in predicting treatment responders, early responders, and placebo responders, all before standard depression efficacy signals emerge.

Quantitative sleep measures, including features of sleep microarchitecture that extend beyond conventional sleep staging, can stratify patient populations and capture pharmacodynamic signals that traditional endpoints miss entirely. For commercial teams, identifying which patients are most likely to benefit informs prescribing guidance, messaging, and market access strategy.

The featured speakers will discuss sleep impairments in clinical practice as shown in claims and survey data, the evidentiary standards required to bring objective sleep trial endpoints to regulators, pragmatic considerations for evaluating FDA-cleared EEG wearables for PSG-equivalent sleep staging, and the utility of real world physiology data in supporting both clinical and commercial objectives.

Register for this webinar to learn how sleep biomarkers can strengthen both clinical development and commercial strategy in depression through better stratification, earlier response prediction, and stronger evidence generation.

Speakers

Andrew Krystal, MD, MS, PhD, Professor of Psychiatry and Neurology and Vice Chair for Research, UCSF

Dr. Andrew Krystal is the Ray and Dagmar Dolby Distinguished Professor and Vice Chair for Research in the Department of Psychiatry and Behavioral Sciences at UCSF where he is also Director of the Clinical and Translational Sleep Research Laboratory, the Dolby Family Center for Mood Disorders and the Interventional Psychiatry Program. The primary focus of his research is the development of biomarkers for mood disorders and sleep disorders and their application in developing novel personalized treatments for these conditions.

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David Matthews, PhD, President of Life Sciences, Beacon Biosignals

David Matthews, PhD, leads Beacon’s Clinical Trials and Real World Data businesses as Chief Business Officer, where he has overseen support of 40+ concurrent phase 1-4 trials across psychiatry and neurology using Beacon’s at-home FDA-cleared EEG and AI-powered analytics for primary, secondary, and exploratory endpoints. Prior to Beacon, Dave served as the Chief Commercial Officer at BrightInsight, a Software-as-Medical-Device platform for biopharma, and a Partner at Boston Consulting Group (BCG) co-leading the Biopharma and Medical Devices verticals on R&D, Commercial, and Strategy topics. As a neuroscientist, his publications span machine learning, bioinformatics, brain imaging, neurophysiology, and health economics, with awards and funding from the NSF and the NIH. He holds a PhD in Computational Neurobiology from UC San Diego and the Salk Institute and a BA from Princeton University.

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Georgina Kontou, PhD, Neuroscientist, Beacon Biosignals

Georgina Kontou, PhD, is a Neuroscientist at Beacon Biosignals, where she focuses on leveraging sleep EEG insights to help biopharma partners de-risk and accelerate drug development. Georgina holds a PhD in Neuroscience from UCL, where she investigated how mitochondrial distribution in inhibitory neurons modulates brain network activity. She subsequently completed a postdoctoral fellowship at the AstraZeneca–Tufts Laboratory for Basic and Translational Neuroscience, contributing to early-stage drug discovery programs. Georgina later transitioned into life science consulting, working with ClearView Healthcare Partners and Kx Advisors (a BGB Group company). There, she partnered with pharmaceutical companies on a broad range of strategic initiatives, from go-to-market planning with commercial teams to evidence generation strategies supporting clinical development.

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