Improving Signal Detection in Mood Disorder Trials: Patient Selection and Ratings Validity
Mood disorder clinical trials rely on clinician ratings for both eligibility determination and efficacy measurement, a dual use that creates significant challenges for signal detection. When the same assessment tools screen patients into trials and measure treatment response, sites face competing pressures that can compromise diagnostic accuracy and inflate baseline severity scores. This measurement bias systematically increases apparent placebo response and obscures true treatment effects, contributing to the high failure rate in bipolar disorder and depression drug development programs.
Dr. Gary Sachs, Clinical Vice President for Bipolar Disease and Mood Disorders at Signant Health, presents evidence-based approaches for addressing these interconnected challenges. As founder of the Bipolar Clinic at Massachusetts General Hospital and Associate Professor of Psychiatry at Harvard Medical School, Dr. Sachs has developed innovative methodologies proven to improve patient selection accuracy while protecting endpoint reliability.
Critical strategies for enhancing trial success:
- Measuring and leveraging diagnostic confidence to ensure appropriate patient enrollment
- Implementing technology-based solutions that identify correlates of high placebo response
- Designing eligibility criteria that minimize pressure for score inflation while maintaining population validity
- Applying blinded monitoring systems to detect and correct rating validity issues during study conduct
Watch the video below to learn methodologies for reducing risk in mood disorder trials and maximizing drug-placebo separation.
