Leveraging Technology And Expert Clinician Review To Enhance Risk Detection In Neuroscience Studies

By Andreas Schreiner and Adam Simmons

The leading cause of trial failure across all indications has consistently been the inability to prove efficacy. A study analyzing 640 Phase 3 trials involving novel therapeutics found that 54% of them failed during clinical development, with over half (57%) failing due to insufficient efficacy. In the realm of neuroscience indications, an alarming 85% of late-phase studies falter, largely attributed to challenges like subjective endpoints, patient and disease variability, rater inconsistencies, and substantial placebo response rates, making it challenging to detect treatment effects.

Neuroscience therapy developers must proactively adopt a strategy to improve data quality and assess responses by strengthening risk and signal detection. In this blog, the authors explore how a combination of technology and expert clinician review can bolster risk and signal detection in neuroscience studies.