Understanding and Optimizing Composite Scores for Targeted Cohorts with Machine Learning

This approach brings a novel tool to the task of endpoint selection, especially in early phase studies where signal detection is paramount. The method produces interpretable findings and can be applied on individual assessments or across assessments. Optimizing composite scores for specific cohorts allows sponsors to define endpoints more sensitive to treatment effects, reduce patient burden, and improve decision making in clinical trials.