Quantifying knowledge gained in early and late phases can help determine the sub-population that new therapies ought to target. This ensures that patients are kept safe while receiving therapies that are effective for them. Yet determining appropriate stratifications and relevant clinical endpoints for these populations can be challenging.Therefore, it is necessary for development strategies to incorporate explorations and determinations of suitable biomarkers early in the development of a new therapy.
Exploratory stages of a trial can use a number of quantitative strategies to pinpoint which subpopulations ought to be chosen for further testing, and to determine possible early biomarkers that may be used as early indicators of efficacy. Given that one of the primary reasons for Phase 3 failures is that primary and surrogate endpoints are not clinically meaningful, quantitative strategies in early phases can focus on clarifying risks associated with different endpoints. There are several ways in which this can occur. Model-based meta-analyses incorporate knowledge gained about biomarkers in exploratory trials to create a framework that helps to choose particular agents to take forward in a trial. A separate but equally important strategic initiative is to use early phase data about biomarkers to leverage in forecasting and simulation.