Novel Uses Of Scoring Functions In Clinical Trial Design Selection

By Esha Senchaudhuri

For decades, statisticians have cultivated methods to optimize and de-risk clinical trials for strong regulatory submissions. As the number of possible clinical trial designs have exponentially increased, the need to construct a new set of quantitative tools for accelerated comparison of these designs has become critical for trial selection.

Cytel has advocated for three specific new methods: expansive simulation, Pareto optimization, and scoring functions.

Here I take a closer look at how these three work in tandem, with a special highlight of the use of scoring functions.

A scoring function is a mathematical tool that enables trial sponsors to review millions of designs quickly, and rank them based on a number of performance characteristics. While such functions are a straightforward and intuitive tool, the way in which scoring functions can be used for clinical development have novel new implications.