Given the rising costs, protracted timelines, and increasing complexity of large molecule R&D, scientists, group heads, and executives all need to take a data-driven approach to optimizing their own processes and decision-making. Especially for companies working in emerging drug modalities, knowing exactly what to measure – and what actions to take in light of certain data – can give you a competitive advantage.
From answering questions like, "For a particular process, what's our average yield?" to answering, "Over time, where within our R&D organization have we made funding changes?", taking a data-driven approach to R&D can create value at all levels of an organization.
In this series, we explore a framework for scientists, group heads, and executives to measure the success of their programs.