Advancing structured decision-making in drug regulation at the FDA and EMA.

Angelis, Aris; Phillips, Lawrence D

FDA's recent Benefit-Risk Framework (BRF) was developed for improving the clarity and consistency in communicating the reasoning behind its decisions, acting as an important advancement in US drug regulation. In the PDUFA VI implementation plan, FDA states that it will continue to explore more structured or quantitative decision analysis approaches, however it restricts their use within the current BRF that is purely qualitative. By contrast, European regulators and researchers have been long exploring the use of quantitative decision analysis approaches for evaluating drug benefit-risk balance. In this paper, we show how quantitative modeling, backed by decision theory, could complement and extend the FDA's BRF to better support the appraisal of evidence and improve decision outcomes. After providing relevant scientific definitions for benefit-risk assessment and describing the FDA and EMA frameworks, we explain the components of and differences between qualitative and quantitative approaches. We present lessons learned from the EMA experience with the use of quantitative modeling and we provide evidence of its benefits, illustrated by a real case study that helped to resolve differences of judgements among EMA regulators.