B1537
Title: Strategies for improving the assessment of the probability of success in late-stage drug development
Authors: Markus Reiner Lange - Novartis Pharma AG (Switzerland) [presenting]
Abstract: There are several steps to confirming the safety and efficacy of a new medicine. A sequence of trials, each with its own objective, is usually required. Quantitative risk metrics can be useful for informing decisions about whether medicine should transition from one stage of development to the next. Traditionally, pharmaceutical companies have used cross-industry success rates to estimate the probability of obtaining regulatory approval. Project teams then typically apply subjective adjustments to reflect project-specific information. However, this approach lacks transparency and fails to make full use of data from previous clinical trials. A quantitative Bayesian approach is described for calculating the probability of success (PoS) at the end of phase II, which incorporates internal clinical data, cross-industry success rates, and expert opinion or external data if needed. Using an example, it is illustrated how PoS can be calculated, accounting for differences between the phase II data and future phase III trials, and how the sensitivity of PoS to assumptions can be evaluated and communicated.
