Drug development is a lengthy process with considerable uncertainty at each milestone. Several trials are needed to progress to confirmatory evaluation and establish a positive benefit-risk balance. One of the critical milestones is the decision to progress to phase III based on phase II trial results. Use of probability of success is becoming standard in pharmaceutical companies to support this decision. However, the lack of consistency in terminology makes it difficult to assess the comparative value of different approaches. By leveraging the availability of high-quality external data (e.g., real-world data, historical clinical trial data, etc.), probability of success-based procedures may further improve decision-making. We performed a scoping review of approaches to calculate the probability of success of a phase III trial depending on the available data sources and the availability of specific endpoints. Calculation of probability of success is relatively straightforward if data for the primary endpoint of the phase III trial are also available in phase II trials. Often, phase II trials are based on biomarker or surrogate outcomes, due to challenges associated with study duration and required sample size. Probability of success-based procedures as reviewed can incorporate external data sources, for example, from clinical trials testing the same or similar drug or real-world data on the targeted population-optimizing the calculation of probability of trial success and the projected drug candidate value. We conclude the paper by reflecting on alternative approaches and ideas for uses within pharmaceutical companies and academia.
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