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Updated: Jan 12, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Forecasting clinical trial success using anonymized external expert panels
Frank S David1, R Edward Benson2, Mark Gordon2
1Pharmagellan LLC, Milton, MA 02186, USA; Department of Biology, Tufts University, Medford, MA 02155, USA.
Abstract:
Drug developers and financial investors have substantial interest in making accurate forecasts of the probability of success (POS) of clinical trials. Current methods developed and used by pharmaceutical companies face challenges in optimizing for accuracy, freedom from bias, and scalability. We describe here an approach based on external expert panels that showed promise across all these dimensions and could be broadly applicable for many stakeholders and scenarios requiring trial-specific POS forecasts.
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