Journal of Translational Medicine (Jan 2023)

Concept and application of the probability of pharmacological success (PoPS) as a decision tool in drug development: a position paper

  • Chao Chen,
  • Xuan Zhou,
  • Silvia Maria Lavezzi,
  • Usman Arshad,
  • Raman Sharma

DOI
https://doi.org/10.1186/s12967-022-03849-y
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 13

Abstract

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Abstract Background In drug development, few molecules from a large pool of early candidates become successful medicines after demonstrating a favourable benefit-risk ratio. Many decisions are made along the way to continue or stop the development of a molecule. The probability of pharmacological success, or PoPS, is a tool for informing early-stage decisions based on benefit and risk data available at the time. Results The PoPS is the probability that most patients can achieve adequate pharmacology for the intended indication while minimising the number of subjects exposed to safety risk. This probability is usually a function of dose; hence its computation typically requires exposure–response models for pharmacology and safety. The levels of adequate pharmacology and acceptable risk must be specified. The uncertainties in these levels, in the exposure–response relationships, and in relevant translation all need to be identified. Several examples of different indications are used to illustrate how this approach can facilitate molecule progression decisions for preclinical and early clinical development. The examples show that PoPS assessment is an effective mechanism for integrating multi-source data, identifying knowledge gaps, and forcing transparency of assumptions. With its application, translational modelling becomes more meaningful and dose prediction more rigorous. Its successful implementation calls for early planning, sound understanding of the disease-drug system, and cross-discipline collaboration. Furthermore, the PoPS evolves as relevant knowledge grows. Conclusion The PoPS is a powerful evidence-based framework to formally capture multiple uncertainties into a single probability term for assessing benefit-risk ratio. In GSK, it is now expected for governance review at all early-phase decision gates.

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