Each week, we select a recently published Open Access article to feature. This week’s article comes from Pharmaceutical Statistics and looks at selection bias in Phase 3 programmes in new drug development.
The article’s abstract is given below, with the full article available to read here.
, . Selection bias, investment decisions and treatment effect distributions. Pharmaceutical Statistics. 2021; 1– 15. https://doi.org/10.1002/pst.2132
When making decisions regarding the investment and design for a Phase 3 programme in the development of a new drug, the results from preceding Phase 2 trials are an important source of information. However, only projects in which the Phase 2 results show promising treatment effects will typically be considered for a Phase 3 investment decision. This implies that, for those projects where Phase 3 is pursued, the underlying Phase 2 estimates are subject to selection bias. We will in this article investigate the nature of this selection bias based on a selection of distributions for the treatment effect. We illustrate some properties of Bayesian estimates, providing shrinkage of the Phase 2 estimate to counteract the selection bias. We further give some empirical guidance regarding the choice of prior distribution and comment on the consequences for decision-making in investment and planning for Phase 3 programmes.