Estimation of clinical trial success rates and related parameters

Abstract

Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial data for over 21 143 compounds from January 1, 2000 to October 31, 2015, we estimate aggregate clinical trial success rates and durations. We also compute disaggregated estimates across several trial features including disease type, clinical phase, industry or academic sponsor, biomarker presence, lead indication status, and time. In several cases, our results differ significantly in detail from widely cited statistics. For example, oncology has a 3.4% success rate in our sample vs. 5.1% in prior studies. However, after declining to 1.7% in 2012, this rate has improved to 2.5% and 8.3% in 2014 and 2015, respectively. In addition, trials that use biomarkers in patient-selection have higher overall success probabilities than trials without biomarkers.

Keywords: Clinical phase transition probabilities; Clinical trial statistics; Probabilities of success.

Fig. 1.

The POS over the period of January 1, 2005, to October 31, 2015, computed using a 3-year rolling window from January 1 in year to December 31 in year , with the exception of the last window, which terminates on October 31, 2015. This POS is computed using the phase-by-phase method, our adaptation of Hay and others (2014)’ methodology, which reports the proportion of phase transitions that advances to the next phase. The algorithm from Figure S5 in the Supplementary Material is not used, as it would overestimate the phase success if applied to a short window. The result for 2015 has to be treated with caution, as boundary effects increase the success rates artificially.