Estimation of clinical trial success rates and related parameters

• Published in: Biostatistics (Oxford, England) Vol. 20; no. 2; pp. 273 - 286
• Main Authors: Wong, Chi Heem, Siah, Kien Wei, Lo, Andrew W
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.04.2019
• Subjects: Biomarkers; Clinical Trials as Topic; Databases, Factual; Drug Development; Humans; Models, Statistical; Outcome Assessment, Health Care - methods; Clinical trial statistics; Clinical phase transition probabilities; Probabilities of success
• ISSN: 1465-4644; 1468-4357; 1468-4357
• DOI: 10.1093/biostatistics/kxx069

SUMMARY 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.