Estimation of clinical trial success rates and related parameters
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kxx069.pdf
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472.74 KB
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Adobe PDF
Checksum (MD5)
40a10b2f4f101700791533d804ee363b
Author(s)
Wong, Chi Heem
Siah, Kien Wei
Lo, Andrew W
Date Issued
January 2018
Journal
Biostatistics
Publisher
Oxford University Press (OUP)
Citation
Wong, Chi Heem et al. “Estimation of Clinical Trial Success Rates and Related Parameters.” Biostatistics 20, 2 (January 2018): 273–286 © 2018 Oxford University Press
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Sloan School of Management
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1093/BIOSTATISTICS/KXX069
