Estimation of clinical trial success rates and related parameters
Name
1023498646-MIT.pdf
Description
Full printable version
Size
6.42 MB
Format
Adobe PDF
Checksum (MD5)
6fa46f6705b8dd5fcee5b1d5b827d5b0
Author(s)
Wong, Chi Heem
Advisor(s)
Andrew W. Lo.
Date Issued
2017
Publisher
Massachusetts Institute of Technology
Abstract
Previous estimates of drug development success rates rely on relatively small samples of pharmaceutical industry-curated databases, which are subject to potential sample selection biases. Using a sample of 185,994 unique entries of clinical-trial data for over 21,143 compounds from January 1st, 2000 to October 31st, 2015, we estimate aggregate success rates and durations of clinical trials. We also compute disaggregated estimates by stratifying across several features including: disease type, clinical phase, industry/academic sponsor, biomarker presence, lead indication status, and over time. In several cases, our results differ significantly 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, it has improved to 2.5% and 8.3% in 2014 and 2015 respectively. Also, trials with biomarkers have slightly lower success probabilities when all therapeutics groups are considered, but have much higher success probabilities in oncology and genitourinary diseases.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references (page 28).
Subjects
Electrical Engineering and Computer Science
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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