Show simple item record

dc.contributor.advisorAndrew W. Lo.en_US
dc.contributor.authorWong, Chi Heemen_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2018-03-02T22:20:51Z
dc.date.available2018-03-02T22:20:51Z
dc.date.copyright2017en_US
dc.date.issued2017en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/113964
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (page 28).en_US
dc.description.abstractPrevious 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.en_US
dc.description.statementofresponsibilityby Chi Heem Wong.en_US
dc.format.extentvi, 41 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Scienceen_US
dc.titleEstimation of clinical trial success rates and related parametersen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc1023498646en_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record