Estimating Clinical Trial Success Rates and Related Parameters in Oncology

20 Pages Posted: 14 Apr 2019 Last revised: 9 May 2019

See all articles by Chi Heem Wong

Chi Heem Wong

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL); Massachusetts Institute of Technology (MIT); MIT Sloan School of Management

Kien Wei Siah

Massachusetts Institute of Technology (MIT)

Andrew W. Lo

Massachusetts Institute of Technology (MIT) - Sloan School of Management; National Bureau of Economic Research (NBER); Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Date Written: March 19, 2019

Abstract

We extend earlier large-scale studies of clinical trial statistics by focusing on the performance of oncology trials. Using 108,248 data points between January 1, 2005, and September 31, 2018, compiled from the Citeline database, we investigate the duration of clinical trials and compute the probabilities of success of 24,448 oncology drug development programs by disease group. While the overall phase 1 to approval rate for all oncology-related drug development programs is 3.3%, individual disease groups have approval rates ranging from 0% to 10.1%. Similar patterns can be seen for oncology orphan drug development programs, where the overall probability of success ranges from 0% to 8.3%, with an overall average of 1.9%. We find overwhelming evidence that using biomarkers for patient selection is effective in almost all disease groups within oncology, raising the overall probability of success by an average of 13.3%.

Keywords: Probabilities of Success; Clinical Trials; Biostatistics; Oncology; Healthcare Finance

JEL Classification: I10, I11, I13

Suggested Citation

Wong, Chi Heem and Siah, Kien Wei and Lo, Andrew W., Estimating Clinical Trial Success Rates and Related Parameters in Oncology (March 19, 2019). Available at SSRN: https://ssrn.com/abstract=3355022 or http://dx.doi.org/10.2139/ssrn.3355022

Chi Heem Wong

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL) ( email )

Stata Center
Cambridge, MA 02142
United States

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
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MIT Sloan School of Management ( email )

100 Main Street
Cambridge, MA 02142
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Kien Wei Siah

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Andrew W. Lo (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-618
Cambridge, MA 02142
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617-253-0920 (Phone)
781 891-9783 (Fax)

HOME PAGE: http://web.mit.edu/alo/www

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Massachusetts Institute of Technology (MIT) - Computer Science and Artificial Intelligence Laboratory (CSAIL)

Stata Center
Cambridge, MA 02142
United States

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