Predicting clinical trial duration via statistical and machine learning models.

Journal: Contemporary clinical trials communications
Published Date: Mar 31, 2025

Abstract

We apply survival analysis as well as machine learning models to predict the duration of clinical trials using the largest dataset so far constructed in this domain. Neural network-based DeepSurv yields the most accurate predictions and we identify key factors that are most predictive of trial duration. This methodology may help clinical researchers optimize trial designs for expedited testing, and can also reduce the financial risk of drug development, which in turn will lower the cost of funding and increase the amount of capital allocated to this sector.

Authors

  • Joonhyuk Cho
    MIT Laboratory for Financial Engineering, Cambridge, MA, USA.
  • Qingyang Xu
    School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai 264209, China.
  • Chi Heem Wong
    Massachusetts Institute of Technology, Cambridge, MA.
  • Andrew W Lo
    Massachusetts Institute of Technology, Cambridge, MA.

Keywords

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