Improving clinical trial design using interpretable machine learning based prediction of early trial termination.

Ece Kavalci¹, Anthony Hartshorn²

¹Lindus Health, London, UK. ece@lindushealth.com.

²Lindus Health, London, UK.

Abstract

This study proposes using a machine learning pipeline to optimise clinical trial design. The goal is to predict early termination probability of clinical trials using machine learning modelling, and to understand feature contributions driving early termination. This will inform further suggestions to the study protocol to reduce the risk of wasted resources. A dataset containing 420,268 clinical t…

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