Literature DB >> 31326235

Artificial Intelligence for Clinical Trial Design.

Stefan Harrer1, Pratik Shah2, Bhavna Antony3, Jianying Hu4.   

Abstract

Clinical trials consume the latter half of the 10 to 15 year, 1.5-2.0 billion USD, development cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the investment into the trial itself but also the preclinical development costs, rendering the loss per failed clinical trial at 800 million to 1.4 billion USD. Suboptimal patient cohort selection and recruiting techniques, paired with the inability to monitor patients effectively during trials, are two of the main causes for high trial failure rates: only one of 10 compounds entering a clinical trial reaches the market. We explain how recent advances in artificial intelligence (AI) can be used to reshape key steps of clinical trial design towards increasing trial success rates.
Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  artificial intelligence; cohort selection; machine learning; patient monitoring; patient recruitment; trial design

Mesh:

Year:  2019        PMID: 31326235     DOI: 10.1016/j.tips.2019.05.005

Source DB:  PubMed          Journal:  Trends Pharmacol Sci        ISSN: 0165-6147            Impact factor:   14.819


  40 in total

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