Critical Appraisal and Future Challenges of Artificial Intelligence and Anticancer Drug Development

Author:

Chamorey Emmanuel1ORCID,Gal Jocelyn1ORCID,Mograbi Baharia2,Milano Gérard3

Affiliation:

1. Epidemiology and Biostatistics Department, Centre Antoine Lacassagne, University Côte d’Azur, 33 Avenue de Valombrose, 06189 Nice, France

2. FHU OncoAge, IHU RespirERA, IRCAN, Inserm, University Côte d’Azur, CNRS 7284, U1081, 06000 Nice, France

3. Oncopharmacology Unit, Centre Antoine Lacassagne, University Côte d’Azur, 33 Avenue de Valombrose, 06189 Nice, France

Abstract

The conventional rules for anti-cancer drug development are no longer sufficient given the relatively limited number of patients available for therapeutic trials. It is thus a real challenge to better design trials in the context of new drug approval for anti-cancer treatment. Artificial intelligence (AI)-based in silico trials can incorporate far fewer but more informative patients and could be conducted faster and at a lower cost. AI can be integrated into in silico clinical trials to improve data analysis, modeling and simulation, personalized medicine approaches, trial design optimization, and virtual patient generation. Health authorities are encouraged to thoroughly review the rules for setting up clinical trials, incorporating AI and in silico methodology once they have been appropriately validated. This article also aims to highlight the limits and challenges related to AI and machine learning.

Funder

IHU Respira University Nice Cote d’Azur

Publisher

MDPI AG

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