Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?

2020/01/20 by Alex Zhavoronkov, Quentin Vanhaelen, Tudor I. Oprea · 153 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Medicine · #Artificial intelligence #Bioinformatics #Biology #Cell Image Analysis Techniques #Clinical Practice #Clinical pharmacology #Clinical trial #Computational Drug Discovery Methods #Computer science #Context (archaeology) #Data science #Drug #Drug discovery #Generative grammar #Identification (biology) #Internal medicine #Medicine #Pharmacology #Statistical Methods in Clinical Trials

paper · pdf · doi:10.1002/cpt.1795

published in Clinical Pharmacology & Therapeutics 107(4), 780-785 (Wiley)

openalex publication_date 2020/01/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

As the field of artificial intelligence and machine learning (AI/ML) for drug discovery is rapidly advancing, we address the question "What is the impact of recent AI/ML trends in the area of Clinical Pharmacology?" We address difficulties and AI/ML developments for target identification, their use in generative chemistry for small molecule drug discovery, and the potential role of AI/ML in clinical trial outcome evaluation. We briefly discuss current trends in the use of AI/ML in health care and the impact of AI/ML context of the daily practice of clinical pharmacologists.

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