Griffen, EJ, Dossetter, AG, Leach, AG and Montague, S (2018) Can we accelerate medicinal chemistry by augmenting the chemist with Big Data and artificial intelligence? Drug Discovery Today. ISSN 1359-6446

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Abstract

It is both the best of times and the worst of times to be a medicinal chemist. Massive amounts of data combined with machine-learning and/or artificial intelligence (AI) tools to analyze it can increase our capabilities. However, drug discovery faces severe economic pressure and a high level of societal need set against challenging targets. Here, we show how improving medicinal chemistry by better curating and exchanging knowledge can contribute to improving drug hunting in all disease areas. Although securing intellectual property (IP) is a critical task for medicinal chemists, it impedes the sharing of generic medicinal chemistry knowledge. Recent developments enable the sharing of knowledge both within and between organizations while securing IP. We also explore the effects of the structure of the corporate ecosystem within drug discovery on knowledge sharing.

Item Type:	Article
Uncontrolled Keywords:	1115 Pharmacology And Pharmaceutical Sciences
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RM Therapeutics. Pharmacology
Divisions:	Pharmacy & Biomolecular Sciences
Publisher:	Elsevier
Related URLs:	https://www.ncbi.nlm.nih.gov/pubmed/29577971
Date Deposited:	20 Apr 2018 10:02
Last Modified:	04 Sep 2021 10:33
DOI or ID number:	10.1016/j.drudis.2018.03.011
URI:	https://researchonline.ljmu.ac.uk/id/eprint/8484

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