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Causal inference in drug discovery and development
JournalArticle (Originalarbeit in einer wissenschaftlichen Zeitschrift)
 
ID 4699250
Author(s) Michoel, Tom; Zhang, Jitao David
Author(s) at UniBasel Zhang, Jitao David
Year 2023
Title Causal inference in drug discovery and development
Journal Drug discovery today
Volume 28
Number 10
Pages / Article-Number 103737
Keywords causal inference, drug discovery, drug development
Abstract To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and improving decision-making in drug discovery. Although it has been applied across the value chain, the concepts and practice of causal inference remain obscure to many practitioners. This article offers a nontechnical introduction to causal inference, reviews its recent applications, and discusses opportunities and challenges of adopting the causal language in drug discovery and development.
Publisher Elsevier
ISSN/ISBN 1359-6446
edoc-URL https://edoc.unibas.ch/95801/
Full Text on edoc Available
Digital Object Identifier DOI 10.1016/j.drudis.2023.103737
PubMed ID http://www.ncbi.nlm.nih.gov/pubmed/37591410
ISI-Number MEDLINE:37591410
Document type (ISI) Journal Article, Review
 
   

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