Integration of innovative statistical methods using genetic data provides pharmacological insight and facilitates drug development.
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Authors
Publication Date
2022-02Journal Title
Br J Clin Pharmacol
ISSN
0306-5251
Publisher
Wiley
Language
eng
Type
Article
This Version
AM
Metadata
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Grant, A. J. (2022). Integration of innovative statistical methods using genetic data provides pharmacological insight and facilitates drug development.. Br J Clin Pharmacol https://doi.org/10.1111/bcp.15114
Abstract
The use of genetic data can be of great benefit in drug development. When analysed with appropriate statistical methods, such resources can be leveraged to identify potential drug targets and inform experimental trials [1]. It has been shown that drug development done with the backing of genetic data is more likely to be successful [2]. Increasingly, pharmacological studies are able to harness the results of genome-wide association studies (GWAS), which test for associations between a phenotype and genetic variation across the entire genome. Such studies are rapidly expanding in terms of both size of samples and range of phenotypes [3]. Although GWAS are able to identify many genetic variants that are associated with a phenotypic trait of interest, they are not able to provide, on their own, evidence as to which of these associations are causal, or by which mechanisms these associations come about. New statistical methodology is being developed which uses genetic data to help to answer these questions.
Keywords
Clozapine, Drug Development, Genome-Wide Association Study, Humans, Neutropenia, Quantitative Trait Loci
Sponsorship
Wellcome Trust (204623/Z/16/Z)
Medical Research Council (MC_UU_00002/7)
Identifiers
External DOI: https://doi.org/10.1111/bcp.15114
This record's URL: https://www.repository.cam.ac.uk/handle/1810/329872
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