A genomic-led strategy to anticipate drug safety effects

Safety-related issues account for approximately 25% of failures in new drug discovery programs. On top of that, many are discovered during post-marketing surveillance, significantly limiting drug utility and application. To proactively address these concerns, we developed a genetics-led strategy leveraging Mendelian Randomization (MR) across large-scale genetic datasets from the Million Veteran Program, FinnGen, and UK Biobank. By mapping genetic variants associated with gene expression and protein abundance to 1,449 harmonized human phenotypes, we systematically identified potential adverse drug reactions (ADR). Our extensive MR analysis, encompassing 16,915 protein-coding genes, demonstrated the capacity to predict hundreds of known ADR for approved medications, with approximately 40% corroborated by FDA Adverse Event Reporting System (FAERS) data. Additionally, we found significant enrichment of identified gene-mechanism pairs in clinical trials terminated early due to safety concerns, highlighting the clinical utility of genetics-informed safety prediction. Notably, immune-related pathways were prominently associated with ADR, indicating particular sensitivity within immune modulation targets. Our comprehensive atlas, integrating genetic evidence with pharmacological mechanisms, provides a robust predictive framework for anticipating drug safety, potentially enhancing decision-making in drug development and pharmacovigilance. An interactive web interface allowing filtering by gene, phenotype, drug phase, and mechanism of action is available at https://shiny.parse-health.org/safety/.

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Publication Details

Journal
PLoS Genetics
Published
2026-07-16
DOI
https://doi.org/10.1371/journal.pgen.1012211
Primary Topic
Biotechnology and Related Fields
Type
article
Field-Weighted Citation Impact
0.00

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article

A genomic-led strategy to anticipate drug safety effects

Hesam Dashti, Danielle Rasooly, Liam Gaziano, Nicole Kosik et al.
PLoS Genetics
Biotechnology and Related Fields
article

A genomic-led strategy to anticipate drug safety effects

Hesam Dashti, Danielle Rasooly, Liam Gaziano, Nicole Kosik, John C. Whittaker, Juan P. Casas, Mohd Anisul Karim, Claudia Giambartolomei, Alexandre C. Pereira, Lauren Costa, Fiona Hunter, Andrew R. Leach, Gina M. Peloso, Sumitra Muralidhar, Brian R. Ferolito, Kelly Cho, Harris Ioannidis, Barbara Zdrazil, Claudia Langenberg, Daniel J Golden, Maya Ghoussaini, Yakov A. Tsepilov, Ines Smit, Tianxi Cai, Andréa R. V. R. Horimoto, Rachael Matty, J. Michael Gaziano, Kai Gravel-Pucillo, Giovanna Winicki
article en

Abstract

Safety-related issues account for approximately 25% of failures in new drug discovery programs. On top of that, many are discovered during post-marketing surveillance, significantly limiting drug utility and application. To proactively address these concerns, we developed a genetics-led strategy leveraging Mendelian Randomization (MR) across large-scale genetic datasets from the Million Veteran Program, FinnGen, and UK Biobank. By mapping genetic variants associated with gene expression and protein abundance to 1,449 harmonized human phenotypes, we systematically identified potential adverse drug reactions (ADR). Our extensive MR analysis, encompassing 16,915 protein-coding genes, demonstrated the capacity to predict hundreds of known ADR for approved medications, with approximately 40% corroborated by FDA Adverse Event Reporting System (FAERS) data. Additionally, we found significant enrichment of identified gene-mechanism pairs in clinical trials terminated early due to safety concerns, highlighting the clinical utility of genetics-informed safety prediction. Notably, immune-related pathways were prominently associated with ADR, indicating particular sensitivity within immune modulation targets. Our comprehensive atlas, integrating genetic evidence with pharmacological mechanisms, provides a robust predictive framework for anticipating drug safety, potentially enhancing decision-making in drug development and pharmacovigilance. An interactive web interface allowing filtering by gene, phenotype, drug phase, and mechanism of action is available at https://shiny.parse-health.org/safety/.

PLoS GeneticsVol. 22(7)
University of North Carolina at Charlotte (US), Broad Institute (US), LifeArc (GB), Boston University (US), Brigham and Women's Hospital (US), Novartis (Switzerland) (CH), Harvard University (US), Queen Mary University of London (GB), Regeneron (United States) (US), University of Cambridge (GB), Open Targets (GB), Novartis (China) (CN), Human Technopole (IT), Bioinformatics Institute (RU), Varian Medical Systems (Switzerland) (CH), Department of Veterans Affairs (AU), Varian Medical Systems (United States) (US)
U.S. Department of Energy, U.S. Department of Veterans Affairs, Office of Research and Development, Office of Science, Medical Research Council, Oak Ridge National Laboratory
Openalex Percentile: Top 100%
Biotechnology and Related Fields
DOIOpen Access PDFOpenAlex
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