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Review
. 2025 Oct 27.
doi: 10.1038/s41573-025-01308-z. Online ahead of print.

Quantitative systems toxicology: modelling to mechanistically understand and predict drug safety

Christopher E Goldring #  1 , Giusy Russomanno #  2 , Carmen Pin #  3 , Panuwat Trairatphisan #  4   5   6 , Kylie A Beattie #  7 , Ciarán P Fisher #  7 , Janet Piñero #  8   9 , Richard J Brennan  10 , Diana Clausznitzer  4 , Ian M Copple  2 , Theo M de Kok  11 , Carrie A Duckworth  12 , Laura I Furlong  8   9 , Barbara Füzi  13 , Attila Gabor  5 , Louis Gall  3 , Jan Hengstler  14 , Henning Hermjakob  15 , Fiona Hunter  15 , Danyel Jennen  11 , Mikko Koskinen  16 , Steven J Kunnen  17 , Lieve Lammens  18 , Sebastian Lobentanzer  5 , Marcel Mohr  6 , Elisa Passini  19   20 , D Mark Pritchard  12 , Rahuman S Malik-Sheriff  15 , Blanca Rodríguez  20 , Eric I Rossman  21 , Julio Saez-Rodríguez  5 , Friedemann Schmidt  6 , Rowena Sison-Young  2 , Inari Soininen  22 , Sean Turner  4 , Bob van de Water  17 , Johan G C van Hasselt  17 , Filippo Venezia  23 , Jeffrey A Willy  24 , Derek J Leishman  25 , James L Stevens  17 , Loic Laplanche  26
Affiliations
Review

Quantitative systems toxicology: modelling to mechanistically understand and predict drug safety

Christopher E Goldring et al. Nat Rev Drug Discov. .

Abstract

Reliable prediction and prevention of adverse drug reactions (ADRs) remains a key challenge in the development of new medicines. Advanced mathematical and computational modelling approaches, which incorporate cutting-edge mechanistic understanding of ADRs in concert with systematically collected data addressing knowledge gaps, are integral components of model-informed drug discovery and development (MID3). These approaches provide a precise, quantitative framework for predicting and mitigating safety risks in the earliest phases of drug development. Here, we highlight recent developments in the burgeoning field of quantitative systems toxicology (QST), including insights into the current state-of-the-art, as well as outcomes from the Innovative Medicines Initiative (IMI) 2 TransQST project. QST models that describe the disruption of cardiovascular, gastrointestinal, hepatic and renal physiological functions following drug exposure are presented, along with recommendations for their application in drug discovery and development.

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Conflict of interest statement

Competing interests: C.P. and L.G. are employees and shareholders of AstraZeneca. K.A.B., C.P.F. and E.I.R. are employees of GSK. F.S., M.M. and P.T. are employees and shareholders, and R.J.B. is a retired employee and shareholder of Sanofi. D.C., S.T. and L.L. are employees and shareholders of AbbVie. M.K. is an employee of Orion Corporation. L.L. is a shareholder of Johnson & Johnson. J.S.-R. reports in the past 3 years funding from GSK and Pfizer and fees or honoraria from Travere Therapeutics, Stadapharm, Astex, Owkin, Pfizer, Grunenthal, Tempus and Moderna. F.V. is an employee of Servier. J.A.W. is an employee of Vertex Pharmaceuticals. D.J.L. is an employee of Eli Lilly and Company. All other authors declared no competing interests for this work.

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