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

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 dat...

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Main Authors: Goldring, Christopher (Author) , Russomanno, Giusy (Author) , Pin, Carmen (Author) , Trairatphisan, Panuwat (Author) , Beattie, Kylie A. (Author) , Fisher, Ciarán P. (Author) , Piñero, Janet (Author) , Brennan, Richard J. (Author) , Clausznitzer, Diana (Author) , Copple, Ian M. (Author) , de Kok, Theo M. (Author) , Duckworth, Carrie A. (Author) , Furlong, Laura I. (Author) , Füzi, Barbara (Author) , Gabor, Attila (Author) , Gall, Louis (Author) , Hengstler, Jan (Author) , Hermjakob, Henning (Author) , Hunter, Fiona (Author) , Jennen, Danyel (Author) , Koskinen, Mikko (Author) , Kunnen, Steven J. (Author) , Lammens, Lieve (Author) , Lobentanzer, Sebastian (Author) , Mohr, Marcel (Author) , Passini, Elisa (Author) , Pritchard, D. Mark (Author) , Malik-Sheriff, Rahuman S. (Author) , Rodríguez, Blanca (Author) , Rossman, Eric I. (Author) , Sáez Rodríguez, Julio (Author) , Schmidt, Friedemann (Author) , Sison-Young, Rowena (Author) , Soininen, Inari (Author) , Turner, Sean (Author) , van de Water, Bob (Author) , van Hasselt, Johan G. C. (Author) , Venezia, Filippo (Author) , Willy, Jeffrey A. (Author) , Leishman, Derek J. (Author) , Stevens, James L. (Author) , Laplanche, Loic (Author)
Format: Article (Journal)
Language:English
Published: 27 October 2025
In: Nature reviews. Drug discovery
Year: 2025, Pages: 1-16
ISSN:1474-1784
DOI:10.1038/s41573-025-01308-z
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1038/s41573-025-01308-z
Verlag, lizenzpflichtig, Volltext: https://www.nature.com/articles/s41573-025-01308-z
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Author Notes:Christopher E. Goldring, Giusy Russomanno, Carmen Pin, Panuwat Trairatphisan, Kylie A. Beattie, Ciarán P. Fisher, Janet Piñero, Richard J. Brennan, Diana Clausznitzer, Ian M. Copple, Theo M. de Kok, Carrie A. Duckworth, Laura I. Furlong, Barbara Füzi, Attila Gabor, Louis Gall, Jan Hengstler, Henning Hermjakob, Fiona Hunter, Danyel Jennen, Mikko Koskinen, Steven J. Kunnen, Lieve Lammens, Sebastian Lobentanzer, Marcel Mohr, Elisa Passini, D. Mark Pritchard, Rahuman S. Malik-Sheriff, Blanca Rodríguez, Eric I. Rossman, Julio Saez-Rodríguez, Friedemann Schmidt, Rowena Sison-Young, Inari Soininen, Sean Turner, Bob van de Water, Johan G.C. van Hasselt, Filippo Venezia, Jeffrey A. Willy, Derek J. Leishman, James L. Stevens & Loic Laplanche

MARC

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520 |a 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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