Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples

Abstract Quantitative systems toxicology (QST) models are increasingly being applied for predicting and understanding toxicity liabilities in pharmaceutical research and development. A European Federation of Pharmaceutical Industries and Associations (EFPIA)‐wide survey was completed by 15 companies...

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Main Authors: Kylie A. Beattie, Meghna Verma, Richard J. Brennan, Diana Clausznitzer, Valeriu Damian, Derek Leishman, Mary E. Spilker, Britton Boras, Zhenhong Li, Elias Oziolor, Theodore R. Rieger, Anna Sher
Format: Article
Language:English
Published: Wiley 2024-12-01
Series:CPT: Pharmacometrics & Systems Pharmacology
Online Access:https://doi.org/10.1002/psp4.13227
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author Kylie A. Beattie
Meghna Verma
Richard J. Brennan
Diana Clausznitzer
Valeriu Damian
Derek Leishman
Mary E. Spilker
Britton Boras
Zhenhong Li
Elias Oziolor
Theodore R. Rieger
Anna Sher
author_facet Kylie A. Beattie
Meghna Verma
Richard J. Brennan
Diana Clausznitzer
Valeriu Damian
Derek Leishman
Mary E. Spilker
Britton Boras
Zhenhong Li
Elias Oziolor
Theodore R. Rieger
Anna Sher
author_sort Kylie A. Beattie
collection DOAJ
description Abstract Quantitative systems toxicology (QST) models are increasingly being applied for predicting and understanding toxicity liabilities in pharmaceutical research and development. A European Federation of Pharmaceutical Industries and Associations (EFPIA)‐wide survey was completed by 15 companies. The results provide insights into the current use of QST models across the industry. 73% of responding companies with more than 10,000 employees utilize QST models. The most applied QST models are for liver, cardiac electrophysiology, and bone marrow/hematology. Responders indicated particular interest in QST models for the central nervous system (CNS), kidney, lung, and skin. QST models are used to support decisions in both preclinical and clinical stages of pharmaceutical development. The survey suggests high demand for QST models and resource limitations were indicated as a common obstacle to broader use and impact. Increased investment in QST resources and training may accelerate application and impact. Case studies of QST model use in decision‐making within EFPIA companies are also discussed. This article aims to (i) share industry experience and learnings from applying QST models to inform decision‐making in drug discovery and development programs, and (ii) share approaches taken during QST model development and validation and compare these with recommendations for modeling best practices and frameworks proposed in the literature. Discussion of QST‐specific applications in relation to these modeling frameworks is relevant in the context of the recently proposed International Council for Harmonization (ICH) M15 guideline on general principles for Model‐Informed Drug Development (MIDD).
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spelling doaj-art-a17a1566d5fd4e59a017f20987c31d4f2025-08-20T02:49:05ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062024-12-0113122036205110.1002/psp4.13227Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examplesKylie A. Beattie0Meghna Verma1Richard J. Brennan2Diana Clausznitzer3Valeriu Damian4Derek Leishman5Mary E. Spilker6Britton Boras7Zhenhong Li8Elias Oziolor9Theodore R. Rieger10Anna Sher11Target and Systems Safety Non‐Clinical Safety, GSK Stevenage UKSystems Medicine, Clinical Pharmacology and Quantitative Pharmacology R&D BioPharmaceuticals, AstraZeneca Gaithersburg Maryland USAGlobal Investigative Toxicology Sanofi Cambridge Massachusetts USAQuantitative, Translational and ADME Sciences AbbVie Deutschland Ludwigshafen GermanyComputational Sciences GSK Upper Providence Pennsylvania USATranslational and Quantitative Toxicology Eli Lilly and Company Indianapolis Indiana USAPharmacokinetics, Dynamics and Metabolism Pfizer Research and Development, Pfizer Inc. La Jolla California USAPharmacokinetics, Dynamics and Metabolism Pfizer Research and Development, Pfizer Inc. La Jolla California USATranslational Modeling and Simulation Pfizer Research and Development, Pfizer Inc. Cambridge Massachusetts USADrug Safety Research and Development Pfizer Research and Development, Pfizer Inc. Groton Connecticut USAPharmacometrics and Systems Pharmacology Pfizer Research and Development, Pfizer Inc. Cambridge Massachusetts USAClinical Pharmacology Modeling and Simulation GSK Waltham Massachusetts USAAbstract Quantitative systems toxicology (QST) models are increasingly being applied for predicting and understanding toxicity liabilities in pharmaceutical research and development. A European Federation of Pharmaceutical Industries and Associations (EFPIA)‐wide survey was completed by 15 companies. The results provide insights into the current use of QST models across the industry. 73% of responding companies with more than 10,000 employees utilize QST models. The most applied QST models are for liver, cardiac electrophysiology, and bone marrow/hematology. Responders indicated particular interest in QST models for the central nervous system (CNS), kidney, lung, and skin. QST models are used to support decisions in both preclinical and clinical stages of pharmaceutical development. The survey suggests high demand for QST models and resource limitations were indicated as a common obstacle to broader use and impact. Increased investment in QST resources and training may accelerate application and impact. Case studies of QST model use in decision‐making within EFPIA companies are also discussed. This article aims to (i) share industry experience and learnings from applying QST models to inform decision‐making in drug discovery and development programs, and (ii) share approaches taken during QST model development and validation and compare these with recommendations for modeling best practices and frameworks proposed in the literature. Discussion of QST‐specific applications in relation to these modeling frameworks is relevant in the context of the recently proposed International Council for Harmonization (ICH) M15 guideline on general principles for Model‐Informed Drug Development (MIDD).https://doi.org/10.1002/psp4.13227
spellingShingle Kylie A. Beattie
Meghna Verma
Richard J. Brennan
Diana Clausznitzer
Valeriu Damian
Derek Leishman
Mary E. Spilker
Britton Boras
Zhenhong Li
Elias Oziolor
Theodore R. Rieger
Anna Sher
Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
CPT: Pharmacometrics & Systems Pharmacology
title Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
title_full Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
title_fullStr Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
title_full_unstemmed Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
title_short Quantitative systems toxicology modeling in pharmaceutical research and development: An industry‐wide survey and selected case study examples
title_sort quantitative systems toxicology modeling in pharmaceutical research and development an industry wide survey and selected case study examples
url https://doi.org/10.1002/psp4.13227
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