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A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug-induced toxicity.
Gall, Louis; Jardi, Ferran; Lammens, Lieve; Piñero, Janet; Souza, Terezinha M; Rodrigues, Daniela; Jennen, Danyel G J; de Kok, Theo M; Coyle, Luke; Chung, Seung-Wook; Ferreira, Sofia; Jo, Heeseung; Beattie, Kylie A; Kelly, Colette; Duckworth, Carrie A; Pritchard, D Mark; Pin, Carmen.
Affiliation
  • Gall L; Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK.
  • Jardi F; Preclinical Sciences & Translational Safety, Janssen Pharmaceutica NV, Beerse, Belgium.
  • Lammens L; Preclinical Sciences & Translational Safety, Janssen Pharmaceutica NV, Beerse, Belgium.
  • Piñero J; Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), UPF, Barcelona, Spain.
  • Souza TM; Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
  • Rodrigues D; Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
  • Jennen DGJ; Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
  • de Kok TM; Department of Toxicogenomics, GROW School for Oncology and Developmental Biology, Maastricht University, Maastricht, The Netherlands.
  • Coyle L; Boehringer Ingelheim International GmbH, Ridgefield, Connecticut, USA.
  • Chung SW; Boehringer Ingelheim International GmbH, Ridgefield, Connecticut, USA.
  • Ferreira S; Simcyp Division, Certara UK Limited, Sheffield, UK.
  • Jo H; Simcyp Division, Certara UK Limited, Sheffield, UK.
  • Beattie KA; Target and Systems Safety, Non-Clinical Safety, In Vivo/In Vitro Translation, GSK, Stevenage, UK.
  • Kelly C; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
  • Duckworth CA; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
  • Pritchard DM; Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.
  • Pin C; Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, Cambridge, UK.
CPT Pharmacometrics Syst Pharmacol ; 12(10): 1511-1528, 2023 10.
Article in En | MEDLINE | ID: mdl-37621010
ABSTRACT
We have built a quantitative systems toxicology modeling framework focused on the early prediction of oncotherapeutic-induced clinical intestinal adverse effects. The model describes stem and progenitor cell dynamics in the small intestinal epithelium and integrates heterogeneous epithelial-related processes, such as transcriptional profiles, citrulline kinetics, and probability of diarrhea. We fitted a mouse-specific version of the model to quantify doxorubicin and 5-fluorouracil (5-FU)-induced toxicity, which included pharmacokinetics and 5-FU metabolism and assumed that both drugs led to cell cycle arrest and apoptosis in stem cells and proliferative progenitors. The model successfully recapitulated observations in mice regarding dose-dependent disruption of proliferation which could lead to villus shortening, decrease of circulating citrulline, increased diarrhea risk, and transcriptional induction of the p53 pathway. Using a human-specific epithelial model, we translated the cytotoxic activity of doxorubicin and 5-FU quantified in mice into human intestinal injury and predicted with accuracy clinical diarrhea incidence. However, for gefitinib, a specific-molecularly targeted therapy, the mice failed to reproduce epithelial toxicity at exposures much higher than those associated with clinical diarrhea. This indicates that, regardless of the translational modeling approach, preclinical experimental settings have to be suitable to quantify drug-induced clinical toxicity with precision at the structural scale of the model. Our work demonstrates the usefulness of translational models at early stages of the drug development pipeline to predict clinical toxicity and highlights the importance of understanding cross-settings differences in toxicity when building these approaches.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Citrulline / Drug-Related Side Effects and Adverse Reactions Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: CPT Pharmacometrics Syst Pharmacol Year: 2023 Document type: Article Affiliation country: Reino Unido

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Citrulline / Drug-Related Side Effects and Adverse Reactions Type of study: Prognostic_studies Limits: Animals / Humans Language: En Journal: CPT Pharmacometrics Syst Pharmacol Year: 2023 Document type: Article Affiliation country: Reino Unido