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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

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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583244/
https://www.ncbi.nlm.nih.gov/pubmed/37621010
http://dx.doi.org/10.1002/psp4.13029
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author 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
author_facet 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
author_sort Gall, Louis
collection PubMed
description 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.
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spelling pubmed-105832442023-10-19 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 CPT Pharmacometrics Syst Pharmacol Research 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. John Wiley and Sons Inc. 2023-09-11 /pmc/articles/PMC10583244/ /pubmed/37621010 http://dx.doi.org/10.1002/psp4.13029 Text en © 2023 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research
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
A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title_full A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title_fullStr A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title_full_unstemmed A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title_short A dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
title_sort dynamic model of the intestinal epithelium integrates multiple sources of preclinical data and enables clinical translation of drug‐induced toxicity
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10583244/
https://www.ncbi.nlm.nih.gov/pubmed/37621010
http://dx.doi.org/10.1002/psp4.13029
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