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Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response

Clinical responses of immuno‐oncology therapies are highly variable among patients. Similar response variability has been observed in syngeneic mouse models. Understanding of the variability in the mouse models may shed light on patient variability. Using a murine anti‐CTLA4 antibody as a case study...

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Autores principales: Qiao, Wenlian, Lin, Lin, Young, Carissa, Narula, Jatin, Hua, Fei, Matteson, Andrew, Hooper, Andrea, Gruenbaum, Lore, Betts, Alison
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286718/
https://www.ncbi.nlm.nih.gov/pubmed/35439371
http://dx.doi.org/10.1002/psp4.12800
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author Qiao, Wenlian
Lin, Lin
Young, Carissa
Narula, Jatin
Hua, Fei
Matteson, Andrew
Hooper, Andrea
Gruenbaum, Lore
Betts, Alison
author_facet Qiao, Wenlian
Lin, Lin
Young, Carissa
Narula, Jatin
Hua, Fei
Matteson, Andrew
Hooper, Andrea
Gruenbaum, Lore
Betts, Alison
author_sort Qiao, Wenlian
collection PubMed
description Clinical responses of immuno‐oncology therapies are highly variable among patients. Similar response variability has been observed in syngeneic mouse models. Understanding of the variability in the mouse models may shed light on patient variability. Using a murine anti‐CTLA4 antibody as a case study, we developed a quantitative systems pharmacology model to capture the molecular interactions of the antibody and relevant cellular interactions that lead to tumor cell killing. Nonlinear mixed effect modeling was incorporated to capture the inter‐animal variability of tumor growth profiles in response to anti‐CTLA4 treatment. The results suggested that intratumoral CD8+ T cell kinetics and tumor proliferation rate were the main drivers of the variability. In addition, simulations indicated that nonresponsive mice to anti‐CTLA4 treatment could be converted to responders by increasing the number of intratumoral CD8+ T cells. The model provides a mechanistic starting point for translation of CTLA4 inhibitors from syngeneic mice to the clinic.
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spelling pubmed-92867182022-07-19 Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response Qiao, Wenlian Lin, Lin Young, Carissa Narula, Jatin Hua, Fei Matteson, Andrew Hooper, Andrea Gruenbaum, Lore Betts, Alison CPT Pharmacometrics Syst Pharmacol Research Clinical responses of immuno‐oncology therapies are highly variable among patients. Similar response variability has been observed in syngeneic mouse models. Understanding of the variability in the mouse models may shed light on patient variability. Using a murine anti‐CTLA4 antibody as a case study, we developed a quantitative systems pharmacology model to capture the molecular interactions of the antibody and relevant cellular interactions that lead to tumor cell killing. Nonlinear mixed effect modeling was incorporated to capture the inter‐animal variability of tumor growth profiles in response to anti‐CTLA4 treatment. The results suggested that intratumoral CD8+ T cell kinetics and tumor proliferation rate were the main drivers of the variability. In addition, simulations indicated that nonresponsive mice to anti‐CTLA4 treatment could be converted to responders by increasing the number of intratumoral CD8+ T cells. The model provides a mechanistic starting point for translation of CTLA4 inhibitors from syngeneic mice to the clinic. John Wiley and Sons Inc. 2022-05-08 2022-07 /pmc/articles/PMC9286718/ /pubmed/35439371 http://dx.doi.org/10.1002/psp4.12800 Text en © 2022 Pfizer Inc. 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
Qiao, Wenlian
Lin, Lin
Young, Carissa
Narula, Jatin
Hua, Fei
Matteson, Andrew
Hooper, Andrea
Gruenbaum, Lore
Betts, Alison
Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title_full Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title_fullStr Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title_full_unstemmed Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title_short Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response
title_sort quantitative systems pharmacology modeling provides insight into inter‐mouse variability of anti‐ctla4 response
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9286718/
https://www.ncbi.nlm.nih.gov/pubmed/35439371
http://dx.doi.org/10.1002/psp4.12800
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