Collaboration with Pfizer - Published in CPT:Pharmacometrics & Systems Pharmacology

Abstract

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. Non-linear 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 intra-tumoral CD8+ T cell kinetics and tumor proliferation rate were the main drivers of the variability. In addition, simulations indicated that non-responsive mice to anti-CTLA4 treatment could be converted to responders by increasing the number of intra-tumoral CD8+ T cells. The model provides a mechanistic starting point for translation of CTLA4 inhibitors from syngeneic mice to the clinic.

Authors

Wenlian Qiao, Lin Lin, Carissa Young, Jatin Narula, Fei Hua, Andrew Matteson, Andrea Hooper, Lore Gruenbaum, Alison Betts (2022)

 

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