Quantitative systems pharmacology modeling provides insight into inter‐mouse variability of Anti‐CTLA4 response. (8th May 2022)

• Record Type: Journal Article
• Authors: Qiao, Wenlian; Lin, Lin; Young, Carissa; Narula, Jatin; Hua, Fei; Matteson, Andrew; Hooper, Andrea; Gruenbaum, Lore; Betts, Alison
• Is Part Of: CPT: pharmacometrics & systems pharmacology. Volume 11:Number 7(2022)
• Page Start: 880
• Page End: 893
• Publication Date: 2022-05-08
• Subjects: Pharmacokinetics -- Periodicals; Pharmacology -- Periodicals; Pharmacokinetics; Periodicals; 615.05
• DOI: 10.1002/psp4.12800
• Languages: English
• ISSNs: 2163-8306

Abstract

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. 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.