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Disentangling Anti-Tumor Response of Immunotherapy Combinations: A Physiologically Based Framework for V937 Oncolytic Virus and Pembrolizumab.
Sancho-Araiz, Aymara; Parra-Guillen, Zinnia P; Troconiz, Iñaki F; Freshwater, Tomoko.
Affiliation
  • Sancho-Araiz A; Department of Pharmaceutical Science, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.
  • Parra-Guillen ZP; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.
  • Troconiz IF; Department of Pharmaceutical Science, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain.
  • Freshwater T; IdiSNA, Navarra Institute for Health Research, Pamplona, Spain.
Clin Pharmacol Ther ; 2024 Jul 22.
Article in En | MEDLINE | ID: mdl-39037559
ABSTRACT
Immuno-oncology (IO) is a growing strategy in cancer treatment. Oncolytic viruses (OVs) can selectively infect cancer cells and lead to direct and/or immune-dependent tumor lysis. This approach represents an opportunity to potentiate the efficacy of immune checkpoint inhibitors (ICI), such as pembrolizumab. Currently, there is a lack of comprehensive quantitative models for the aforementioned scenarios. In this work, we developed a mechanistic framework describing viral kinetics, viral dynamics, and tumor response after intratumoral (i.t.) or intravenous (i.v.) administration of V937 alone or in combination with pembrolizumab. The model accounts for tumor shrinkage, in both injected and non-injected lesions, induced by viral-infected tumor cell death and activated CD8 cells. OV-infected tumor cells enhanced the expansion of CD8 cells, whereas pembrolizumab inhibits their exhaustion by competing with PD-L1 in their binding to PD-1. Circulating viral levels and treatment effects on tumor volume were adequately characterized in all the different scenarios. This mechanistic-based model has been developed by combining top-down and bottom-up approaches and provides individual estimates of viral and ICI responses. The robustness of the model is reflected by the description of the tumor size time profiles in a variety of clinical scenarios. Additionally, this platform allows us to investigate not only the contribution of processes related to the viral kinetics and dynamics on tumor response, but also the influence of its interaction with an ICI. Additionally, the model can be used to explore different scenarios aiming to optimize treatment combinations and support clinical development.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Clin Pharmacol Ther / Clin. pharmacol. ther / Clinical pharmacology and therapeutics Year: 2024 Document type: Article Affiliation country: Country of publication:

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: Clin Pharmacol Ther / Clin. pharmacol. ther / Clinical pharmacology and therapeutics Year: 2024 Document type: Article Affiliation country: Country of publication: