A quantitative systems pharmacology (QSP) model of oncolytic immunotherapies based on the myxoma virus (MYXV) platform was constructed to project systemic cytokine exposure after intravenous (IV) administration, and to determine safe doses. Oncolytic viruses selectively replicate in and lyse tumor cells and provide stimulation to the immune system. The genome of MYXV is relatively large and is amenable to engineering for expression of transgenic proteins. The QSP model mechanistically describes virus administration, infection of competent cells, promoter-dependent gene transcription, cytokine payload production and secretion, and secondary cytokine responses.
An in vitro model was calibrated to cytokine release data from virus infected PBMCs. A mouse model was developed to recapitulate virus PK data and cytokine data collected in the serum of tumor-bearing mice who received various IV doses of oncolytic virus constructs. The cytokine data include time-resolved measurements of transgenic cytokine expression (the viral payload), the immediate endogenous cytokine response to the virus vehicle itself, as well as secondary cytokine responses.
Learnings from the in vitro model, the in vivo mouse model as well as from human specific literature information were used to create the human model. The resulting human model was used to project systemic expression of cytokine payloads and subsequent secondary cytokine responses for various IV doses of the oncolytic virus construct. Projected cytokine levels were compared to previously established cytokine exposure at maximum tolerated doses of IV administered cytokines to assess potential safety implications.
The impact of uncertainties in model predictions stemming from variability in the available data and from the assumptions made during model building was evaluated. The upper range of predicted systemic cytokine exposure in humans is still expected to fall within known safety margins at the planned doses of oncolytic immunotherapies.
In the absence of human data, QSP modeling represents a holistic approach of integrating all available knowledge and preclinical data for the purpose of human prediction. It yields valuable insight on the system-wide effects of IV oncolytic viral administration and can be expanded in the future to include assessment of efficacy in the form of tumor growth inhibition.
Citation Format: A. Katharina Wilkins, Lina S. Franco, Diana H. Marcantonio, Karyn L. Sutton, Joshua F. Apgar, John M. Burke, Grant McFadden, Fei Hua, Leslie L. Sharp. Prediction of systemic cytokine exposure in human after IV administration of oncolytic myxoma virus, using quantitative systems pharmacology modeling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1919.