Mechanistic Modeling of a Novel Oncolytic Virus, V937, to Describe Viral Kinetic and Dynamic Processes Following Intratumoral and Intravenous Administration

Abstract

V937 is an investigational novel oncolytic non-genetically modified Kuykendall strain of Coxsackievirus A21 which is in clinical development for the treatment of advanced solid tumor malignancies. V937 infects and lyses tumor cells expressing the intercellular adhesion molecule I (ICAM-I) receptor. We integrated in vitro and in vivo data from six different preclinical studies to build a mechanistic model that allowed a quantitative analysis of the biological processes of V937 viral kinetics and dynamics, viral distribution to tumor, and anti-tumor response elicited by V937 in human xenograft models in immunodeficient mice following intratumoral and intravenous administration. Estimates of viral infection and replication which were calculated from in vitro experiments were successfully used to describe the tumor response in vivo under various experimental conditions. Despite the predicted high clearance rate of V937 in systemic circulation (t_1/2 = 4.3 min), high viral replication was observed in immunodeficient mice which resulted in tumor shrinkage with both intratumoral and intravenous administration. The described framework represents a step towards the quantitative characterization of viral distribution, replication, and oncolytic effect of a novel oncolytic virus following intratumoral and intravenous administrations in the absence of an immune response. This model may further be expanded to integrate the role of the immune system on viral and tumor dynamics to support the clinical development of oncolytic viruses.

Keywords: mechanistic modeling; oncolytic virus; tumor distribution; viral dynamics; viral kinetics.

FIGURE 1

Schematic representation of the modelling and data workflow, highlighting the key processes identified at each step.

FIGURE 2

Schematic representation of the mechanistic model for viral kinetics, viral dynamics and tumor growth. uTC, uninfected tumor cells; iTC, infected tumor cells; VL_S, serum viral load and VL_VAS, viral load in tumor vasculature.

FIGURE 3

Model evaluation. Model predictions (lines) versus real observations (dots) for (A) in vitro viral replication model and (B) in vivo viral kinetic model at typical level, and (C) tumor growth inhibition model at individual level for the different experimental scenarios. ID: individual. In panel A viral dynamics of RD-ICAM-1 and SK-Mel-28 are almost equivalent and model predictions appear superimposed.

FIGURE 4

Model exploration. Model predicted time course of the different entities following intravenous (i.v.) or intratumoral (i.t.) single administration of V937 at a dose levels of 10⁴ TCID₅₀. VL_S, viral load in serum; VL_VAS, viral load in tumor vasculature; uTC, uninfected tumor cells; iTC, infected tumor cells. Log-log scale used.

FIGURE 5

Sensitivity analysis. (A) Impact of varying viral replication (α) parameter on the predicted time course of viral concentrations in viral load in serum (VL_S, left panels) and tumor size volume (right panel) following intravenous (dashed line) or intratumoral (solid line) administration of a single V937 dose of 10⁴ TCID₅₀. (B). First-order and total-order Sobol’s sensitivity indices computed using model predicted tumor size at day 14 following intravenous (i.v.) or intratumoral (i.t.) single administration of a V937 dose of 10⁴ TCID₅₀.

FIGURE 6

Model applicability. Probability of observing at least 20% of tumor shrinkage at day 14 in a simulated virtual population at different two-by-two parameter combinations after single intratumoral dose. α, viral particles released per infected cell (viral production); β, viral infectivity; RF, retention factor.