Assessment of Clinical Response to V937 Oncolytic Virus After Intravenous or Intratumoral Administration Using Physiologically‐Based Modeling

Abstract

Oncolytic viruses (OVs) represent a potential therapeutic strategy in cancer treatment. However, there is currently a lack of comprehensive quantitative models characterizing clinical OV kinetics and distribution to the tumor. In this work, we present a mechanistic modeling framework for V937 OV, after intratumoral (i.t.) or intravascular (i.v.) administration in patients with cancer. A minimal physiologically‐based pharmacokinetic model was built to characterize biodistribution of OVs in humans. Viral dynamics was incorporated at the i.t. cellular level and linked to tumor response, enabling the characterization of a direct OV killing triggered by the death of infected tumor cells and an indirect killing induced by the immune response. The model provided an adequate description of changes in V937 mRNA levels and tumor size obtained from phase I/II clinical trials after V937 administration. The model showed prominent role of viral clearance from systemic circulation and infectivity in addition to known tumor aggressiveness on clinical response. After i.v. administration, i.t. exposure of V937 was predicted to be several orders of magnitude lower compared with i.t. administration. These differences could be overcome if there is high virus infectivity and/or replication. Unfortunately, the latter process could not be identified at the current clinical setting. This work provides insights on selecting optimal OV considering replication rate and infectivity.

Mathematical Modeling of Oncolytic Virus Therapy Reveals Role of the Immune Response

“…The model without an immune response fails to capture the small oscillation present in the treated tumor data and also predicts that virus will simply decay. Other studies have also found it necessary to incorporate an immune response to accurately capture the behavior of oncolytic viruses, although the mathematical implementation of the immune response differed from the implementation presented in this manuscript [ 31 , 48 ]. The importance of the immune response is also supported by experimental studies that have found that due to the interaction of OVs with the tumor system, an immune response will almost always be elicited [ 49 , 50 ].…”

“…This potentially indicates that the viruses had greater success in delaying tumor growth due to higher infection rates and less clearance of the virus, allowing it to proliferate further. Other studies have also noted the importance of high viral infectivity and low viral clearance in tumor suppression [ 48 , 58 , 59 ]. The high value of is consistent with the idea that the optimal immune response is one that builds slowly, allowing viral replication to slow, but not stop replication, helping to prolong the infection.…”

Moving the needle for oncology dose optimization: A call for action

“…We are pleased to note steady progress in this area, with several recent publications across all three ASCPT journals highlighting advances in translational, quantitative, and clinical pharmacology applications for these emerging anticancer therapeutics. 50 , 51 , 52 , 53 , 54 , 55 As we learn from present and future real‐life examples and continue to refine best practices in oncology dose optimization, we invite our readership and cross‐sector practitioners to submit these advances for timely publication. We trust that the scientific discussion and rigorous debate that will ensue across our communities of practice, further facilitated by ASCPT's Networks and Communities, will go a long way in elevating patient‐focused evidence generation for maximizing the benefit/ risk profile of next‐generation oncology therapies.…”

Novel Therapeutic Modalities: The Future is Now

“…23 Physiologically-based PK (PBPK) and quantitative systems pharmacology (QSP) modeling approaches are also evolving to support development of novel modalities. Parra-Guillen et al 24 describe the development and application of a mechanistic PBPK model linked to tumor response to assess clinical response to an oncolytic virus. Renardy et al 25 demonstrate the potential value of mechanistic models for an entirely different class of novel modalities: microbiome therapies.…”