Quantitative Characterization of Innate and Adaptive Pharmacology of Allogeneic anti-CD20 Chimeric Antigen Receptor (CAR) Vδ1 γδ T cells using Multiscale Mechanistic Modeling.

Authors

Devam A Desai, Omar Elashkar, Rodrigo Cristofoletti, Ganesh Mugundu, Aman P Singh

Published in

The AAPS journal. Volume 28. Issue 6. Sep 18, 2026. Epub Sep 18, 2026.

Abstract

Gamma Delta (γδ) T Cells are currently being evaluated as a therapeutic alternative to traditional alpha-beta (αβ) T-cells due to their superior safety profile and enhanced tissue retention properties. The application of CAR technology to gamma delta (γδ) T cells presents a novel therapeutic avenue with the potential to overcome some limitations of conventional CAR T-cell therapies, such as targeting solid tumors and reducing on-target, off-tumor toxicities. The objective of this manuscript is development of a translational PK-PD framework to first characterize in vitro killing potential of un-transduced and CAR transduced anti- CD20 Vδ1 γδ T cells as well as development of an in vivo mechanistic CK-PD model designed to understand the complex dynamics of CAR γδ T cells and their interaction with IL-15 and tumor cells. All the preclinical and clinical datasets along with relevant information were digitized and obtained from the published work on Adicet Bio's AD-001. The developed model was able to estimate the in vitro killing potential of untransduced and CAR transduced anti- CD20 Vδ1 γδ T cells as well as expansion, tissue distribution, the impact of lymphodepletion and interleukin-15 (IL-15), and the tumor-killing potential of CAR-modified γδ T cells. These insights offer a deeper understanding of the potential therapeutic benefits and mechanisms of γδ T cells in immunotherapy, particularly in their application against various cancers. The development of this translational framework can be paramount in understanding the underlying dose-exposure-response relationship of CAR modified γδ T cell therapy and facilitate the discovery and development of these agents.

PMID:
42760488
Bibliographic data and abstract were imported from PubMed on 19 Sep 2026.

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