Clinical Pharmacology Perspectives for Adoptive Cell Therapies in Oncology. Issue 5 (21st January 2022) - Huang, Weize; Li, Junyi; Liao, Michael Z.; Liu, Stephanie N.; Yu, Jiajie; Jing, Jing; Kotani, Naoki; Kamen, Lynn; Guelman, Sebastian; Miles, Dale R.
Abstract : Adoptive cell therapies (ACTs) have shown transformative efficacy in oncology with five US Food and Drug Administration (FDA) approvals for chimeric antigen receptor (CAR) T‐cell therapies in hematological malignancies, and promising activity for T cell receptor T‐cell therapies in both liquid and solid tumors. Clinical pharmacology can play a pivotal role in optimizing ACTs, aided by modeling and simulation toolboxes and deep understanding of the underlying biological and immunological processes. Close collaboration and multilevel data integration across functions, including chemistry, manufacturing, and control, biomarkers, bioanalytical, and clinical science and safety teams will be critical to ACT development. As ACT is comprised of alive, polyfunctional, and heterogeneous immune cells, its overall physicochemical and pharmacological property is vastly different from other platforms/modalities, such as small molecule and protein therapeutics. In this review, we first describe the unique kinetics of T cells and the appropriate bioanalytical strategies to characterize cellular kinetics. We then assess the distinct aspects of clinical pharmacology for ACTs in comparison to traditional small molecule and protein therapeutics. Additionally, we provide a review for the five FDA‐approved CAR T‐cell therapies and summarize their properties, cellular kinetic characteristics, dose‐exposure‐response relationship, and potential baseline factors/variables in product, patient, and regimen that may affect the safety and efficacy. Finally, we probe into existing empirical and mechanistic quantitative techniques to understand how various modeling and simulation approaches can support clinical pharmacology strategy and propose key considerations to be incorporated and explored in future models.