(T-008) Model-informed dose priming strategy for T cell engagers: Leveraging early clinical data to mitigate CRS

Ravi Kumar Pallantla – Vantage Research Inc; Pratik Mondal – Vantage Research Inc; Saumya Yadav – Vantage Research Inc; Goutam Nair – Vantage Research Inc; Mrittika Roy – Vantage Research Inc; Seshasai Chakravarthy – Vantage Research Inc; Dinesh Bedathuru – Vantage Research Inc; Bhairav Paleja – Vantage Research Inc; Rukmini Kumar – Vantage Research Inc

Introduction: CD3 bispecific T cell engagers (TCEs) are potent immunotherapies that redirect T cells to tumor-associated antigens, but they frequently induce cytokine release syndrome (CRS), particularly during initial dosing. Step-up (priming) regimens are used to reduce CRS risk but are often determined empirically over multiple dose-escalation cohorts. Epcoritamab, a subcutaneously administered CD3 × CD20 bispecific antibody, has shown promising activity in patients with B-cell non-Hodgkin lymphoma, with CRS emerging as a key early toxicity that guided the adoption of step-up strategies.

Objectives: To determine whether early clinical cohort data from Epcoritamab early phase trial can be used within a mechanistic QSP modeling framework to identify efficient step-up regimens and optimal target doses. The model aims to support priming strategy design and therapeutic dose selection for distinct patient populations.

Methods: A mechanistic QSP model was developed incorporating subcutaneous pharmacokinetics, CD3/CD20 trimer formation, T cell activation, cytokine release, and tumor growth inhibition (TGI) (1, 2). The model was calibrated using early clinical cohort data from EPCORE NHL-1 study (3) and simulated across multiple dosing strategies. A virtual population (Vpop) was generated to capture variability in immune responsiveness and tumor burden. Step-up regimens ranging from 2 to 4 steps were evaluated for their impact on predicted cytokine release syndrome (CRS), pharmacologic engagement, and tumor-killing outcomes across the Vpop (4).

Results: Model simulations reproduced observed CRS incidence and TGI trends across dose levels. Step-up priming regimens with fewer escalation steps achieved comparable safety and maintained tumor suppression similar to more prolonged regimens. Simulations across the Vpop showed that efficient step-up strategies could reduce CRS incidence while maintaining robust T cell activation and predicted tumor control.

Conclusions: This case study illustrates the value of integrating early clinical data into QSP models to design rational step-up dosing strategies for CD3 bispecifics. For TCEs, model-guided identification of priming strategies may reduce the need for extended cohort-based escalation, support more efficient entry into therapeutic dose ranges, and inform adaptive designs in future development.

Citations: 1. Nair G, et al., Development of QSP platform model for predicting clinical efficacy and CRS incidence of CD3 bispecifics in STEAP1 Prostate Cancer. Poster presented at ACoP 2024
2. Hosseini I, et al., Mitigating the risk of cytokine release syndrome in a Phase I trial of CD20/CD3 bispecific antibody mosunetuzumab in NHL: impact of translational system modeling. NPJ Syst Biol Appl. 2020 Aug 28;6(1):28.
3. Hutchings M, et al., Dose escalation of subcutaneous epcoritamab in patients with relapsed or refractory B-cell non-Hodgkin lymphoma: an open-label, phase 1/2 study. Lancet. 2021 Sep 25;398(10306):1157-1169.
4. Joslyn LR, et al., Digital twins elucidate critical role of Tscm in clinical persistence of TCR-engineered cell therapy. NPJ Syst Biol Appl. 2024 Jan 26;10(1):11.

Keywords: Dose priming, T-cell engagers, QSP