Goutam Nair, Dinesh Bedathuru, Bhairav Palleja, Debarshi Mitra, Seshasai Pallikonda Chakravarthy
Vantage Research Inc 16192, Coastal Highway Lewes DE, 19958
Introduction: CD3 bispecifics are engineered antibodies that bind CD3 on T cells and target antigens on cancer cells (TAAs), activating T cells to kill cancerous cells. However, they may induce adverse effects such as CRS (Cytokine Release Syndrome) from on-target off-tumor toxicity, prompting ongoing research to define the optimal therapeutic balance. Research aimed at optimizing CD3 bispecifics for cancer therapy involves integrating mechanistic modeling with experimental data to comprehensively elucidate the drug’s mechanism of action (effected via the bispecific – TAA – CD3 trimers) in tumor and normal tissues, emphasizing tumor-associated antigen (TAA) receptor occupancy as pivotal in determining both efficacy and potential adverse events like cytokine release syndrome (CRS).
Objectives: The primary goal of developing CD3 bispecific’s QSP platform models is to simulate alternative dose fractionation techniques in the patient population by varying T-Cell numbers and TAA expression levels, thereby facilitating their potential applications in early clinical stages. We focus on Xaluritamig (a STEAP TDB for prostate cancer). In particular, we simulate the following scenarios:
1. To simulate tumor tissue (surrogate for efficacy) and normal tissue Bispecific – TAA – CD3 complex formation (surrogate for safety) for different doses of Xaluritamig.
2. Recommend an alternate dosing regimen and incremental dose for Xaluritamig based on optimal trimer formation by calibrating the platform model to capture (PK/PD) properties, and safety profiles obtained from previous studies or clinical trials.
3. Explore dose priming strategies to mitigate CRS/adverse events.
Methods: In this study, a Quantitative Systems Pharmacology (QSP) platform model was developed for a 2+1 STEAP1 x CD3 bispecific antibody targeting prostate cancer. This platform model was built upon the foundation provided by Hosseini et al. (2020) [1], which elucidated drug interactions with CD3 and tumor-associated antigens, influencing dimer/trimer formation along with the T cell dynamics. Furthermore, the study highlighted the crucial importance of target receptor occupancy in dictating both drug efficacy and toxicity, providing valuable insights for non-Hodgkin’s lymphoma cancer indication with a 1+1 CD3 bispecific antibody. In this work, we have further extended this model to a 1+2 bivalent bispecific antibody for Prostate cancer indication to determine the optimal efficacy and dose priming strategy to mitigate CRS. We have used the clinical data for Xaluritamig available from the public source [2] to calibrate and validate this expanded platform model. In this work, we have used IL6 as the primary biomarker for toxicity as it strongly correlates with CRS events.
Results: The QSP model effectively represented complex PBPK characteristics of drug and T Cells, clinical efficacy, and cytokine biomarker data post-Xaluritamig dosing in prostate cancer.
1. It accurately predicted observed biological phenomena, including cytokine Cmax suppression, with step-up dosing and emphasized the significance of on-target off-tumor binding in CRS and toxicity in a cohort of patients with varying TCell concentrations & antigen expression.
2. Explored dose priming strategies to mitigate CRS/adverse events.
Conclusions: The model also has the capability to study the impact of antigen expression levels, binding affinities, and baseline T Cell concentration on anti-tumor efficacy and CRS incidence. This platform approach can be used in early clinical drug development stages to inform dose priming strategies,
1. Clinical trial outcomes such as efficacy and toxicity predictions.
2. The developed QSP platform model can be applied across different solid cancer indications.
References:
[1] Hosseini, Iraj 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 systems biology and applications vol. 6,1 28. 28 Aug. 2020, doi:10.1038/s41540-020-00145-7.
[2] Kelly, William K et al. “Xaluritamig, a STEAP1 × CD3 XmAb 2+1 Immune Therapy for Metastatic Castration-Resistant Prostate Cancer: Results from Dose Exploration in a First-in- Human Study.” Cancer discovery vol. 14,1 (2024): 76-89. doi:10.1158/2159-8290.CD-23-0964
Reference: PAGE 32 (2024) Abstr 11132 [www.page-meeting.org/?abstract=11132]
Poster: Drug/Disease Modelling - Oncology