Javier Sánchez (1, 2), Valeria Nicolini (3), Linda Fahrni (3), Inja Waldhauer (3), Antje-Christine Walz (1), Candice Jamois (1), Stephen Fowler (1), Silke Simon (1), Christian Klein (3), Pablo Umaña (3), Siv Jonsson (2), Lena E. Friberg (2), Nicolas Frances (1)
(1) Roche Pharma Research and Early Development, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland. (2). Department of Pharmacy, Uppsala University, Uppsala, Sweden. (3). Roche Pharma Research and Early Development, Roche Innovation Center Zurich, Schlieren, Switzerland
Objectives: TYRP1-TCB is a CD3 T-cell bispecific (CD3-TCB) antibody developed for the treatment of advanced melanoma [1]. Upon dual binding of this molecule to TYRP1 on the tumor cell and to the CD3 receptor expressed on T-cells, an immune synapse is formed, leading to tumor cell killing. In this study, we developed a PKPD model leveraging longitudinal tumor-growth inhibition data in mouse xenografts treated with different doses of TYRP1-TCB single agent or TYRP1-TCB plus anti-PD-L1 combination. The developed PKPD model was translated to humans to support a refined clinical strategy for TYRP1-TCB.
Methods: The PKPD model was developed in Monolix v2019R2 [2]. A two-compartment PK model was developed as input for the tumor-growth inhibition model. A separate PK model, where non-linearity in central volume of distribution versus dose is accounted for by target-mediated drug disposition, was developed for PK translation to humans. A tumor-growth inhibition model describing the delay between drug exposure and tumor-shrinkage driven by TYRP1-TCB exposure in the central compartment, tumor regrowth, and the beneficial effects from anti-PD-L1 combination, was developed.
Later, this PKPD model was translated to humans. The tumor growth rate constant was selected from literature [3]. The ratio between growth constant and the maximum killing rate, between growth constants before and during tumor regrowth, as well as the synergistic parameters of the combination between TYRP1-TCB and anti-PD-L1 were assumed to be conserved across species. All other PK and PD parameters were allometrically scaled from mouse to human.
The translated model was used to simulate 1000 virtual patients using the RxODE package [4] in R version 3.6.2 [5]. The tumor growth kinetic profiles of the 1000 virtual patients were assessed as recommended by the RECIST v1.1 guidelines. Overall Response Rate (ORR), Duration of Response (DoR) and Progression-Free Survival (PFS) of the simulated tumor growth kinetic profiles were predicted assuming either high, medium or low scanning frequency (scans every 6, 9 and 12 weeks, respectively).
Results: In mice, the tumor-growth inhibition model enabled the characterization of:
1) The delay between tumor shrinkage and drug exposure lasting an average of 1.26 days
2) The EC50 (0.345 mg/L) during the tumor shrinkage phase (similar to the in vitro EC50 of 0.107 mg/L after accounting for TYRP1-TCB distribution to the tumor)
3) The tumor regrowth even in presence of TYRP1-TCB exposure
The model showed that, even though an increased dose of TYRP1-TCB in monotherapy delays the time to tumor regrowth and promotes higher tumor cell killing, it also induces a faster rate of tumor regrowth. Combination with anti-PD-L1 extended the time to tumor regrowth by 25% while also decreasing the tumor growth rate during the regrowth phase by 69% compared to the same dose of TYRP1-TCB alone.
The model translation to humans predicts that if patients’ tumors were scanned every 6 weeks, only 46% of the monotherapy responders would be detected even at a TYRP1-TCB dose resulting in exposures above the EC90. However, combination of TYRP1-TCB and anti-PD-L1 in the clinic is predicted to more than double the ORR (12.6% versus 35.2%) and median DoR (84 versus 210 days), while increasing the median PFS by more than 70% (175 days versus 301 days) compared to TYRP1-TCB monotherapy.
Conclusions: The developed PKPD model with mice data allows to characterize the benefit of the combination versus monotherapy and to propose an optimized therapy in clinic. In particular, the benefit of combining anti-PD-L1 with TYRP1 TCB comes from an extended effect duration and a controlled tumor regrowth rate after escape to treatment. The predicted RECIST-based clinical efficacy of TYRP1-TCB monotherapy is unlikely to warrant further investigation, despite its combination with anti-PD-L1 being potentially beneficial for patients. As a result, it is highly recommended to consider development of CD3-TCBs as part of a combination therapy from the outset, without the need to escalate the CD3-TCB up to the Maximum Tolerated Dose (MTD) in monotherapy and without gating the combination only on
RECIST-derived efficacy metrics from monotherapy clinical trials.
References:
[1] Nicolini VG, Waldhauer I, Freimoser-Grundschober A, Richard M, Fahrni L, Bommer E, et al. Abstract LB-389: Combination of TYRP1-TCB, a novel T cell bispecific antibody for the treatment of melanoma, with immunomodulatory agents. Cancer Research 2020;80:LB-389- LB-
[2] Monolix version 2019R2. 2019R2. Antony, France: Lixoft SAS, 2019: Lixoft; 2019.
[3] Lindauer A, Valiathan CR, Mehta K, Sriram V, de Greef R, Elassaiss-Schaap J, et al. Translational Pharmacokinetic/Pharmacodynamic Modeling of Tumor Growth Inhibition Supports Dose-Range Selection of the Anti-PD-1 Antibody Pembrolizumab. CPT Pharmacometrics Syst Pharmacol 2017;6:11-20
[4] Fidler M HM, Wilkins J, Wang W. RxODE: Facilities for Simulating from ODE-Based Models 2021.
[5] R Core Team (2019). R: A language and environment for statistical computing. Vienna, Austria. R Foundation for Statistical Computing.
Reference: PAGE 30 (2022) Abstr 9965 [www.page-meeting.org/?abstract=9965]
Poster: Drug/Disease Modelling - Oncology