Pharmacology Model Predicts Treatment Benefits of Mosunetuzumab Among Patients With Non-Hodgkin Lymphoma

Results from the Phase 1/2 Dose-Escalation/Expansion GO29781 Trial 

According to findings of the phase 1/2 GO29781 trial recently published in Clinical and Translational Science, a quantitative systems pharmacology (QSP) model predicted that increased exposure to mosunetuzumab, an anti-CD20-CD3 T-cell engaging bispecific antibody, improved tumor size reduction among patients with relapsed/refractory (R/R) non-Hodgkin lymphoma (NHL).

Monica E. Susilo, MD, Genentech Inc., San Francisco, California, and coauthors aimed to develop a workflow to generate digital twins, or individualized virtual patients (iVPs), which they described as “a virtual representation of a mosunetuzumab-treated clinical patient that integrates patient-specific clinical data (i.e., pharmacokinetics, tumor size, and biomarker data) alongside other in vitro/in vivo data within the established mosunetuzumab QSP model.” By doing so, Dr Susilo and colleagues were able to “simulate the response of the [virtual population] to mosunetuzumab at different dosing regimens to more robustly identify the clinical dose–response and propose predictive biomarkers to distinguish responders from nonresponders within the [virtual population].” 

Using this novel workflow, researchers aimed to reach an endpoint of evaluating the efficacy, safety, tolerability, and pharmacokinetics (PKs) of mosunetuzumab monotherapy among patients with R/R NHL, as well as the potential biological differences between patients who responded well to therapy (responders) vs patients who did not respond well to treatment (non-responders). 

140 iVPs were generated and assigned to dose-escalation cohorts to receive mosunetuzumab monotherapy at 2 different dosing regimens in order to analyze the potential biological differences between responders and non-responders. 73 iVPs were assessed for diffuse large b-cell lymphoma (DLBCL) and transformed follicular lymphoma (FL), and 50 were assessed for FL. 

Results of the novel model simulations suggest that tumor parameters, including size, proliferation rate, baseline T-cell infiltration, and parameters defining the effect of mosunetuzumab on T-cell activation and B-cell killing, were factors that could potentially influence response to the treatment. Results also suggest that the antitumor activity of mosunetuzumab may be due to the expansion of pre-existing T-cells within the tumor, rather than an influx of T-cells from the rest of the body. Finally, the simulations based on the virtual population that represented data from prior studies predicted that an increase in mosunetuzumab monotherapy would reduce tumors by at least 50% by day 42. 

Dr Susilo et al concluded that findings “demonstrate that a single mechanistic QSP model can be applied to support the molecule's clinical development for both efficacy and safety, as well as the identification of potential biological determinants of clinical response.”

Source:

Susilo ME, Li CC, Gadkar K, et al. Systems-based digital twins to help characterize clinical dose-response and propose predictive biomarkers in a Phase I study of bispecific antibody, mosunetuzumab, in NHL. Clinical and Translational Science. Published online March 13, 2023. doi:https://doi.org/10.1111/cts.13501