2311P - Population pharmacokinetic-pharmacodynamic modeling to inform optimal dosing strategies for GI-101, a novel fusion protein, targeting IL2βγR and CTLA4

Background

Interleukin-2 receptor (IL2R) and cytotoxic T-lymphocyte-associated protein 4 (CTLA4) are key immunotherapeutic targets in cancer treatment. GI-101, a novel bispecific Fc fusion protein, targets both CTLA4 and IL2Rβγ, offering potential for improved patient outcomes. This study developed a mathematical model linking GI-101 pharmacokinetics (PK), absolute lymphocyte count (ALC) dynamics, and progression-free survival (PFS) to optimize the biological dose for maximal therapeutic benefit.

Methods

Preclinical monkey (n=74) and phase 1/2 human (n=31) data of GI-101 were used for model development. The dataset was randomly split into training and test datasets at a ratio of 7 to 3, and the final model was validated using the test dataset. Data from a phase 1/2 clinical trial were analyzed using a random survival forest algorithm to assess the effect of immune cell dynamics on PFS. Potential dose-response correlations were assessed for Grade 3 or 4 treatment-related adverse events (TrAE) and immune-related adverse events (irAE) using logistic regression. Stochastic simulations determined the optimal biological dose (OBD) to achieve the target peak ALC.

Results

A pharmacodynamics-mediated drug disposition (PDMDD) model adequately described drug pharmacokinetics, captured changes of cell count across all lymphocyte subsets, and demonstrated strong performance in the test dataset. Random survival forest analysis of the GI-101 clinical data revealed that peak total lymphocyte (p=0.00191) and CD8+ T cell (p=0.00515) counts significantly predicted PFS. There was no significant dose-response correlation for TrAE (p=0.66) and irAE (p=0.92). Simulations suggested an OBD of 0.3 mg/kg every three weeks, achieving target peak total lymphocyte and CD8+ T cell counts of 2,000 cells/μL and 350 cells/μL, respectively.

Conclusions

Our findings underscore the value of translational mathematical modeling for informing optimal dosing strategies in novel immunotherapies targeting IL2βγR and CTLA4. The identified OBD merits further investigation in clinical trials to validate its potential for enhancing patient outcomes.

Clinical trial identification

NCT04977453

Editorial acknowledgement

Legal entity responsible for the study

GI Innovation, Inc.

Funding

GI Innovation, Inc.

Disclosure

All authors have declared no conflicts of interest.