Quantitative Systems Pharmacology Modeling And Analysis Provides Biological Insights Into Anti -Pd-1 Dosing And Predicts Optimal Pd-1 X Tim-3 Therapeutic Properties For Bispecifics And Fixed Dose Combinations In Immuno-Oncology

Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LAThe goal of this collaboration was to enable early quantitative thought experiments and risk assessments by developing and interrogating a quantitative systems pharmacology (QSP) model of the co-modulation inhibitory receptors PD-1 and TIM-3 in immuno-oncology. The QSP model was to: (1) provide predictions of best-in-class profiles for a PD-1 and TIM-3 fixed dose combination (FDC) and dual antagonist platforms, and (2) provide biological insights.The QSP model was based on first principles as a system of elementary mass-action, mechanistic PKPD, ordinary differential equations. The model parameters and reactions were based on biophysics, and are interpretable. The model reactions include protein synthesis and elimination, ligand-receptor and drug-target formation and turnover, and drug administration and first order clearance. There were four versions of the model: PD-1 monospecific, TIM-3 monospecific, PD-1 x TIM-3 bispecific and fixed dose combination (FDC) targeting PD-1 and TIM-3. The monospecific models were then benchmarked against published data such that model parameter values were set to known values and unknown parameters were estimated. Once benchmarked, the FDC and bispecific models were analyzed by systematically investigating how tuning the model parameters (e.g., affinity, avidity, dose, half-life, target expression, etc.) impacted target inhibition, and to simulate patient variability.The model predictions were in good agreement with published clinical data from Nivolumab and Pembrolizumab, providing a hypothesis for the apparent inconsistencies in similar clinical doses for therapeutics with affinities differing by several orders of magnitude, and data from RMT3-23 in the TIM-3 driven mouse model. QSP model analysis predicted: (1) there would be diminishing returns on very tight binding biologics due to Target Mediated Drug Disposition (TMDD) that offsets potency, and (2) there is no advantage between FDC, 2-2 bispecific, and 2-1 bispecific formats, which are predicted to be roughly equivalent.Citation Format: Joshua Apgar, Jamie Wong, Ryan Phennicie, Robert Mabry, Tatiana Novobrantseva, Michael Briskin, John M. Burke. Quantitative systems pharmacology modeling and analysis provides biological insights into anti-PD-1 dosing and predicts optimal PD-1 x TIM-3 therapeutic properties for bispecifics and fixed dose combinations in immuno-oncology. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 5001.