Computational modeling of the glucoregulatory system provides a critical platform for preclinical assessment and mechanistic understanding of diabetes therapies. Yet, despite its importance, glucagon a key hormone in glucose regulation remains underrepresented in physiological models. This gap limits the development of novel therapeutic strategies, such as glucose-responsive glucagon (GRG). To address this need, we introduce IMPACT 2.0, an advanced physiological compartment model that incorporates explicit glucagon kinetics and a restructured liver module. The model features mechanistic upgrades including dynamic glucose transport, receptor-ligand interactions, and hepatic glycogen turnover, enabling more accurate simulation of glycemic responses to both insulin and glucagon interventions. We validated IMPACT 2.0 using experimental data from healthy and diabetic rats, demonstrating strong predictive performance for glucose excursions following hormone administration. A sensitivity analysis was performed to assess the identifiability of model parameters under subcutaneous insulin and glucagon delivery. Notably, comparisons between diabetic and non-diabetic conditions revealed that 16 out of 37 fitted parameters significantly differed, highlighting physiological distinctions captured by the model. Furthermore, we used IMPACT 2.0 to evaluate a novel GRG therapy delivered via microneedle patch, showcasing the model's ability to link in vitro drug release profiles with in vivo metabolic outcomes. By offering a physiologically rigorous and experimentally validated representation of glucagon dynamics and hepatic metabolism, IMPACT 2.0 serves as a powerful pharmacokinetic-pharmacodynamic tool for accelerating therapeutic development, refining GRG design, and advancing closed-loop hormone delivery systems.
