(141d) Model-Aided Design and Translation of Glucose-Responsive Insulins: From Simple to Complex Mechanisms

Despite considerable experimental progress, the development of glucose-responsive insulins (GRIs) still largely depends on empirical knowledge and repeated experimentation. Moreover, the only GRI that entered the clinical trials, MK-2640, failed to replicate its outstanding preclinical performance in humans. We developed a program named PAMERAH to assist the rational design and clinical translation of GRIs. PAMERAH constitutes a framework for predicting the therapeutic efficacy of a GRI candidate from its user-specified mechanism of action, kinetics, and dosage, which we show is accurate when checked against data from experiments and literature. Results from simulated glucose clamps also agree quantitatively with recent GRI publications. We demonstrate that the model can be used to explore the vast number of permutations constituting the GRI parameter space, and thereby identify the optimal design ranges that yield desired performance. A design guide aside, PAMERAH more importantly can facilitate GRI’s clinical translation by connecting each candidate’s efficacies in rats, mice, and humans. The resultant mapping helps find GRIs which appear promising in rodents but underperform in humans. Conversely, it also allows for the discovery of optimal human GRI dynamics not captured by experiments on a rodent population. Our recent efforts focus on applying PAMERAH to more involved GRI mechanisms. We show that MK-2640’s complex mechanism of competitive receptor binding and clearance can be modeled equally well as the proof-of-concept kinetics reported earlier. The failed GRI candidate’s animal and human design spaces provide insights on why the clinical translation was challenging. On another front, we demonstrate the applicability of PAMERAH to hypothetical GRI designs before any physical prototype is built. By docking PAMERAH with circuit simulations, we demonstrate the feasibility of a microrobotic GRI where the insulin release is intelligently controlled by a printed cell-sized circuit.