In Silico Hypothesis Testing in Drug Discovery: Using Quantitative Systems Pharmacology Modeling to Evaluate the...

Background/Objectives: Proinsulin, the precursor to insulin, has limited activity on the insulin receptor. Proinsulin levels increase with increasing insulin resistance in type 2 diabetes due to incomplete processing by the β-cell. To assess whether the development of peptides that could convert circulating proinsulin to insulin in the blood would provide therapeutic value, we used a quantitative systems pharmacology (QSP) model of glucose homeostasis. In silico hypothesis testing such as this is an example of how modeling can inform decisions in drug discovery. Methods: In silico hypothesis testing involved (1) the addition and qualification of proinsulin biology into a preexisting QSP model, (2) the creation and validation of virtual patients (VPs) for subpopulations of type 2 diabetics based on phenotypic traits, and (3) the simulation of clinical trials evaluating the therapeutic value of the conversion of circulating proinsulin to insulin in the VPs created. Results: Proinsulin conversion led to a ~0.2% reduction in HbA1c in VPs at varying stages of diabetes, a decrease that does not hold meaningful therapeutic value. The lack of significant impact on HbA1c was likely a result of the surprisingly small effect on plasma insulin levels from proinsulin, which has a significantly slower secretion and clearance rate. Although patients with higher proinsulin/insulin ratios showed the largest reductions, clinically significant ≥ 0.5% reduction in HbA1c required ratios of proinsulin/insulin above the reported physiological range. Conclusions: This effort demonstrates how in silico hypothesis testing using QSP modeling can provide insights on the probability of success of novel interventions with minimal time and resources. These efficiencies are a means of overcoming the pressures on the pharmaceutical industry to do more with less in providing therapies that improve the lives of patients.