Connecting Rodent and Human Pharmacokinetic Models for the Design and Translation of Glucose-Responsive Insulin

Abstract

Despite considerable progress, development of glucoseresponsive insulins (GRIs) still largely depends on empirical knowledge and tedious experimentation-especially on rodents. To assist the rational design and clinical translation of the therapeutic, we present a Pharmacokinetic Algorithm Mapping GRI Efficacies in Rodents and Humans (PAMERAH) built upon our previous human model. PAMERAH constitutes a framework for predicting the therapeutic efficacy of a GRI candidate from its userspecified 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 to find GRIs that appear promising in rodents but underperform in humans (i.e., false positives). Conversely, it also allows for the discovery of optimal human GRI dynamics not captured by experiments on a rodent population (false negatives). We condense such information onto a "translatability grid" as a straightforward, visual guide for GRI development.

‘Smart’ insulin-delivery technologies and intrinsic glucose-responsive insulin analogues

“…Although animal-based and pilot clinical studies were pursued, this approach is no longer under development. These challenges to create a modified insulin with an improved therapeutic index that enables tighter glycaemic control with a reduced risk for hypoglycaemia, as well as the challenges of translating in vivo animal models and data for application in humans, highlight the importance of developing better in silico GRI modelling in the developmental pipeline [23,[103][104][105].…”

“…In addition to the elegance of the associated chemistries and macromolecular structures, ongoing research has a compelling clinical motivation: to enhance the health and quality of life of patients with type 1 diabetes and of patients with type 2 diabetes refractory to oral therapy-and with less burden on patients [136]. To bridge the valley between basic science and clinical applications, in silico simulations of animal physiology and human patients are likely to provide key guidance [23,[103][104][105].…”

The future of insulin therapy

“…Therefore, the development of MK-2640 was abandoned. As animal studies were only a poor predictor of the clinical outcome, a wider use of compartmental mathematical models has been proposed for the development of future GRIs [48,49].…”

Smarter Modeling to Enable a Smarter Insulin

“…Thus, from a drug discovery perspective, there is an important unmet research need to improve the predictive value of experimental results obtained in preclinical animal models. In this issue of Diabetes , Yang et al ( 12 ) address this unmet need by providing a mathematical model (Pharmacokinetic Algorithm Mapping GRI Efficacies in Rodents and Humans [PAMERAH]) to predict whether a GRI can provide a favorable outcome in clinical studies based upon preclinical observations in mice and rats. Their compartmental model describes the complex set of integrated interactions that control plasma glucose.…”

“…Similar mathematical models integrating pharmacokinetics (PK) and pharmacodynamics (PD) are often applied in drug discovery projects, but the extensive literature about insulin PK/PD contributed to the ability to construct the high-quality PAMERAH model. Of particular note, Yang et al ( 12 ) suggest that a universal signature of glucose responsiveness is the ability of GRI therapy to enhance hepatic glucose uptake in hyperglycemia more than an equivalent concentration of a non-GRI treatment. This is consistent with the hypothesis that an insulin preferentially active at the liver might diminish hypoglycemia risk ( 13 ).…”