Quantitative model of the relationship between dipeptidyl peptidase-4 (DPP-4) inhibition and response: meta-analysis of alogliptin, saxagliptin, sitagliptin, and vildagliptin efficacy results.

Dipeptidyl peptidase-4 (DPP-4) inhibition is a well- characterized treatment for type 2 diabetes mellitus (T2DM). The objective of this model-based meta-analysis was to describe the time course of HbA1c response after dosing with alogliptin (ALOG), saxagliptin (SAXA), sitagliptin (SITA), or vildagliptin (VILD). Publicly available data involving late-stage or marketed DPP-4 inhibitors were leveraged for the analysis. Nonlinear mixed-effects modeling was performed to describe the relationship between DPP-4 inhibition and mean response over time. Plots of the relationship between metrics of DPP-4 inhibition (ie, weighted average inhibition [WAI], time above 80% inhibition, and trough inhibition) and response after 12 weeks of daily dosing were evaluated. The WAI was most closely related to outcome, although other metrics performed well. A model was constructed that included fixed effects for placebo and drug and random effects for intertrial variability and residual error. The relationship between WAI and outcome was nonlinear, with an increasing response up to 98% WAI. Response to DPP-4 inhibitors could be described with a single drug effect. The WAI appears to be a useful index of DPP-4 inhibition related to HbA1c. Biomarker to response relationships informed by model-based meta-analysis can be leveraged to support study designs including optimization of dose, duration of therapy, and patient population.