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.