Population Pharmacokinetic and Pharmacodynamic Modelling and Simulation of Linagliptin, a Novel Dipeptidyl-Peptidase 4 Inhibitor for the Treatment of Type 2 Diabetes

Abstract

Linaglipin is a novel dipeptidyl-peptidase 4 (DPP-4) inhibitor in clinical development for the treatment of type 2 diabetes. This thesis investigated the nonlinear pharmacokinetics of linagliptin as well as the relationship between linagliptin pharmacokinetics and plasma DPP-4 activity using nonlinear mixed-effect modelling. The developed models supported the clinical drug development of linagliptin by clinical trial simulations. <br /> Based on previous <i>in vitro</i> plasma protein binding studies, concentration-dependent protein binding was considered to be the most likely cause of the nonlinear pharmacokinetics of linagliptin. This hypothesis was tested by analysing linagliptin plasma concentrations and plasma DPP-4 activities from two phase IIa studies in type 2 diabetic patients. A model assuming concentration-dependent protein binding of linagliptin in plasma and tissues resulted in the best description of the linagliptin plasma concentrations, supporting the initial hypothesis. Several lines of evidence suggested that the binding partner of linagliptin responsible for the nonlinear pharmacokinetics is its target, DPP-4. Accordingly, plasma DPP-4 activity was included in the model in a semi-mechanistic way by relating it to the model-calculated plasma DPP-4 occupancy with linagliptin. The assumption of target-mediated drug disposition was confirmed in a subsequent analysis evaluating the pharmacokinetics of wildtype and DPP-4 deficient rats. Both analyses suggest that concentration-dependent binding of linagliptin to plasma and tissue DPP-4 is responsible for the nonlinear pharmacokinetics of linagliptin.<br /> The nonlinear pharmacokinetics of linagliptin complicate predictions that are based solely on noncompartmental parameters. The availability of the target-mediated drug disposition model allowed simulations that greatly supported the design of future clinical studies. E.g. a twice-daily dosing strategy for a fixed dose combination of linagliptin with metformin was simulated. The simulations predicted that despite the nonlinear pharmacokinetics, 2.5 mg linagliptin twice daily would result in a bioequivalent extent of exposure (AUC_24h,SS) as well as a similar DPP-4 inhibition compared to 5 mg linagliptin once daily. <br /> Covariate analyses were performed to identify clinically relevant covariates for the pharmacokinetics and the pharmacodynamics of linagliptin. The analyses were based on linagliptin plasma concentrations and DPP-4 activities of type 2 diabetic patients from two phase IIa and two phase IIb studies. Demographic information, laboratory values including liver enzymes and creatinine clearance, as well as study related factors like metformin co-treatment were investigated. None of the tested covariates was found to be clinically relevant. <br /> For compounds with nonlinear pharmacokinetics, the standard approach to determine the absolute bioavailability is not valid. Thus, linagliptin plasma concentrations after single oral administration of 10 mg linagliptin and single intravenous administrations of 0.5, 2.5, 5, or 10 mg linagliptin were analysed by the target-mediated drug disposition model. Using this approach, the absolute bioavailability could be estimated despite the nonlinear pharmacokinetics. The absolute bioavailability was estimated to be 29.5%.<br /> In conclusion, the work presented in this thesis contributes to a comprehensive understanding and characterisation of the nonlinear pharmacokinetics of the novel DPP-4 inhibitor linagliptin and significantly supports the clinical development of this promising compound to be used for the treatment of type 2 diabetes.