E. Hoeben (1), W. De Winter (1), M. Neyens (1), A. Vermeulen (1) and D. Devineni (2)
(1) Janssen Research and Development, Model Based Drug Development, Turnhoutseweg 30, B-2340 Beerse, Belgium; (2) Janssen Research and Development, Clinical Pharmacology, 920 Route 202, Raritan, New Jersey, USA
Objectives: Canagliflozin, an orally active inhibitor of SGLT2, is currently in development for the treatment of patients with T2DM. The objective of this analysis was to develop a population pharmacokinetic (PK) model, including relevant covariates as source of inter-individual variability (IIV), with the aim to describe Phase 1, 2 and 3 PK data of canagliflozin in healthy subjects and in patients with T2DM.
Methods: Data were obtained from 1616 subjects enrolled in 9 Phase 1, 2 Phase 2 and 3 Phase 3 trials. Nonlinear mixed effects modeling of pooled data was conducted using NONMEM®[1.2]. IIV was evaluated using an exponential error model and residual error described using an additive model in the log domain. The FOCE method with interaction was applied and the model was parameterized in terms of rate constants. Covariate effects were explored graphically on empirical Bayes estimates of PK parameters, as shrinkage was low. Clinical relevance of statistically significant covariates on model parameters was evaluated. The model was evaluated internally (visual and numerical predictive check) and externally (bias and precision)[3].
Results: The population PK model was first developed using richly sampled Phase 1 data. Gender, age and WT on Vc/F, BMI on ka and BMI and over-encapsulation on Tlag were identified as the most significant covariates affecting the absorption and distribution characteristics of canagliflozin. The absorption and distribution parameters from the final Phase 1 model, including their covariate and random effects, were fixed and the model was re-run on a combined Phase 1, 2 and 3 dataset. A two-compartment PK model with lag-time and sequential zero- and first order absorption was found to provide an adequate description of the observed study data. Further covariate evaluation on ke, estimated in the final model, demonstrated that eGFR, dose and genetic polymorphism (carriers of UGT1A9*3 allele) were statistically significant. The model passed internal and external evaluation and was considered valid from an accuracy and precision point of view.
Conclusions: The developed population model successfully described the PK of canagliflozin in healthy subjects and in patients with T2DM. Although the effects of gender, age and WT on Vc/F and eGFR, dose and genetic polymorphism on ke were statistically significant, given the small magnitude of these effects, they were considered not to be of clinical relevance.
References:
[1] NONMEM 7.1.0 Users Guides (1989-2009). Beal SL, Sheiner LB, Boeckmann AJ, and Bauer RJ (eds). Icon Development Solutions, Ellicott City, MD.
[2] FDA (1999) Guidance for Industry: Population Pharmacokinetics, U.S. Food and Drug Administration, 1999.
[3] Sheiner LB, Beal SL. Some suggestions for measuring predictive performance. J Pharmacokinet Biopharm. 1981; 9:503-512.
Reference: PAGE 22 (2013) Abstr 2751 [www.page-meeting.org/?abstract=2751]
Poster: Other Drug/Disease Modelling