Pharmacodynamic model of sodium-glucose transporter 2 (SGLT2) inhibition: implications for quantitative translational pharmacology

Tristan S Maurer, Avijit Ghosh, Nahor Haddish-Berhane, Aarti Sawant-Basak, Carine M Boustany-Kari, Li She, Michael T Leininger, Tong Zhu, Meera Tugnait, Xin Yang, Emi Kimoto, Vincent Mascitti, Ralph P Robinson
AAPS Journal 2011, 13 (4): 576-84
Sodium-glucose co-transporter-2 (SGLT2) inhibitors are an emerging class of agents for use in the treatment of type 2 diabetes mellitus (T2DM). Inhibition of SGLT2 leads to improved glycemic control through increased urinary glucose excretion (UGE). In this study, a biologically based pharmacokinetic/pharmacodynamic (PK/PD) model of SGLT2 inhibitor-mediated UGE was developed. The derived model was used to characterize the acute PK/PD relationship of the SGLT2 inhibitor, dapagliflozin, in rats. The quantitative translational pharmacology of dapagliflozin was examined through both prospective simulation and direct modeling of mean literature data obtained for dapagliflozin in healthy subjects. Prospective simulations provided time courses of UGE that were of consistent shape to clinical observations, but were modestly biased toward under prediction. Direct modeling provided an improved characterization of the data and precise parameter estimates which were reasonably consistent with those predicted from preclinical data. Overall, these results indicate that the acute clinical pharmacology of SGLT2 inhibitors in healthy subjects can be reasonably well predicted from preclinical data through rational accounting of species differences in pharmacokinetics, physiology, and SGLT2 pharmacology. Because these data can be generated at the earliest stages of drug discovery, the proposed model is useful in the design and development of novel SGLT2 inhibitors. In addition, this model is expected to serve as a useful foundation for future efforts to understand and predict the effects of SGLT2 inhibition under chronic administration and in other patient populations.

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