Physiologically-based Pharmacokinetics/Pharmacodynamics model of Dapagliflozin, an oral SGLT2 inhibitor
Pavel Balazki (1, 2), Verena Woerle (3), Stephan Schaller (4), Thomas Eissing(2), Thorsten Lehr (1)
(1) Clinical Pharmacy, Saarland University, Saarbruecken, Germany, (2) Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany, (3) Integrated Life Science, Friedrich-Alexander University, Erlangen, Germany, (4) esqlabs GmbH, Germany
Objectives: Physiologically-based (PB) systems pharmacology models of glucose homeostasis allow insight into diseases such as type 2 diabetes mellitus (T2DM). Combined with PB pharmacokinetics (PBPK) models of anti-diabetic drugs, they allow hypothesis testing, treatment personalization, or disease-progression studies. Our objectives are: 1) to develop a PBPK model of dapagliflozin, first approved inhibitor of SGTL2 glucose transporter and 2) to couple the PBPK model with a model of glucose homeostasis based on [1] to predict the observed pharmacodynamic (PD) effects.
Methods: PK and physico-chemical parameters of dapagliflozin as well as mean concentration-time profiles were extracted from literature for model development and validation. The data include concentration profiles gathered in a 80 µg intravenous (iv) micro-tracer [2], oral single ascending dose (SAD) (range 2.5 – 500 mg) [3, 4], or multiple ascending dose (MAD) (14 days once daily, range 2.5 – 100 mg) [3] studies.
The PBPK model was developed with PK-Sim® and MoBi® as part of the Open Systems Pharmacology Suite (OSPS), version 7.0 [5], and coupled with a glucose-insulin homeostasis model based on [1]. The PD effect on urinary glucose excretion was evaluated by simulating the stepped hyperglycemic clamp with a single 10 mg dapagliflozin dose reported in [6].
Results: Model development and parameter identification were performed with the iv and 2.5, 5, and 50 mg SAD datasets. The final model includes metabolization of dapagliflozin by the enzymes CYP3A4 and UGT1A9. The drug is filtrated in the glomeruli and reabsorbed in the proximal tubuli of the kidney. Distribution in tissues is calculated by the OSPS software including P-gp transport as an active process. Along with the four datasets used for development, the model is able to reproduce observed dapagliflozin data from the 12 remaining datasets with maximal 20% AUC deviation.
Inhibition of SGLT2 is modeled as reversible binding of dapagliflozin to the transporter. With in vitro values for K_d = 6 nM and k_off = 0.12 1/min [6], the model successfully predicted increased urinary glucose excretion observed over a wide range of plasma glucose concentrations (5.5-30.5 mM).
Conclusions: The developed model incorporates all relevant processes involved in PK of dapagliflozin. Its mechanistic coupling with the glucose homeostasis model extends the area of application of the latter towards personalized treatment or treatment combination exploration.
References:
[1] Schaller, S., et al. "A generic integrated physiologically based whole-body model of the glucose-insulin-glucagon regulatory system." CPT: pharmacometrics & systems pharmacology 2.8 (2013): 1-10.
[2] Boulton, David W., et al. "Simultaneous oral therapeutic and intravenous 14C-microdoses to determine the absolute oral bioavailability of saxagliptin and dapagliflozin." British Journal of Clinical Pharmacology 75.3 (2013): 763-768.
[3] Komoroski, B., et al. "Dapagliflozin, a novel SGLT2 inhibitor, induces dose-dependent glucosuria in healthy subjects." Clinical Pharmacology & Therapeutics 85.5 (2009): 520-526.
[4] Kasichayanula, S., et al. "Influence of hepatic impairment on the pharmacokinetics and safety profile of dapagliflozin: an open-label, parallel-group, single-dose study." Clinical Therapeutics 33.11 (2011): 1798-1808.
[5] www.open-systems-pharmacology.com
[6] DeFronzo, Ralph A., et al. "Characterization of renal glucose reabsorption in response to dapagliflozin in healthy subjects and subjects with type 2 diabetes." Diabetes Care 36.10 (2013): 3169-3176.
[7] Hummel, Charles S., et al. "Structural selectivity of human SGLT inhibitors." American Journal of Physiology-Cell Physiology 302.2 (2012): C373-C382.
