Pavel Balazki (1, 2), Stephan Schaller (2), Thorsten Lehr (1)
(1) Clinical Pharmacy, Saarland University, Saarbruecken, Germany, (2) esqLABS GmbH, Saterland, Germany
Objectives:
Type 2 Diabetes Mellitus (T2DM) is a complex disease that results in the dysregulation of glucose control and elevated glucose levels. The manifestation of T2DM is a long-term process, and different therapies may be required depending on the state of disease progression. The three most common pharmacological therapies are metformin, dipeptidyl peptidase 4 (DPP4) inhibitors, and sodium–glucose cotransporter 2 (SGLT2) inhibitors [1].
The aim of this work is to develop a physiologically-based (PB) Quantitative Systems Pharmacology (QSP) model of glucose regulation in healthy individuals and T2DM patients for the prediction of metformin, DPP4 inhibitor (DPP4i), and SGLT2 inhibitor (SGLT2i) treatment outcomes with HbA1c as biomarker.
Methods:
The model was developed with the Open Systems Pharmacology Suite (OSPS), version 9 [2]. A previously published model of glucose homeostasis in healthy individuals [3] was coupled with PBPK and pharmacodynamic (PD) models of the SGLT2i dapagliflozin [4], the DPP4i sitagliptin [5], and a PBPK model of metformin [6]. The latter was extended by the PD effects of metformin, considering both, increase in overall glucose metabolization and improvement of insulin sensitivity. Furthermore, a mechanistic model of hemoglobin glycation to describe HbA1c levels was developed and integrated into the PBPK-QSP model. The differences between healthy and T2DM populations were described using data on incretin secretion, insulin response, and oral glucose tolerance tests (OGTT) [7]–[12]. The HbA1c model has been fitted to 5.6%, a value typical for healthy individuals.
Results:
The developed platform integrates PBPK models of glucose, insulin, glucagon, GLP-1 and its metabolites, GIP and its metabolite, and the feedback loops on their endogenous production and metabolization processes.
The model accurately describes glucose homeostasis in healthy and T2DM populations, capturing observed glucose concentrations after intravenous perturbation experiments, as well as oral glucose administrations as liquid solution (OGTT) or as a part of ingested meals. Different stages of T2DM progression were described by individualizing physiological and effect-related parameters.
The treatment effect of SGLT2i was validated with urinary glucose excretion data in healthy and T2DM [13], the effect DPP4i with percentage inhibition of plasma DPP4. Metformin PD were validated with the observed percentage changes in glucose production rates and fasting plasma glucose in healthy individuals and T2DM patients [14] and with published OGTT data [15]. The predicted HbA1c levels were in line with the values observed in T2DM, including the effects of pharmacological therapies.
Conclusions:
We present an integrative PBPK -QSP model for predictions of T2DM treatment combinations with the most commonly used therapies. The model provides a platform for evaluation of efficacy of new anti-diabetic drugs and optimization of treatment combinations with HbA1c as a long-term marker.
References:
[1] American Diabetes Association Professional Practice Committee, “9. Pharmacologic Approaches to Glycemic Treatment: Standards of Medical Care in Diabetes—2022,” Diabetes Care, vol. 45, no. Supplement_1, pp. S125–S143, Jan. 2022, doi: 10.2337/dc22-S009.
[2] Open Systems Pharmacology Suite. [Online]. Available: www.open-systems-pharmacology.org
[3] Balazki, P., Eissing, T., and Lehr, T., “Physiologically-based pharmacokinetics/pharmacodynamics (PBPK/PD) systems pharmacology model of glucose homeostasis in human,” presented at the DPhG annual meeting, Sep. 2017.
[4] P. Balazki, S. Schaller, T. Eissing, and T. Lehr, “A Quantitative Systems Pharmacology Kidney Model of Diabetes Associated Renal Hyperfiltration and the Effects of SGLT Inhibitors,” CPT Pharmacomet. Syst. Pharmacol., vol. 7, no. 12, pp. 788–797, Dec. 2018, doi: 10.1002/psp4.12359.
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[13] R. A. Defronzo et al., “Characterization of renal glucose reabsorption in response to dapagliflozin in healthy subjects and subjects with type 2 diabetes,” Diabetes Care, vol. 36, no. 10, pp. 3169–3176, 2013, doi: 10.2337/dc13-0387.
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Reference: PAGE 30 (2022) Abstr 10063 [www.page-meeting.org/?abstract=10063]
Poster: Drug/Disease Modelling - Absorption & PBPK