Pavel Balazki (1, 2), Stephan Schaller (2), Thorsten Lehr (1)
(1) Clinical Pharmacy, Saarland University, Saarbruecken, Germany, (2) esqLABS GmbH, Saterland, Germany
Objectives:
The progression of Type 2 Diabetes Mellitus (T2DM) is characterized by pathological changes in insulin secretion and clearance rates. While secretion of insulin is impaired in manifested T2DM (1), fasting plasma insulin (FPI) levels are inversely correlated with insulin resistance in the pre-diabetic state (2). Extraction of insulin is increased in hepatic and decreased in peripheral tissues (3), and the combination of alterations in insulin secretion and extraction constitute the metabolic condition of an individual. While insulin secretion rate canot be estimated from insulin concentrations alone, as hepatic extraction varies between patients, plasma concentrations of c-peptide, which is secreted equimolarly with insulin and primarily cleared in the kidneys, can be used as a marker for insulin secretion.
We developed a physiologically-based (PB) pharmacokinetics (PK) model of c-peptide and insulin for the PB-QSP Diabetes Platform that allows patient-specific characterization of insulin secretory state based on c-peptide measurements.
Methods:
The model was developed with the Open Systems Pharmacology Suite (OSPS), version 8 (4). C-peptide kinetics were fitted to PK data following i.v. infusion (5,6). The insulin receptor (IR) submodel was fitted to in vitro data (7,8). IR distribution in tissues was fitted to fractional insulin extraction and interstitial/plasma concentration ratios, and the basal insulin secretion rate was fitted with associated c-peptide concentrations (9).
Results:
C-peptide is secreted into pancreas plasma and distributed within tissues according to the standard PBPK model for proteins (10). 12% of c-peptide is extracted by the liver (11), and the remaining c-peptide is cleared in the kidney through glomerular filtration and tubular secretion. A fraction unbound of 30% was assumed to describe the distribution phase after a bolus administration. Binding of c-peptide to albumin has been recently suggested in literature (12).
Insulin is secreted with the same rate as c-peptide, filtered in the kidney, and eliminated in liver, fat, muscle, and kidney tissues by target-mediated drug-disposition after binding to the IR. The IR model captures binding of up to two insulin molecules per receptor, insulin-receptor complex internalization, and the phosphorylation of IR substrate (IRS) 1. IRS1 and IR are deactivated by the enzyme PTP1B, which is activated by IRS1. Overall, the IR model encompasses 29 states. The complex feedback loops allow to capture the observed time-courses of IR and IRS1 phosphorylation, crucial for modeling the pharmacodynamic (PD) effects of insulin.
Conclusions:
The combination of the c-peptide and insulin PBPK models allows for precise individualization of the secretory capacity based on c-peptide data, which enables capturing the various states of T2DM disease progression. The IR model mechanistically translates the plasma insulin concentrations to the anticipated PD effect, including time delays and non-linearities.
Integrated in the PB-QSP Diabetes Platform (13,14), the model will allow to create virtual populations of T2DM and pre-diabetic patients based on individual c-peptide data. The physiology database of the PBPK backbone and the information on the variability and changes in parameters of glucose regulation will enable personalized 1) prediction of disease progression, 2) treatment optimization, and 3) prediction of individual treatment outcome within a chosen population.
References:
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[14] Balazki P, Schaller S, Eissing T, Lehr T. A Quantitative Systems Pharmacology Kidney Model of Diabetes Associated Renal Hyperfiltration and the Effects of SGLT Inhibitors. CPT Pharmacomet Syst Pharmacol. 2018 Dec;7(12):788–97.
Reference: PAGE () Abstr 9514 [www.page-meeting.org/?abstract=9514]
Poster: Drug/Disease Modelling - Absorption & PBPK