An Extended Minimal Physiologically Based Pharmacokinetic Model: Evaluation of Type II Diabetes Mellitus and Diabetic Nephropathy on Human IgG Pharmacokinetics in Rats
Journal Title: The AAPS Journal - Year 2015, Vol 17, Issue 6
Abstract
Although many studies have evaluated the effects of type 2 diabetes mellitus (T2DM) on the pharmacokinetics (PK) of low molecular weight molecules, there is limited information regarding effects on monoclonal antibodies. Our previous studies have reported significant increases in total (2–4 fold) and renal (100–300 fold) clearance of human IgG, an antibody isotype, in Zucker diabetic fatty (ZDF) rats. Pioglitazone treatment incompletely reversed the disease-related PK changes. The objective of this study was to construct a mechanistic model for simultaneous fitting plasma and urine data, to yield physiologically relevant PK parameters. We propose an extended minimal physiologically based PK (mPBPK) model specifically for IgG by classifying organs as either leaky or tight vascular tissues, and adding a kidney compartment. The model incorporates convection as the primary mechanism of IgG movement from plasma into tissues, interstitial fluid (ISF) in extravascular distribution space, and glomerular filtration rate (GFR), sieving coefficient and fraction reabsorbed in the kidney. The model captured the plasma and urine PK profiles well, and simulated concentrations in ISF. The model estimated a 2–4 fold increase in nonrenal clearance from plasma and 30–120 fold increase in renal clearance with T2DM, consistent with the experimental findings, and these differences in renal clearance were related to changes in GFR, sieving coefficient, and proximal tubular reabsorption. In conclusion, the mPBPK model offers a more relevant approach for analyzing plasma and urine IgG concentration-time data than conventional models and provides insight regarding alterations in distributional and elimination parameters occurring with T2DM.
Authors and Affiliations
Gurkishan S. Chadha, Marilyn E. Morris
Keywords
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- DOI 10.1208/s12248-015-9810-0
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