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Updated: Mar 30, 2026

Author Spotlight: Developing a Simple and Robust Hepatic Model for Pharmacological and Toxicological Applications
Published on: October 20, 2023
Predicting the effect of hepatic disease on systemic drug exposure
Patrick J McNamara1, Joseph Fleishaker2, Darius Meiman3
1Department of Pharmaceutical Sciences College of Pharmacy University of Kentucky, 789 S. Limestone, 361 Lexington, KY 40536-0596, USA.
None:
The purpose of this study was to employ a comprehensive Top-Down scaling approach to estimate the impact of alterations in bioavailability (gut wall (FG) and hepatic first pass (FH,)) and clearance pathways (renal (ClR) and hepatic (ClH)) on the relative changes to drug exposure (AUCR, area under the curve ratio in liver disease compared to otherwise healthy patients). Observations evaluating drug clearance as a function of Child-Pugh (C-P) categories (mild, moderate, and severe) for hepatically cleared drugs (fe <0.3) were obtained from literature sources. The analysis consisted of 319 AUCR observations across 127 unique drugs. Top-down analysis was used to account for changes in FG, FH, ClR, and ClH using information regarding specific CYP pathways (fm) and available pharmacokinetic parameters, as well as additional scaling approaches for renal function, CYP activity, shunting, and other factors. In several data cuts, the Top-Down scaling approach provided reasonable estimates of the effect of liver disease. Analysis of a dataset of 77 data points (48 drugs) with observed AUCR values exceeding 2 in patients with severe liver disease, revealed that these drugs were predominantly CYP3А4 substrates. Studies with complete data sets for multiple C-P categories provided greater insights into drug risk in liver disease, especially for identifying drugs with AUCR>2 in severe liver disease. The Top-Down scaling approach was comparable to bottom-up methods (PBPK) in predicting the relative changes to drug exposure (AUCR) for various degrees of liver disease based on C-P categories. Furthermore, this approach was able to highlight the key criteria for drugs with the highest risk of increased exposure (AUCR>2) in liver disease. These drugs are primarily eliminated via hepatic metabolism (fe < 0.5), and their clearance pathways include either one (or a combination) of CYP1A2, CYP2C19, CYP2D6, and CYP3A4. Oral administration significantly increases the risk of increased exposures, particularly those with substantial hepatic and gut wall first-pass (FH and FG) metabolism.
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