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Current Drug Metabolism

Editor-in-Chief

ISSN (Print): 1389-2002
ISSN (Online): 1875-5453

Opinion Article

Evaluating Lean Liver Volume as a Potential Scaler for In Vitro-In Vivo Extrapolation of Drug Clearance in Obesity Using the Model Drug Antipyrine

Author(s): Jaydeep Sinha*, Stephen B. Duffull, Bruce Green and Hesham S. Al-Sallami

Volume 21, Issue 10, 2020

Page: [746 - 750] Pages: 5

DOI: 10.2174/1389200221666200515105800

Price: $65

Abstract

Background: In vitro-in vivo extrapolation (IVIVE) of hepatic drug clearance (CL) involves the scaling of hepatic intrinsic clearance (CLint,uH) by functional liver size, which is approximated by total liver volume (LV) as per the convention. However, in most overweight and obese patients, LV includes abnormal liver fat, which is not thought to contribute to drug elimination, thus overestimating drug CL. Therefore, lean liver volume (LLV) might be a more appropriate scaler of CLint,uH.

Objective: The objective of this work was to assess the application of LLV in CL extrapolation in overweight and obese patients (BMI >25 kg/m2) using a model drug antipyrine.

Methods: Recently, a model to predict LLV from patient sex, weight, and height was developed and evaluated. In order to assess the LLV model’s use in IVIVE, a correlation-based analysis was conducted using antipyrine as an example drug.

Results: In the overweight group (BMI >25 kg/m2), LLV could describe 36% of the variation in antipyrine CL (R2 = 0.36), which was >2-fold higher than that was explained by LV (R2 = 0.17). In the normal-weight group (BMI ≤25 kg/m2), the coefficients of determination were 58% (R2 = 0.58) and 43% (R2= 0.43) for LLV and LV, respectively.

Conclusion: The analysis indicates that LLV is potentially a more appropriate descriptor of functional liver size than LV, particularly in overweight individuals. Therefore, LLV has a potential application in IVIVE of CL in obesity.

Keywords: IVIVE, NAFLD, NASH, PBPK, FFM, drug development, obesity, lean liver volume, functional liver volume.

Graphical Abstract

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