Ken Korzekwa1, Swati Nagar2. 1. Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N Broad Street, Philadelphia, Pennsylvania, 19140, USA. 2. Department of Pharmaceutical Sciences, Temple University School of Pharmacy, 3307 N Broad Street, Philadelphia, Pennsylvania, 19140, USA. swati.nagar@temple.edu.
Abstract
PURPOSE: Volume of distribution is an important pharmacokinetic parameter in the distribution and half-life of a drug. Protein binding and lipid partitioning together determine drug distribution. METHODS: Here we present a simple relationship that estimates the volume of distribution with the fraction of drug unbound in both plasma and microsomes. Model equations are based upon a two-compartment system and the experimental fractions unbound in plasma and microsomes represent binding to plasma proteins and cellular lipids, respectively. RESULTS: The protein and lipid binding components were parameterized using a dataset containing human in vitro and in vivo parameters for 63 drugs. The resulting equation explains ~84% of the variance in the log of the volume of distribution with an average fold-error of 1.6, with 3 outliers. CONCLUSIONS: These results suggest that Vss can be predicted for most drugs from plasma protein binding and microsomal partitioning.
PURPOSE: Volume of distribution is an important pharmacokinetic parameter in the distribution and half-life of a drug. Protein binding and lipid partitioning together determine drug distribution. METHODS: Here we present a simple relationship that estimates the volume of distribution with the fraction of drug unbound in both plasma and microsomes. Model equations are based upon a two-compartment system and the experimental fractions unbound in plasma and microsomes represent binding to plasma proteins and cellular lipids, respectively. RESULTS: The protein and lipid binding components were parameterized using a dataset containing human in vitro and in vivo parameters for 63 drugs. The resulting equation explains ~84% of the variance in the log of the volume of distribution with an average fold-error of 1.6, with 3 outliers. CONCLUSIONS: These results suggest that Vss can be predicted for most drugs from plasma protein binding and microsomal partitioning.
Entities:
Keywords:
microsomal partitioning; volume of distribution
Authors: Rupert P Austin; Patrick Barton; Scott L Cockroft; Mark C Wenlock; Robert J Riley Journal: Drug Metab Dispos Date: 2002-12 Impact factor: 3.922
Authors: Stefan S De Buck; Vikash K Sinha; Luca A Fenu; Ron A Gilissen; Claire E Mackie; Marjoleen J Nijsen Journal: Drug Metab Dispos Date: 2007-01-31 Impact factor: 3.922
Authors: Eduarda Fernandes; Sofia Benfeito; Fernando Cagide; Hugo Gonçalves; Sigrid Bernstorff; Jana B Nieder; M Elisabete Cd Real Oliveira; Fernanda Borges; Marlene Lúcio Journal: Nanotechnol Sci Appl Date: 2021-02-09
Authors: Neha Murad; Kishore K Pasikanti; Benjamin D Madej; Amanda Minnich; Juliet M McComas; Sabrinia Crouch; Joseph W Polli; Andrew D Weber Journal: Drug Metab Dispos Date: 2020-11-25 Impact factor: 3.922