Rosa Chan1, Tom De Bruyn2, Matthew Wright2, Fabio Broccatelli3. 1. Department of Bioengineering and Therapeutic Sciences, School of Pharmacy and Medicine, University of California San Francisco, San Francisco, California, USA. 2. Drug Metabolism & Pharmacokinetics Genentech, Inc, 1 DNA Way, South San Francisco, California, 94080-4990, USA. 3. Drug Metabolism & Pharmacokinetics Genentech, Inc, 1 DNA Way, South San Francisco, California, 94080-4990, USA. broccatelli@gene.com.
Abstract
PURPOSE: Volume of distribution at steady state (Vdss) is a fundamental pharmacokinetic (PK) parameter driven predominantly by passive processes and physicochemical properties of the compound. Human Vdss can be estimated using in silico mechanistic methods or empirically scaled from Vdss values obtained from preclinical species. In this study the accuracy and the complementarity of these two approaches are analyzed leveraging a large data set (over 150 marketed drugs). METHODS: For all the drugs analyzed in this study experimental in vitro measurements of LogP, plasma protein binding and pKa are used as input for the mechanistic in silico model to predict human Vdss. The software used for predicting human tissue partition coefficients and Vdss based on the method described by Rodgers and Rowland is made available as supporting information. RESULTS: This assessment indicates that overall the in silico mechanistic model presented by Rodgers and Rowland is comparably accurate or superior to empirical approaches based on the extrapolation of in vivo data from preclinical species. CONCLUSIONS: These results illustrate the great potential of mechanistic in silico models to accurately predict Vdss in humans. This in silico method does not rely on in vivo data and is, consequently, significantly time and resource sparing. The success of this in silico model further suggests that reasonable predictability of Vdss in preclinical species could be obtained by a similar process.
PURPOSE: Volume of distribution at steady state (Vdss) is a fundamental pharmacokinetic (PK) parameter driven predominantly by passive processes and physicochemical properties of the compound. Human Vdss can be estimated using in silico mechanistic methods or empirically scaled from Vdss values obtained from preclinical species. In this study the accuracy and the complementarity of these two approaches are analyzed leveraging a large data set (over 150 marketed drugs). METHODS: For all the drugs analyzed in this study experimental in vitro measurements of LogP, plasma protein binding and pKa are used as input for the mechanistic in silico model to predict human Vdss. The software used for predicting human tissue partition coefficients and Vdss based on the method described by Rodgers and Rowland is made available as supporting information. RESULTS: This assessment indicates that overall the in silico mechanistic model presented by Rodgers and Rowland is comparably accurate or superior to empirical approaches based on the extrapolation of in vivo data from preclinical species. CONCLUSIONS: These results illustrate the great potential of mechanistic in silico models to accurately predict Vdss in humans. This in silico method does not rely on in vivo data and is, consequently, significantly time and resource sparing. The success of this in silico model further suggests that reasonable predictability of Vdss in preclinical species could be obtained by a similar process.
Entities:
Keywords:
PBPK; mechanistic in silico model; physicochemical properties; preclinical; volume of distribution (Vdss)
Authors: David S Wishart; Craig Knox; An Chi Guo; Savita Shrivastava; Murtaza Hassanali; Paul Stothard; Zhan Chang; Jennifer Woolsey Journal: Nucleic Acids Res Date: 2006-01-01 Impact factor: 16.971
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