Literature DB >> 34168949

Methods to Predict Volume of Distribution.

Kimberly Holt1, Swati Nagar1, Ken Korzekwa1.   

Abstract

PURPOSE OF REVIEW: Prior to human studies, knowledge of drug disposition in the body is useful to inform decisions on drug safety and efficacy, first in human dosing, and dosing regimen design. It is therefore of interest to develop predictive models for primary pharmacokinetic parameters, clearance, and volume of distribution. The volume of distribution of a drug is determined by the physiological properties of the body and physiochemical properties of the drug, and is used to determine secondary parameters, including the half-life. The purpose of this review is to provide an overview of current methods for the prediction of volume of distribution of drugs, discuss a comparison between the methods, and identify deficiencies in current predictive methods for future improvement. RECENT
FINDINGS: Several volumes of distribution prediction methods are discussed, including preclinical extrapolation, physiological methods, tissue composition-based models to predict tissue:plasma partition coefficients, and quantitative structure-activity relationships. Key factors that impact the prediction of volume of distribution, such as permeability, transport, and accuracy of experimental inputs, are discussed. A comparison of current methods indicates that in general, all methods predict drug volume of distribution with an absolute average fold error of 2-fold. Currently, the use of composition-based PBPK models is preferred to models requiring in vivo input.
SUMMARY: Composition-based models perfusion-limited PBPK models are commonly used at present for prediction of tissue:plasma partition coefficients and volume of distribution, respectively. A better mechanistic understanding of important drug distribution processes will result in improvements in all modeling approaches.

Entities:  

Keywords:  Distribution; Membranepartitioning; Predictionmodels; Tissue:plasmapartitioncoefficients; Volumeofdistribution

Year:  2019        PMID: 34168949      PMCID: PMC8221585          DOI: 10.1007/s40495-019-00186-5

Source DB:  PubMed          Journal:  Curr Pharmacol Rep        ISSN: 2198-641X


  49 in total

1.  Prediction of pharmacokinetics prior to in vivo studies. 1. Mechanism-based prediction of volume of distribution.

Authors:  Patrick Poulin; Frank-Peter Theil
Journal:  J Pharm Sci       Date:  2002-01       Impact factor: 3.534

2.  Commentary: a physiological approach to hepatic drug clearance.

Authors:  G R Wilkinson; D G Shand
Journal:  Clin Pharmacol Ther       Date:  1975-10       Impact factor: 6.875

3.  Quantitative structure-pharmacokinetic relationship modelling: apparent volume of distribution.

Authors:  Taravat Ghafourian; Mohammad Barzegar-Jalali; Nasim Hakimiha; Mark T D Cronin
Journal:  J Pharm Pharmacol       Date:  2004-03       Impact factor: 3.765

Review 4.  Prediction of volume of distribution at steady state in humans: comparison of different approaches.

Authors:  Peng Zou; Nan Zheng; Yongsheng Yang; Lawrence X Yu; Duxin Sun
Journal:  Expert Opin Drug Metab Toxicol       Date:  2012-05-17       Impact factor: 4.481

5.  Prediction of drug tissue to plasma concentration ratios using a measured volume of distribution in combination with lipophilicity.

Authors:  Rasmus Jansson; Ulf Bredberg; Michael Ashton
Journal:  J Pharm Sci       Date:  2008-06       Impact factor: 3.534

6.  Correlation-based prediction of tissue-to-plasma partition coefficients using readily available input parameters.

Authors:  Y E Yun; A N Edginton
Journal:  Xenobiotica       Date:  2013-02-19       Impact factor: 1.908

Review 7.  Organic anion transporting polypeptide (OATP)1B1 and OATP1B3 as important regulators of the pharmacokinetics of substrate drugs.

Authors:  Kazuya Maeda
Journal:  Biol Pharm Bull       Date:  2015       Impact factor: 2.233

Review 8.  Industry Perspective on Contemporary Protein-Binding Methodologies: Considerations for Regulatory Drug-Drug Interaction and Related Guidelines on Highly Bound Drugs.

Authors:  Li Di; Christopher Breen; Rob Chambers; Sean T Eckley; Robert Fricke; Avijit Ghosh; Paul Harradine; J Cory Kalvass; Stacy Ho; Caroline A Lee; Punit Marathe; Everett J Perkins; Mark Qian; Susanna Tse; Zhengyin Yan; Maciej J Zamek-Gliszczynski
Journal:  J Pharm Sci       Date:  2017-09-18       Impact factor: 3.534

9.  Prediction of drug distribution in distribution dialysis and in vivo from binding to tissues and blood.

Authors:  J Clausen; M H Bickel
Journal:  J Pharm Sci       Date:  1993-04       Impact factor: 3.534

Review 10.  On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical?

Authors:  Ken Korzekwa; Swati Nagar
Journal:  Pharm Res       Date:  2016-12-27       Impact factor: 4.200

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  1 in total

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Authors:  Daniel Gomez; Diego Mengual Gómez; Romina Armando; Maia Cabrera; Roman Vilarullo; Patricio Chinestrad; Julian Maggio; Camila Paderta; Pablo Lorenzano Menna
Journal:  Oncol Rep       Date:  2022-09-14       Impact factor: 4.136

  1 in total

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