Literature DB >> 19455625

Development of a novel method for predicting human volume of distribution at steady-state of basic drugs and comparative assessment with existing methods.

Patrick Poulin1, Frank-Peter Theil.   

Abstract

The parameters characterizing tissue distribution refer to the tissue/plasma partition coefficients (Kp), which can be used to derive volume of distribution at steady-state (V(ss)). The effort for predicting drug distribution in human has been further expanded to calculation methods using in vitro-based algorithms. The objective of the present study was to develop a novel prediction method to estimate human V(ss) for moderate-to-strong bases. The predictive performance of the novel method was compared with other well established in vitro-based methods available in the literature. Relevant information collected from previous prediction studies of V(ss) facilitated the development of the novel method. This was based on the calculation of V(ss) from data on Kp, which were estimated by correlating the unbound tissue/plasma ratio in vivo (Kpu) with the unbound red blood cells partitioning (RBCu) determined in vitro. The comparative assessment of the novel correlation method with existing prediction methods of human V(ss) was done using a literature dataset of 61 basic drugs (at least one pK(a) > or = 7). The five existing V(ss) prediction methods published in the literature are comprised of four versions of tissue composition-based models along with the model of Lombardo using the principle of Oie-Tozer. The statistical analysis of the prediction performance indicated that the novel method demonstrated a greater degree of accuracy compared to all other published methods. The maximum percentage of predicted values that fall within a twofold-error range is 77% for the basic drugs tested. Overall, the present study describes the development and the assessment of the predictive performance of the novel prediction method of human V(ss) based upon in vitro data, which appears to be superior based on the current dataset studied for basic drugs. 2009 Wiley-Liss, Inc. and the American Pharmacists Association

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 19455625     DOI: 10.1002/jps.21759

Source DB:  PubMed          Journal:  J Pharm Sci        ISSN: 0022-3549            Impact factor:   3.534


  25 in total

1.  Lumping of physiologically-based pharmacokinetic models and a mechanistic derivation of classical compartmental models.

Authors:  Sabine Pilari; Wilhelm Huisinga
Journal:  J Pharmacokinet Pharmacodyn       Date:  2010-07-27       Impact factor: 2.745

2.  Development of a decision tree to classify the most accurate tissue-specific tissue to plasma partition coefficient algorithm for a given compound.

Authors:  Yejin Esther Yun; Cecilia A Cotton; Andrea N Edginton
Journal:  J Pharmacokinet Pharmacodyn       Date:  2013-11-21       Impact factor: 2.745

3.  Prediction of Tissue-to-Plasma Ratios of Basic Compounds in Mice.

Authors:  Prashant B Nigade; Jayasagar Gundu; K Sreedhara Pai; Kumar V S Nemmani
Journal:  Eur J Drug Metab Pharmacokinet       Date:  2017-10       Impact factor: 2.441

4.  A single-species approach considering additional physiological information for prediction of hepatic clearance of glycoprotein derivate therapeutics.

Authors:  Patrick Poulin
Journal:  Clin Pharmacokinet       Date:  2011-10       Impact factor: 6.447

5.  Interethnic scaling of fraction unbound of a drug in plasma and volume of distribution: an analysis of extrapolation from Caucasians to Chinese.

Authors:  Guo Yu; Hong-Hao Zhou; Qing-Shan Zheng; Guo-Fu Li
Journal:  Eur J Clin Pharmacol       Date:  2018-12-19       Impact factor: 2.953

Review 6.  Dose selection based on physiologically based pharmacokinetic (PBPK) approaches.

Authors:  Hannah M Jones; Kapil Mayawala; Patrick Poulin
Journal:  AAPS J       Date:  2012-12-27       Impact factor: 4.009

7.  Whole body physiologically based modelling of β-blockers in the rat: events in tissues and plasma following an i.v. bolus dose.

Authors:  S Y A Cheung; T Rodgers; L Aarons; I Gueorguieva; G L Dickinson; S Murby; C Brown; B Collins; M Rowland
Journal:  Br J Pharmacol       Date:  2017-12-01       Impact factor: 8.739

8.  Evaluating In Vitro-In Vivo Extrapolation of Toxicokinetics.

Authors:  John F Wambaugh; Michael F Hughes; Caroline L Ring; Denise K MacMillan; Jermaine Ford; Timothy R Fennell; Sherry R Black; Rodney W Snyder; Nisha S Sipes; Barbara A Wetmore; Joost Westerhout; R Woodrow Setzer; Robert G Pearce; Jane Ellen Simmons; Russell S Thomas
Journal:  Toxicol Sci       Date:  2018-05-01       Impact factor: 4.849

9.  Global Sensitivity Analysis of the Rodgers and Rowland Model for Prediction of Tissue: Plasma Partitioning Coefficients: Assessment of the Key Physiological and Physicochemical Factors That Determine Small-Molecule Tissue Distribution.

Authors:  Estelle Yau; Andrés Olivares-Morales; Michael Gertz; Neil Parrott; Adam S Darwich; Leon Aarons; Kayode Ogungbenro
Journal:  AAPS J       Date:  2020-02-03       Impact factor: 4.009

10.  Drug Distribution Part 2. Predicting Volume of Distribution from Plasma Protein Binding and Membrane Partitioning.

Authors:  Ken Korzekwa; Swati Nagar
Journal:  Pharm Res       Date:  2016-12-13       Impact factor: 4.200

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.