Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions
- PMID: 16639716
- DOI: 10.1002/jps.20502
Physiologically based pharmacokinetic modelling 2: predicting the tissue distribution of acids, very weak bases, neutrals and zwitterions
Erratum in
- J Pharm Sci. 2007 Nov;96(11):3153-4
Abstract
A key component of whole body physiologically based pharmacokinetic (WBPBPK) models is the tissue-to-plasma water partition coefficients (Kpu's). The predictability of Kpu values using mechanistically derived equations has been investigated for 7 very weak bases, 20 acids, 4 neutral drugs and 8 zwitterions in rat adipose, bone, brain, gut, heart, kidney, liver, lung, muscle, pancreas, skin, spleen and thymus. These equations incorporate expressions for dissolution in tissue water and, partitioning into neutral lipids and neutral phospholipids. Additionally, associations with acidic phospholipids were incorporated for zwitterions with a highly basic functionality, or extracellular proteins for the other compound classes. The affinity for these cellular constituents was determined from blood cell data or plasma protein binding, respectively. These equations assume drugs are passively distributed and that processes are nonsaturating. Resultant Kpu predictions were more accurate when compared to published equations, with 84% as opposed to 61% of the predicted values agreeing with experimental values to within a factor of 3. This improvement was largely due to the incorporation of distribution processes related to drug ionisation, an issue that is not addressed in earlier equations. Such advancements in parameter prediction will assist WBPBPK modelling, where time, cost and labour requirements greatly deter its application.
(c) 2006 Wiley-Liss, Inc. and the American Pharmacists Association
Similar articles
-
Physiologically based pharmacokinetic modeling 1: predicting the tissue distribution of moderate-to-strong bases.J Pharm Sci. 2005 Jun;94(6):1259-76. doi: 10.1002/jps.20322. J Pharm Sci. 2005. PMID: 15858854
-
A priori prediction of tissue:plasma partition coefficients of drugs to facilitate the use of physiologically-based pharmacokinetic models in drug discovery.J Pharm Sci. 2000 Jan;89(1):16-35. doi: 10.1002/(SICI)1520-6017(200001)89:1<16::AID-JPS3>3.0.CO;2-E. J Pharm Sci. 2000. PMID: 10664535
-
Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.Eur J Pharm Sci. 2017 Nov 15;109:419-430. doi: 10.1016/j.ejps.2017.08.014. Epub 2017 Aug 18. Eur J Pharm Sci. 2017. PMID: 28823852
-
On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical?Pharm Res. 2017 Mar;34(3):529-534. doi: 10.1007/s11095-016-2089-8. Epub 2016 Dec 27. Pharm Res. 2017. PMID: 28028770 Free PMC article. Review.
-
Prediction of the volume of distribution of a drug: which tissue-plasma partition coefficients are needed?J Pharm Pharmacol. 2002 Sep;54(9):1237-45. doi: 10.1211/002235702320402080. J Pharm Pharmacol. 2002. PMID: 12356278 Review.
Cited by
-
Assessment of DCE-MRI parameters for brain tumors through implementation of physiologically-based pharmacokinetic model approaches for Gd-DOTA.J Pharmacokinet Pharmacodyn. 2016 Oct;43(5):529-47. doi: 10.1007/s10928-016-9493-x. Epub 2016 Sep 19. J Pharmacokinet Pharmacodyn. 2016. PMID: 27647272
-
Muscle to Brain Partitioning as Measure of Transporter-Mediated Efflux at the Rat Blood-Brain Barrier and Its Implementation into Compound Optimization in Drug Discovery.Pharmaceutics. 2019 Nov 11;11(11):595. doi: 10.3390/pharmaceutics11110595. Pharmaceutics. 2019. PMID: 31718023 Free PMC article.
-
Preterm Physiologically Based Pharmacokinetic Model. Part II: Applications of the Model to Predict Drug Pharmacokinetics in the Preterm Population.Clin Pharmacokinet. 2020 Apr;59(4):501-518. doi: 10.1007/s40262-019-00827-4. Clin Pharmacokinet. 2020. PMID: 31587145 Clinical Trial.
-
Physiologically Based Pharmacokinetic (PBPK) Modeling of Clopidogrel and Its Four Relevant Metabolites for CYP2B6, CYP2C8, CYP2C19, and CYP3A4 Drug-Drug-Gene Interaction Predictions.Pharmaceutics. 2022 Apr 22;14(5):915. doi: 10.3390/pharmaceutics14050915. Pharmaceutics. 2022. PMID: 35631502 Free PMC article.
-
Using partition analysis as a facile method to derive net clearances.Clin Transl Sci. 2022 Aug;15(8):1867-1879. doi: 10.1111/cts.13310. Epub 2022 Jun 2. Clin Transl Sci. 2022. PMID: 35579201 Free PMC article.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources