Literature DB >> 17883888

Prediction of human pharmacokinetics--evaluation of methods for prediction of volume of distribution.

Urban Fagerholm1.   

Abstract

The aim was to evaluate and review methods for prediction of the steady-state volume of distribution (V(D,ss)) of xenobiotics in man. For allometry, approximately 30-40% of predictions are classified as incorrect, humans and animals belong to different V(D,ss) categories for approximately 30% of the compounds, maximum prediction errors are large (>10-fold), the b-exponent ranges between -0.2 and 2.2 (averaging approximately 0.8-0.9), and >2-fold prediction errors are found for 35% of the substances. The performance is consistent with species differences of binding in and outside the vasculature. The largest errors could potentially lead to very poor prediction of exposure profile and failure in clinical studies. A re-evaluation of allometric scaling of unbound tissue volume of distribution demonstrates that this method is less accurate (27% of predictions >2-fold errors) than a previous evaluation demonstrated. By adding molecular descriptor information, predictions based on animal V(D,ss) data can be improved. Improved predictions (approximately 1/10 of allometric errors) can also be obtained by using the relationship between unbound fraction in plasma (f(u,pl)) and V(D,ss) for each substance (method suggested by the author). A physiologically-based 4-compartment model (plasma, red blood cells, interstitial fluid and cell volume) together with measured tissue-plasma partitioning coefficients in rats, f(u,pl), interstitial-plasma concentration ratio of albumin, organ weight and blood flow data has been successfully applied. Prediction errors for one basic and one neutral drug are only 3-5%. The data obtained with this comparably laboratory-intensive method are limited to these two compounds. A similar approach where predicted tissue partitioning is used, and a computational model, give prediction errors similar to that of allometry. Advantages with these are the suitability for screening and avoidance of animal experiments. The evaluated methods do not account for potential active transport and slow dissociation rates.

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Year:  2007        PMID: 17883888     DOI: 10.1211/jpp.59.9.0001

Source DB:  PubMed          Journal:  J Pharm Pharmacol        ISSN: 0022-3573            Impact factor:   3.765


  6 in total

Review 1.  Applications of human pharmacokinetic prediction in first-in-human dose estimation.

Authors:  Peng Zou; Yanke Yu; Nan Zheng; Yongsheng Yang; Hayley J Paholak; Lawrence X Yu; Duxin Sun
Journal:  AAPS J       Date:  2012-03-10       Impact factor: 4.009

Review 2.  Prediction of drug disposition on the basis of its chemical structure.

Authors:  David Stepensky
Journal:  Clin Pharmacokinet       Date:  2013-06       Impact factor: 6.447

3.  In silico analysis for factors affecting anti-malarial penetration into red blood cells.

Authors:  Natapol Pornputtapong; Bovornpat Suriyapakorn; Anchisa Satayamapakorn; Kanidsorn Larpadisorn; Pariyachut Janviriyakul; Phisit Khemawoot
Journal:  Malar J       Date:  2020-06-23       Impact factor: 2.979

4.  PKQuest_Java: free, interactive physiologically based pharmacokinetic software package and tutorial.

Authors:  David G Levitt
Journal:  BMC Res Notes       Date:  2009-08-05

5.  Quantifying and Communicating Uncertainty in Preclinical Human Dose-Prediction.

Authors:  M Sundqvist; A Lundahl; M B Någård; U Bredberg; P Gennemark
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2015-04-16

6.  Predicting blood-to-plasma concentration ratios of drugs from chemical structures and volumes of distribution in humans.

Authors:  Hideaki Mamada; Kazuhiko Iwamoto; Yukihiro Nomura; Yoshihiro Uesawa
Journal:  Mol Divers       Date:  2021-02-10       Impact factor: 3.364

  6 in total

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