Cargando…

Predicting human pharmacokinetics from preclinical data: volume of distribution

This tutorial introduces background and methods to predict the human volume of distribution (V(d)) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: V(d) = V(p) + ∑(T)(V(T) × k(tp)). In this equation, V(p...

Descripción completa

Detalles Bibliográficos
Autores principales: Yim, Dong-Seok, Choi, Suein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Clinical Pharmacology and Therapeutics 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781809/
https://www.ncbi.nlm.nih.gov/pubmed/33425799
http://dx.doi.org/10.12793/tcp.2020.28.e19
_version_ 1783631753769910272
author Yim, Dong-Seok
Choi, Suein
author_facet Yim, Dong-Seok
Choi, Suein
author_sort Yim, Dong-Seok
collection PubMed
description This tutorial introduces background and methods to predict the human volume of distribution (V(d)) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: V(d) = V(p) + ∑(T)(V(T) × k(tp)). In this equation, V(p) (plasma volume) and V(T) (tissue volume) are known physiological values, and k(tp) (tissue plasma partition coefficient) is experimentally measured. Here, the k(tp) may be predicted by PBPK models because it is known to be correlated with the physicochemical property of drugs and tissue composition (fraction of lipid and water). Thus, PBPK models' evolution to predict human V(d) has been the efforts to find a better function giving a more accurate k(tp). When animal PK parameters estimated using i.v. PK data in ≥ 3 species are available, allometric methods can also be used to predict human V(d). Unlike the PBPK method, many different models may be compared to find the best-fitting one in the allometry, a kind of empirical approach. Also, compartmental V(d) parameters (e.g., V(c), V(p), and Q) can be predicted in the allometry. Although PBPK and allometric methods have long been used to predict V(d), there is no consensus on method choice. When the discrepancy between PBPK-predicted V(d) and allometry-predicted V(d) is huge, physiological plausibility of all input and output data (e.g., r(2)-value of the allometric curve) may be reviewed for careful decision making.
format Online
Article
Text
id pubmed-7781809
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Korean Society for Clinical Pharmacology and Therapeutics
record_format MEDLINE/PubMed
spelling pubmed-77818092021-01-08 Predicting human pharmacokinetics from preclinical data: volume of distribution Yim, Dong-Seok Choi, Suein Transl Clin Pharmacol Tutorial This tutorial introduces background and methods to predict the human volume of distribution (V(d)) of drugs using in vitro and animal pharmacokinetic (PK) parameters. The physiologically based PK (PBPK) method is based on the familiar equation: V(d) = V(p) + ∑(T)(V(T) × k(tp)). In this equation, V(p) (plasma volume) and V(T) (tissue volume) are known physiological values, and k(tp) (tissue plasma partition coefficient) is experimentally measured. Here, the k(tp) may be predicted by PBPK models because it is known to be correlated with the physicochemical property of drugs and tissue composition (fraction of lipid and water). Thus, PBPK models' evolution to predict human V(d) has been the efforts to find a better function giving a more accurate k(tp). When animal PK parameters estimated using i.v. PK data in ≥ 3 species are available, allometric methods can also be used to predict human V(d). Unlike the PBPK method, many different models may be compared to find the best-fitting one in the allometry, a kind of empirical approach. Also, compartmental V(d) parameters (e.g., V(c), V(p), and Q) can be predicted in the allometry. Although PBPK and allometric methods have long been used to predict V(d), there is no consensus on method choice. When the discrepancy between PBPK-predicted V(d) and allometry-predicted V(d) is huge, physiological plausibility of all input and output data (e.g., r(2)-value of the allometric curve) may be reviewed for careful decision making. Korean Society for Clinical Pharmacology and Therapeutics 2020-12 2020-12-15 /pmc/articles/PMC7781809/ /pubmed/33425799 http://dx.doi.org/10.12793/tcp.2020.28.e19 Text en Copyright © 2020 Translational and Clinical Pharmacology https://creativecommons.org/licenses/by-nc/4.0/ It is identical to the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/).
spellingShingle Tutorial
Yim, Dong-Seok
Choi, Suein
Predicting human pharmacokinetics from preclinical data: volume of distribution
title Predicting human pharmacokinetics from preclinical data: volume of distribution
title_full Predicting human pharmacokinetics from preclinical data: volume of distribution
title_fullStr Predicting human pharmacokinetics from preclinical data: volume of distribution
title_full_unstemmed Predicting human pharmacokinetics from preclinical data: volume of distribution
title_short Predicting human pharmacokinetics from preclinical data: volume of distribution
title_sort predicting human pharmacokinetics from preclinical data: volume of distribution
topic Tutorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7781809/
https://www.ncbi.nlm.nih.gov/pubmed/33425799
http://dx.doi.org/10.12793/tcp.2020.28.e19
work_keys_str_mv AT yimdongseok predictinghumanpharmacokineticsfrompreclinicaldatavolumeofdistribution
AT choisuein predictinghumanpharmacokineticsfrompreclinicaldatavolumeofdistribution