Ability of mathematical models to predict human in vivo percutaneous penetration of steroids.
Aqueous solubility
Human
Hydrogen bonds
In vivo
Octanol water partition coefficient
Percutaneous penetration
Permeability constant
Potts and Guy model
Steroids
Journal
Regulatory toxicology and pharmacology : RTP
ISSN: 1096-0295
Titre abrégé: Regul Toxicol Pharmacol
Pays: Netherlands
ID NLM: 8214983
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
received:
22
04
2021
revised:
31
08
2021
accepted:
03
09
2021
pubmed:
10
9
2021
medline:
18
1
2022
entrez:
9
9
2021
Statut:
ppublish
Résumé
Human skin is a common route for topical steroids to enter the body. To aid with risk management of therapeutic steroid usage, the US Environmental Protection Agency estimates percutaneous penetration using mathematical models. However, it is unclear how accurate are mathematical models in estimating percutaneous penetration/absorption of steroids. In this study, accuracy of predicted flux (penetration/absorption) by the main mathematical model used by the EPA, the Potts and Guy model based on in vitro data is compared to actual human in vivo data from our laboratory of percutaneous absorption of topical steroids. We focused on steroids due to the availability of steroid in vivo human data in our laboratory. For most steroids the flux was underestimated by a factor 10-60. However, within the group itself, there was an association between the Potts and Guy model and experimental human in vivo data (Pearson Correlation = 0.8925, p = 0.000041). Additionally, some physiochemical parameters used in the Potts and Guy equation, namely log Kp (Pearson Correlation = 0.7307, p = 0.0046) and molecular weight (Pearson correlation = -0.6807, p = 0.0105) correlated significantly with in vivo flux. Current mathematical models used in estimating percutaneous penetration/absorption did not accurately predict in vivo flux of steroids. Why? Proposed limitations to mathematical models currently used include: not accounting for volatility, lipid solubility, hydrogen bond effects, drug metabolism, as well as protein binding. Further research is needed in order to increase the predictive nature of such models for in vivo flux.
Identifiants
pubmed: 34499979
pii: S0273-2300(21)00182-3
doi: 10.1016/j.yrtph.2021.105041
pii:
doi:
Substances chimiques
Steroids
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
105041Informations de copyright
Copyright © 2021. Published by Elsevier Inc.