Fragment contribution models for predicting skin permeability using HuskinDB.

Mathematical models to predict skin permeation tend to be based on animal derived experimental data as well as knowing physicochemical properties of the compound under investigation, such as molecular volume, polarity and lipophilicity. This paper presents a strikingly contrasting model to predict permeability, formed entirely from simple chemical fragment (functional group) data and a recently released, freely accessible human (i.e.

Predicting skin permeability using HuskinDB.

A freely accessible database has recently been released that provides measurements available in the literature on human skin permeation data, known as the 'Human Skin Database - HuskinDB'. Although this database is extremely useful for sourcing permeation data to help with toxicity and efficacy determination, it cannot be beneficial when wishing to consider unlisted, or novel compounds. This study undertakes analysis of the data from within HuskinDB to create a model that predicts permeation for any compound (within the range of properties used to create the model).