title: Modeling and Prediction of Solvent Effect on Human Skin Permeability using Support Vector Regression and Random Forest.
abstract: OBJECTIVE
  The solvent effect on skin permeability is important for assessing the effectiveness and toxicological risk of new dermatological formulations in pharmaceuticals and cosmetics development. The solvent effect occurs by diverse mechanisms, which could be elucidated by efficient and reliable prediction models. However, such prediction models have been hampered by the small variety of permeants and mixture components archived in databases and by low predictive performance. Here, we propose a solution to both problems.
  
  
  METHODS
  We first compiled a novel large database of 412 samples from 261 structurally diverse permeants and 31 solvents reported in the literature. The data were carefully screened to ensure their collection under consistent experimental conditions. To construct a high-performance predictive model, we then applied support vector regression (SVR) and random forest (RF) with greedy stepwise descriptor selection to our database. The models were internally and externally validated.
  
  
  RESULTS
  The SVR achieved higher performance statistics than RF. The (externally validated) determination coefficient, root mean square error, and mean absolute error of SVR were 0.899, 0.351, and 0.268, respectively. Moreover, because all descriptors are fully computational, our method can predict as-yet unsynthesized compounds.
  
  
  CONCLUSIONS
  Our high-performance prediction model offers an attractive alternative to permeability experiments for pharmaceutical and cosmetic candidate screening and optimizing skin-permeable topical formulations.
authors.affiliation: Kyoto R&D Center, Maruho Co., Ltd., 93 Awata-cho, Chudoji, Shimogyo-ku, 600-8815, Kyoto, Japan. baba_dfq@mii.maruho.co.jp.|Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, 46-29, Yoshida-shimoadachicho, Sakyo-ku, Kyoto, 606-8501, Japan. baba_dfq@mii.maruho.co.jp.
authors.forename: Hiromi
authors.initials: H
authors.lastname: Baba
authors.affiliation: Kyoto R&D Center, Maruho Co., Ltd., 93 Awata-cho, Chudoji, Shimogyo-ku, 600-8815, Kyoto, Japan.
authors.forename: Jun-ichi
authors.initials: J
authors.lastname: Takahara
authors.affiliation: Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, 46-29, Yoshida-shimoadachicho, Sakyo-ku, Kyoto, 606-8501, Japan.
authors.forename: Fumiyoshi
authors.initials: F
authors.lastname: Yamashita
authors.affiliation: Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, 46-29, Yoshida-shimoadachicho, Sakyo-ku, Kyoto, 606-8501, Japan.|Institute for Integrated Cell-Material Sciences, Kyoto University, 46-29, Yoshida-shimoadachicho, Sakyo-ku, Kyoto, 606-8501, Japan.
authors.forename: Mitsuru
authors.initials: M
authors.lastname: Hashida
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D006801:Humans; D016014:Linear Models; D008954:Models, Biological; D015233:Models, Statistical; D010539:Permeability; D004364:Pharmaceutical Preparations / Q000008:administration & dosage / Q000737:chemistry* / Q000378:metabolism*; D012867:Skin / Q000378:metabolism*; D012869:Skin Absorption / Q000187:drug effects*; D012997:Solvents / Q000737:chemistry* / Q000378:metabolism; D060388:Support Vector Machine
chemical_list: D004364:Pharmaceutical Preparations; D012997:Solvents
keywords: in silico prediction; quantitative structure–property relationship; skin permeability; solvent effect; support vector regression