Role of physicochemical properties in the estimation of skin permeability: in vitro data assessment by Partial Least-Squares Regression

References

• Degim , T . 2005 . Understanding skin penetration: Computer aided modeling and data interpretation . Curr. Comput. Aided Drug Des. , 1 : 11 – 19 .
   Web of Science ®Google Scholar
• Degim , T . 2006 . New tools and approaches for predicting skin permeability . Drug Discov. Today , 11 : 517 – 523 .
   PubMed Web of Science ®Google Scholar
• Kielhorn , J , Kollmuß , SM and Mangelsdorf , I . 2005 . The Dermal Absorption , 90 – 91 . Hanover : Fraunhofer Institute Toxicology and Experimental Medicine .
   Google Scholar
• Vecchia , BE and Bunge , AL . 2003 . Transdermal drug delivery, in Skin Absorption Database and Predictive Equations , Edited by: Guy , RH and Hadgraft , J . 57 – 142 . New York : Marcel Dekker .
   Google Scholar
• Roberts , MS , Pugh , WJ , Hadgraft , J and Watkinson , AC . 1995 . Epidermal permeability-penetrant structure relationships: 1. An analysis of methods of predicting penetration of monofunctional solutes from aqueous solutions . Int. J. Pharm. , 126 : 219 – 233 .
   Web of Science ®Google Scholar
• Pugh , WJ , Degim , IT and Hadgraft , J . 2000 . Epidermal permeability-penetrant structure relationships: 4, QSAR of permeant diffusion across human stratum corneum in terms of molecular weight, H-bonding and electronic charge . Int. J. Pharm. , 197 : 203 – 211 .
   PubMed Web of Science ®Google Scholar
• Chen , LJ , Lian , GP and Han , LJ . 2007 . Prediction of human skin permeability using artificial neural network (ANN) Modeling . Acta Pharmacol. Sin. , 28 : 591 – 600 .
   PubMed Web of Science ®Google Scholar
• Mitragotri , S . 2003 . Modeling skin permeability to hydrophilic and hydrophobic solutes based on four permeation pathways . J. Control. Rel. , 86 : 69 – 92 .
   PubMed Web of Science ®Google Scholar
• Lian , G , Chen , L and Han , L . 2008 . An evaluation of mathematical models for predicting skin permeability . J. Pharm. Sci. , 97 : 584 – 598 .
   PubMed Web of Science ®Google Scholar
• Chen , L , Lian , G and Han , L . 2010 . Modeling transdermal permeation. Part I. Predicting skin permeability of both hydrophobic and hydrophilic solutes . AIChE J. , 56 : 1136 – 1146 .
   Web of Science ®Google Scholar
• Flynn , GL . 1990 . “ Physicochemical determinants of skin absorption ” . In Principles of Route-to-Route Extrapolation for Risk Assessment , Edited by: Gerrity , TR and Henry , CJ . 93 – 127 . New York : Elsevier .
   Google Scholar
• Potts , RO and Guy , RH . 1992 . Predicting skin permeability . Pharm. Res. , 9 : 663 – 669 .
   PubMed Web of Science ®Google Scholar
• Lien , EJ and Gao , H . 1995 . QSAR analysis of skin permeability of various drugs in man as compared to in vivo and in vitro studies in rodents . Pharm. Res. , 12 : 583 – 587 .
   PubMed Web of Science ®Google Scholar
• Barratt , MD . 1995 . Quantitative structure-activity relationships for skin permeability . Toxicol. In Vitro , 9 : 27 – 37 .
   PubMed Web of Science ®Google Scholar
• Potts , RO and Guy , RH . 1995 . A predictive algorithm for skin permeability: The effects of molecular size and hydrogen bond activity . Pharm. Res. , 12 : 1628 – 1633 .
   PubMed Web of Science ®Google Scholar
• Abraham , MH , Chadha , HS and Mitchell , RC . 1995 . The factors that influence skin penetration of solutes . J. Pharm. Pharmacol. , 47 : 8 – 16 .
   Web of Science ®Google Scholar
• Kirchner , LA , Moody , RP , Doyle , E , Bose , R , Jeffrey , J and Chu , I . 1997 . The prediction of skin permeability by using physicochemical data . Altern. Lab Anim. , 25 : 359 – 370 .
   Web of Science ®Google Scholar
• Hostynek , JJ and Magee , PS . 1997 . Modelling in vivo human skin absorption . Quant. Struct. Act. Relat. , 16 : 473 – 479 .
   Google Scholar
• Abraham , MH , Chadha , HS , Martins , F , Mitchell , RC , Bradbury , MW and Gratton , JA . 1999 . Hydrogen bonding part 46: A review of the correlation and prediction of transport properties by an LFER method: Physicochemical properties, brain penetration and skin permeability . Pestic. Sci. , 55 : 78 – 88 .
   Google Scholar
• Gute , BD , Grunwald , GD and Basak , SC . 1999 . Prediction of the dermal penetration of polycyclic aromatic hydrocarbons (PAHs): A hierarchical QSAR approach . SAR QSAR Environ. Res. , 10 : 1 – 15 .
   PubMed Web of Science ®Google Scholar
• Cronin , MTD , Dearden , JC , Moss , GP and Murray-Dickson , G . 1999 . Investigation of the mechanism of flux across human skin in vitro by quantitative structure-permeability relationships . Eur. J. Pharm. Sci. , 7 : 325 – 330 .
   PubMed Web of Science ®Google Scholar
• Dearden , JC , Cronin , MTD , Patel , H and Raevsky , OA . 2000 . QSAR prediction of human skin permeability coefficients . J. Pharm. Pharmacol. , 52 : 221
   Google Scholar
• Patel , H , Berge , W and Cronin , MTD . 2002 . Quantitative structure-activity relationships (QSARs) for the prediction of skin permeation of exogenous chemicals . Chemosphere , 48 : 603 – 613 .
   PubMed Web of Science ®Google Scholar
• Roy , TA , Krueger , AJ , Mackerer , CR , Neil , W , Arroyo , AM and Yang , JJ . 1998 . SAR models for estimating the percutaneous absorption of polynuclear aromatic hydrocarbons . SAR QSAR Environ. Res. , 9 : 171 – 185 .
   PubMed Web of Science ®Google Scholar
• Wilschut , A , Ten-Berge , WF , Robinson , PJ and McKone , TE . 1995 . Estimating skin permeation. The validation of five mathematical skin permeation models . Chemosphere , 30 : 1275 – 1296 .
   PubMed Web of Science ®Google Scholar
• Dearden , JC , Cronin , MTD and Kaiser , KLE . 2009 . How not to develop a quantitative structure-activity or structure-property relationship (QSAR/QSPR) . SAR QSAR Environ. Res. , 20 : 241 – 266 .
   PubMed Web of Science ®Google Scholar
• Geinoz , S , Guy , RH , Testa , B and Carrupt , PA . 2004 . Quantitative structure-permeation relationships (QSPeRs) to predict skin permeation: A critical evaluation . Pharm. Res. , 21 : 83 – 92 .
   PubMed Web of Science ®Google Scholar
• EDETOX database. Available at http://edetox.ncl.ac.uk/. Accessed 24 December 2009
   Google Scholar
• Tropsha , A , Gramatica , P and Gombar , VK . 2003 . The importance of being earnest: Validation is the absolute essential for successful application and interpretation of QSAPR models . QSAR Comb. Sci. , 22 : 69 – 77 .
   Google Scholar
• Lei , B , Li , J , Liu , H and Yao , X . 2008 . Accurate prediction of aquatic toxicity of aromatic compounds based on genetic algorithm and least square support vector machines . QSAR Comb. Sci. , 27 : 850 – 865 .
   Google Scholar
• Kennard , RW and Stone , L . 1969 . Computer aided design of experiments . Technometrics , 11 : 137 – 148 .
   Web of Science ®Google Scholar
• Daszykowski , M , Serneels , S , Kaczmarek , K , Van Espen , P , Croux , C and Walczak , B . 2007 . TOMCAT: A MATLAB toolbox for multivariate calibration techniques . Chemom. Intell. Lab. Syst. , 85 : 269 – 277 .
   Web of Science ®Google Scholar