title: Quantitative structure-property relationship modeling of remote liposome loading of drugs.
abstract: Remote loading of liposomes by trans-membrane gradients is used to achieve therapeutically efficacious intra-liposome concentrations of drugs. We have developed Quantitative Structure Property Relationship (QSPR) models of remote liposome loading for a data set including 60 drugs studied in 366 loading experiments internally or elsewhere. Both experimental conditions and computed chemical descriptors were employed as independent variables to predict the initial drug/lipid ratio (D/L) required to achieve high loading efficiency. Both binary (to distinguish high vs. low initial D/L) and continuous (to predict real D/L values) models were generated using advanced machine learning approaches and 5-fold external validation. The external prediction accuracy for binary models was as high as 91-96%; for continuous models the mean coefficient R(2) for regression between predicted versus observed values was 0.76-0.79. We conclude that QSPR models can be used to identify candidate drugs expected to have high remote loading capacity while simultaneously optimizing the design of formulation experiments.
authors.affiliation: Department of Biochemistry, IMRIC, The Hebrew University-Hadassah Medical School Jerusalem, Israel.
authors.forename: Ahuva
authors.initials: A
authors.lastname: Cern
authors.forename: Alexander
authors.initials: A
authors.lastname: Golbraikh
authors.forename: Aleck
authors.initials: A
authors.lastname: Sedykh
authors.forename: Alexander
authors.initials: A
authors.lastname: Tropsha
authors.forename: Yechezkel
authors.initials: Y
authors.lastname: Barenholz
authors.forename: Amiram
authors.initials: A
authors.lastname: Goldblum
mesh_terms: D001185:Artificial Intelligence; D002626:Chemistry, Pharmaceutical; D003198:Computer Simulation; D003663:Decision Trees; D004337:Drug Carriers / Q000737:chemistry*; D004339:Drug Compounding; D057927:Hydrophobic and Hydrophilic Interactions; D008567:Membranes, Artificial; D008956:Models, Chemical; D015394:Molecular Structure; D004364:Pharmaceutical Preparations / Q000008:administration & dosage* / Q000737:chemistry*; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D015203:Reproducibility of Results; D012984:Software
chemical_list: D004337:Drug Carriers; D008567:Membranes, Artificial; D004364:Pharmaceutical Preparations