title: Application of artificial neural networks in optimizing the fatty alcohol concentration in the formulation of an O/W emulsion.
abstract: The purpose of this study was to optimize the concentration of a fatty alcohol, in addition to internal phase, for formulating a stable O/W emulsion, by using artificial neural networks (ANNs). Predictions from ANNs are accurate and allow quantification of the relative importance of the inputs. Furthermore, by varying the network topology and parameters it was possible to obtain output values that were close to experimental values. The ANN model's predictive results and the actual output values were compared. R(2) values depict the percentage of response variability for the model; R(2) value of 0.84 for the model suggested adequate modeling, which is supported by the correlation coefficient value of 0.9445.
authors.affiliation: Birla Institute of Technology, Mesra Ranchi, 835215, India. jayaram_res@yahoo.com
authors.forename: K Jayaram
authors.initials: KJ
authors.lastname: Kumar
authors.forename: Gopal Mohan
authors.initials: GM
authors.lastname: Panpalia
authors.forename: Surabhi
authors.initials: S
authors.lastname: Priyadarshini
mesh_terms: D055598:Chemical Phenomena; D007851:Dodecanol / Q000737:chemistry; D004339:Drug Compounding; D004355:Drug Stability; D004553:Electric Conductivity; D045703:Emulsifying Agents / Q000737:chemistry*; D004655:Emulsions; D005233:Fatty Alcohols / Q000737:chemistry*; D008899:Mineral Oil / Q000737:chemistry; D008956:Models, Chemical; D016571:Neural Networks, Computer; D009994:Osmolar Concentration; D014677:Pharmaceutical Vehicles / Q000737:chemistry; D012967:Sodium Dodecyl Sulfate / Q000737:chemistry; D013501:Surface-Active Agents / Q000737:chemistry; D013678:Technology, Pharmaceutical; D014783:Viscosity
chemical_list: D045703:Emulsifying Agents; D004655:Emulsions; D005233:Fatty Alcohols; D014677:Pharmaceutical Vehicles; D013501:Surface-Active Agents; D007851:Dodecanol; D012967:Sodium Dodecyl Sulfate; D008899:Mineral Oil