title: Generalized regression neural networks in prediction of drug stability.
abstract: This study had two aims. Firstly, we wanted to model the effects of the percentage of Eudragit RS PO and compression pressure as the most important process and formulation variables on the time course of drug release from extended-release matrix aspirin tablets. Secondly, we investigated the possibility of predicting drug stability and shelf-life using an artificial neural network (ANN). Ten types of matrix aspirin tablets were prepared as model formulations and were stored in stability chambers at 60 degrees C, 50 degrees C, 40 degrees C and 30 degrees C and controlled humidity. Samples were removed at predefined time points and analysed for acetylsalicylic acid (ASA) and salicylic acid (SA) content using stability-indicating HPLC. The decrease in aspirin content followed apparent zero-order kinetics. The amount of Eudragit RS PO and compression pressure were selected as causal factors. The apparent zero-order rate constants for each temperature were chosen as output variables for the ANN. A set of output parameters and causal factors were used as training data for the generalized regression neural network (GRNN). For two additional test formulations, Arrhenius plots were constructed from the experimentally observed and GRNN-predicted results. The slopes of experimentally observed and predicted Arrhenius plots were tested for significance using Student's t-test. For test formulations, the shelf life (t(95%)) was then calculated from experimentally observed values (t(95%) 82.90 weeks), as well as from GRNN-predicted values (t(95%) 81.88 weeks). These results demonstrate that GRNN networks can be used to predict ASA content and shelf life without stability testing for formulations in which the amount of polymer and tablet hardness are within the investigated range.
authors.affiliation: Department of Pharmaceutical Technology, Faculty of Pharmacy, University of Belgrade, Vojvode Stepe 450, 11221 Belgrade, Serbia. ibric@beotel.yu
authors.forename: Svetlana
authors.initials: S
authors.lastname: Ibrić
authors.forename: Milica
authors.initials: M
authors.lastname: Jovanović
authors.forename: Zorica
authors.initials: Z
authors.lastname: Djurić
authors.forename: Jelena
authors.initials: J
authors.lastname: Parojcić
authors.forename: Ljiljana
authors.initials: L
authors.lastname: Solomun
authors.forename: Branka
authors.initials: B
authors.lastname: Lucić
mesh_terms: D000894:Anti-Inflammatory Agents, Non-Steroidal / Q000737:chemistry*; D001241:Aspirin / Q000737:chemistry*; D002626:Chemistry, Pharmaceutical; D002851:Chromatography, High Pressure Liquid; D003692:Delayed-Action Preparations; D004339:Drug Compounding; D015195:Drug Design; D004355:Drug Stability; D004356:Drug Storage; D006244:Hardness; D016571:Neural Networks, Computer; D011109:Polymethacrylic Acids / Q000737:chemistry*; D020156:Salicylic Acid; D013607:Tablets; D013696:Temperature
chemical_list: D000894:Anti-Inflammatory Agents, Non-Steroidal; D003692:Delayed-Action Preparations; C496966:Eudragit RSPO; D011109:Polymethacrylic Acids; D013607:Tablets; D020156:Salicylic Acid; D001241:Aspirin