期刊
JOURNAL OF PHARMACEUTICAL SCIENCES
卷 94, 期 12, 页码 2764-2776出版社
JOHN WILEY & SONS INC
DOI: 10.1002/jps.20358
关键词
dissolution; Biopharmaceutical Classification System; Box-Behnken experimental design; hard gelatin capsules; similarity factor; Bayesian Networks; in silico modeling; encapsulation; formulation; low solubility drugs
This project compared the effect of formulation variables on the dissolution performance of model Biopharmaceutics Classification System (BCS) Class II drugs from hard gelatin capsules using statistical analysis and Bayesian networks. The drugs chosen for this study were carbamazepine (CAR), chlorpropamide (CHL), diazepam (DIA), ketoprofen (YET), and naproxen (NAP). Formulations contained anhydrous lactose, microcrystalline cellulose, sodium stearyl fumerate, sodium lauryl sulfate, and croscarmellose sodium. A Box-Behnken experimental design was used in the statistical analysis. The weakly acidic drugs were tested using USP apparatus II with capsule sinkers in 0.1M pH 6.8 Potassium Phosphate buffer. The weakly basic drugs were tested using USP apparatus I in 0.1N HCl buffer. Mean dissolution profiles were compared via calculation of the similarity factor. The Box-Behnken experimental design was found to be useful in assessing primary and secondary excipient effects on dissolution. The Bayesian Network developed for the dataset mirrored the key excipient effects on dissolution performance. (c) 2005 Wiley-Liss, Inc. and the American Pharmacists Association.
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