title: Application of artificial neural networks in the design of controlled release drug delivery systems.
abstract: Controlled release drug delivery systems offer great advantages over the conventional dosage forms. However, there are great challenges to efficiently develop controlled release drug delivery systems due to the complexity of these delivery systems. Traditional statistic response surface methodology (RSM) is one of the techniques that has been employed to develop and formulate controlled release dosage forms. However, there are some limitations to the RSM technique. Hence, another technique called artificial neural networks (ANN) has recently gained wide popularity in the development of controlled release dosage forms. In this review, the basic ANN structure, the development of the ANN model and an explanation of how to use ANN to design and develop controlled release drug delivery systems are discussed. In addition, the applications of ANN in the design and development of controlled release dosage forms are also summarized in this review.
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee, 26 South Dunlap Street, 214 Feurt Building, Memphis, TN 38163, USA. ysun@utmem.edu
authors.forename: Yichun
authors.initials: Y
authors.lastname: Sun
authors.forename: Yingxu
authors.initials: Y
authors.lastname: Peng
authors.forename: Yixin
authors.initials: Y
authors.lastname: Chen
authors.forename: Atul J
authors.initials: AJ
authors.lastname: Shukla
mesh_terms: D003692:Delayed-Action Preparations / Q000008:administration & dosage / Q000737:chemistry* / Q000493:pharmacokinetics; D015195:Drug Design; D016571:Neural Networks, Computer; D013678:Technology, Pharmaceutical / Q000379:methods*
chemical_list: D003692:Delayed-Action Preparations