An Artificial Neural Network Approach to Predict the Effects of Formulation and Process Variables on Prednisone Release from a Multipartite System

An Artificial Neural Network Approach to Predict the Effects of Formulation and Process Variables on Prednisone Release from a Multipartite System

The impact of formulation and process variables on the in-vitro release of prednisone from a multiple-unit pellet system was investigated. Box-Behnken Response Surface Methodology (RSM) was used to generate multivariate experiments. The extrusion-spheronization method was used to produce pellets and...

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Bibliographic Details
Main Authors: Arthur Manda, Roderick B. Walker, Sandile M. M. Khamanga
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Pharmaceutics
Subjects:
prednisone
Response Surface Methodology
artificial neural networks
multi-layer perceptron
multiple-unit
extrusion-spheronization
USP Apparatus 2
Box–Behnken
reversed-phase high-performance liquid chromatography
Online Access:http://www.mdpi.com/1999-4923/11/3/109

Internet

http://www.mdpi.com/1999-4923/11/3/109

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