https://commons.ru.ac.za/vital/access/manager/Index ${session.getAttribute("locale")} 5 An artificial neural network approach to predict the effects of formulation and process variables on prednisone release from a multipartite system https://commons.ru.ac.za/vital/access/manager/Repository/vital:43933 Tue 14 May 2024 10:58:09 SAST ]]> The use of quantitative analysis and Hansen solubility parameter predictions for the selection of excipients for lipid nanocarriers to be loaded with water soluble and insoluble compounds https://commons.ru.ac.za/vital/access/manager/Repository/vital:43981 Tue 14 May 2024 10:57:46 SAST ]]> Formulation optimization of smart thermosetting lamotrigine loaded hydrogels using response surface methodology, box benhken design and artificial neural networks https://commons.ru.ac.za/vital/access/manager/Repository/vital:43936 Tue 14 May 2024 10:57:23 SAST ]]> Formulation and Characterisation of a Combination Captopril and Hydrochlorothiazide Microparticulate Dosage Form https://commons.ru.ac.za/vital/access/manager/Repository/vital:43926 75% for both hydrochlorothiazide and captopril. The microparticulate technology is able to offer potential resolution to the half-life mediated dosing frequency of captopril as sustained release of the molecule was observed over a 12-h period. The release of hydrochlorothiazide of >80% suggests an improvement in solubility limited dissolution.]]> Tue 14 May 2024 10:56:57 SAST ]]> Design, Optimization, Manufacture and Characterization of Efavirenz-Loaded Flaxseed Oil Nanoemulsions https://commons.ru.ac.za/vital/access/manager/Repository/vital:43919 Tue 14 May 2024 10:55:07 SAST ]]>