Dexamethasone-releasing cochlear implant coatings: application of artificial neural networks for modelling of formulation parameters and drug release profile

2013 ◽  
Vol 65 (8) ◽  
pp. 1145-1157 ◽  
Author(s):  
Pedram Nemati ◽  
Mohammad Imani ◽  
Farhid Farahmandghavi ◽  
Hamid Mirzadeh ◽  
Ehsan Marzban-Rad ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Drug Release ◽  
Cochlear Implant ◽  
Release Profile ◽  
Drug Release Profile ◽  
Artificial Neural ◽  
Formulation Parameters ◽  
Implant Coatings

scholarly journals Effect of Processing/Formulation Parameters on Particle Size of Nanoemulsions Containing Ibuprofen - An Artificial Neural Networks Study

2020 ◽  
Vol 27 (2) ◽  
pp. 230-237
Author(s):  
Ali Hanafi ◽  
Amir Amani
Keyword(s):  
Neural Networks ◽  
Particle Size ◽  
Artificial Neural Networks ◽  
Droplet Size ◽  
Tween 80 ◽  
Homogenization Time ◽  
Minimum Particle Size ◽  
Artificial Neural ◽  
Formulation Parameters ◽  
Positive Effect

Background: Nanoemulsions are colloidal transparent systems for the delivery of hydrophobic drugs. This study aimed to determine the effect of parameters affecting particle size of a nanoemulsion containing ibuprofen using artificial neural networks (ANNs). Methods: Nanoemulsion samples with different values of independent variables, namely, concentration of ethanol, ibuprofen and Tween 80 as well as exposure (homogenization) time were prepared and their particle size was measured using dynamic light scattering (DLS). The data were then modelled by ANNs. Results: From the results, increasing the exposure time had a positive effect on reducing droplet size. The effect of concentration of ethanol and Tween 80 on droplet size depended on the amount of ibuprofen. Our results demonstrate that ibuprofen concentration also had a reverse relation with the size of the nanoemulsions. Conclusion: It was concluded that to obtain minimum particle size, exposure (homogenization)time should be maximized.

Application of artificial neural networks (ANNs) and genetic programming (GP) for prediction of drug release from solid lipid matrices

2012 ◽  
Vol 436 (1-2) ◽  
pp. 877-879 ◽  
Author(s):  
Sinan Güres ◽  
Aleksander Mendyk ◽  
Renata Jachowicz ◽  
Przemysław Dorożyński ◽  
Peter Kleinebudde
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Drug Release ◽  
Genetic Programming ◽  
Solid Lipid ◽  
Artificial Neural
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