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Title: Preparation and Optimization of N-Acetylcysteine Nanosuspension through Nanoprecipitation: An Artificial Neural Networks Study
Journal: Journal of Pharmaceutical Innovation
Author: 1. Shayan Abbasi, 2. Ali Afrasiabi, 3,4. Ali Akbar Karimi Zarchi, Amir Amani, 5. Mohammad Ali Faramarzi, 6. Gholamreza Tavoosidana
Year: 2014
Address: 1. Department of Biology, Faculty of Science, University of Guilan, Rasht, Iran 2.Institute of Biochemistry and Biophysics (IBB), University of Tehran, Tehran, Iran 3. Department of Medical Nanotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran 4. Department of Pharmaceutical Biotechnology, Biotechnology Research Center, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran 5. Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran 6. Medical Biomaterials Research Center, Tehran University of Medical Sciences, Tehran, Iran
Abstract: Purpose Nanosuspensions, as a promising strategy to improve the solubility and bioavailability of poorly water soluble drugs, have been widely investigated in recent years. However, no comprehensive work so far has detailed the effect of independent processing/formulation parameters on the quality of the prepared nanosuspension. Methods In the present study, the relations between solvent flow rate, stirring rate of antisolvent and surfactant concentration (i.e., inputs) on size, and polydispersity index (PDI) (i.e., outputs) of an N-acetylcysteine nanosuspension were investigated using artificial neural networks (ANNs). Results and conclusion The response surfaces, generated as 3D graphs after ANNs modeling, demonstrated that all the three factors have a reverse effect on size and PDI. The dominant factor appeared to be the concentration of surfactant. Overall, it was found that the optimum formulation (i.e., minimum size and PDI value) is obtained at high values of surfactant concentration, solvent flow rate, and stirring rate (i.e., >0.9 mg/ml and 120 ml/h and 500 rpm, respectively).
Keywords: N-acetylcysteine . Artificial neural networks . Nanoprecipitation . Nanosuspension . Polydispersity index
Application: Drug Delivery
Product Model 1: Syringe Pump
Product Model 2:
URL: https://link.springer.com/article/10.1007/s12247-014-9178-1#="https://link.springer.com" & "/article/10.1007/s12247-014-9178-1"#