title: Determination of factors controlling the particle size and entrapment efficiency of noscapine in PEG/PLA nanoparticles using artificial neural networks.
abstract: In this study, di- and triblock copolymers based on polyethylene glycol and polylactide were synthesized by ring-opening polymerization and characterized by proton nuclear magnetic resonance and gel permeation chromatography. Nanoparticles containing noscapine were prepared from these biodegradable and biocompatible copolymers using the nanoprecipitation method. The prepared nanoparticles were characterized for size and drug entrapment efficiency, and their morphology and size were checked by transmission electron microscopy imaging. Artificial neural networks were constructed and tested for their ability to predict particle size and entrapment efficiency of noscapine within the formed nanoparticles using different factors utilized in the preparation step, namely polymer molecular weight, ratio of polymer to drug, and number of blocks that make up the polymer. Using these networks, it was found that the polymer molecular weight has the greatest effect on particle size. On the other hand, polymer to drug ratio was found to be the most influential factor on drug entrapment efficiency. This study demonstrated the ability of artificial neural networks to predict not only the particle size of the formed nanoparticles but also the drug entrapment efficiency. This may have a great impact on the design of polyethylene glycol and polylactide-based copolymers, and can be used to customize the required target formulations.
authors.affiliation: Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
authors.forename: Karim S
authors.initials: KS
authors.lastname: Shalaby
authors.affiliation: Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
authors.forename: Mahmoud E
authors.initials: ME
authors.lastname: Soliman
authors.affiliation: Department of Biomolecular Sciences, School of Pharmacy, University of Urbino, Urbino, Italy.
authors.forename: Luca
authors.initials: L
authors.lastname: Casettari
authors.affiliation: School of Pharmacy, University of Camerino, Camerino, Italy.
authors.forename: Giulia
authors.initials: G
authors.lastname: Bonacucina
authors.affiliation: School of Pharmacy, University of Camerino, Camerino, Italy.
authors.forename: Marco
authors.initials: M
authors.lastname: Cespi
authors.affiliation: School of Pharmacy, University of Camerino, Camerino, Italy.
authors.forename: Giovanni F
authors.initials: GF
authors.lastname: Palmieri
authors.affiliation: Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
authors.forename: Omaima A
authors.initials: OA
authors.lastname: Sammour
authors.affiliation: Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, Cairo, Egypt.
authors.forename: Abdelhameed A
authors.initials: AA
authors.lastname: El Shamy
mesh_terms: D002626:Chemistry, Pharmaceutical / Q000379:methods*; D053758:Nanoparticles / Q000737:chemistry*; D036103:Nanotechnology / Q000379:methods*; D016571:Neural Networks, Computer; D009665:Noscapine / Q000737:chemistry*; D010316:Particle Size; D011092:Polyethylene Glycols / Q000737:chemistry*
chemical_list: C542623:monomethoxypolyethyleneglycol-polylactide block copolymer; D011092:Polyethylene Glycols; D009665:Noscapine
keywords: artificial neural networks (ANNs); biodegradable nanoparticles; noscapine; polyethylene glycol (PEG); polylactide (PLA)