The pre-formulative screening for polymeric nanoparticles (NPs) manufacture is a very long and laborious process. It is essential however for the selection of the best experimental conditions. The chemical and physical properties of NPs can be affected by different factors and variables during their preparation and thus, the aim of this work is to study the influence of the polymer concentration and the organic to aqueous phase ratio on PLGA-PEG NPs by using a D-optimal Response Surface Methodology (RSM) design. A total of nine formulations were prepared using the nanoprecipitation method, purified and characterized for their size, polydispersity index (PDI) and zeta potential. All formulations were subjected to stability studies after storage over six months under refrigeration. Prediction of the optimal nanosystem was performed using the desirability function targeting the reduction of NPs size and PDI. The optimized NPs formulation (F-1) showed similar theoretical and experimental values, confirming the predictive ability of the mathematical model. The formulation F-1 loaded with Berberine Chloride showed appropriate technological properties for potential intranasal or systemic administration. Our results conclusively demonstrated that RSM is a useful and efficient tool to design new nanoformulation with the least number of experiments

Design and optimization of PEGylated nanoparticles intended for Berberine Chloride delivery

Musumeci, Teresa;Bonaccorso, Angela
;
Carbone, Claudia;Russo, Giulia;Pappalardo, Francesco;Puglisi, Giovanni
2019-01-01

Abstract

The pre-formulative screening for polymeric nanoparticles (NPs) manufacture is a very long and laborious process. It is essential however for the selection of the best experimental conditions. The chemical and physical properties of NPs can be affected by different factors and variables during their preparation and thus, the aim of this work is to study the influence of the polymer concentration and the organic to aqueous phase ratio on PLGA-PEG NPs by using a D-optimal Response Surface Methodology (RSM) design. A total of nine formulations were prepared using the nanoprecipitation method, purified and characterized for their size, polydispersity index (PDI) and zeta potential. All formulations were subjected to stability studies after storage over six months under refrigeration. Prediction of the optimal nanosystem was performed using the desirability function targeting the reduction of NPs size and PDI. The optimized NPs formulation (F-1) showed similar theoretical and experimental values, confirming the predictive ability of the mathematical model. The formulation F-1 loaded with Berberine Chloride showed appropriate technological properties for potential intranasal or systemic administration. Our results conclusively demonstrated that RSM is a useful and efficient tool to design new nanoformulation with the least number of experiments
2019
Design of experiment; Nanoprecipitation; Natural compound; Optimization strategies; Polymer; Stability studies
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/365409
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