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Pharmaceutical Nanotechnology


ISSN (Print): 2211-7385
ISSN (Online): 2211-7393

Research Article

Computer Optimization of Stealth Biodegradable Polymeric Dual-loaded Nanoparticles for Cancer Therapy Using Central Composite Face-centered Design

Author(s): Yvonne A. Berko and Emmanuel O. Akala*

Volume 8, Issue 2, 2020

Page: [108 - 132] Pages: 25

DOI: 10.2174/2211738508666200224110410

Price: $65


Background: Combination chemotherapy capable of overcoming cancer drug resistance can be facilitated by nanotechnology.

Objective: Synthesis, characterization, statistical experimental design, analysis and optimization of stealth pH-sensitive polymeric nanoparticles suitable as a platform for simultaneous delivery of paclitaxel and 17-AAG in breast cancer therapy were investigated.

Methods: An acetal crosslinker and a poly(ɛ)caprolactone macromonomer were synthesized and characterized. The statistical experimental design used was the response surface method (RSM). We used the central composite face-centered design (CCF) in three independent factors and seventeen runs. Nanoparticles were fabricated by dispersion polymerization techniques. Response variables evaluated were: particle size, drug loading, encapsulation efficiency, and in vitro availability.

Results: Scanning electron micrographs showed the formation of spherical nanoparticles. Computer software was used for the analysis of variance with a 95% confidence level and Q2 (goodness of prediction) to select an appropriate model for each of the response variables. Each term in each of the models was tested for the significance of the regression coefficients. The computer software optimizer was used for optimization to select factor combination to minimize particle size, time (h) for maximum release of paclitaxel and 17-AAG, to maximize paclitaxel and 17-AAG loading efficiency and to maximize paclitaxel and 17-AAG encapsulation efficiency.

Conclusion: The optimization was successful, as shown by the validation data which lie within the confidence intervals of predicted values of the response variables. The selected factor combination is suitable for the in vivo evaluation of the nanoparticles loaded with paclitaxel and 17-AAG.

Keywords: Computer optimization, dispersion polymerization, pH-responsive crosslinker, poly(ɛ) caprolactone macromonomer, polymeric nanoparticles, statistical experimental design.

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