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This work was aimed to formulate the atenolol loaded PLGA nanoparticles through optimizing formulation variables using 33 factorial design.
Interactions between the formulation variables were evaluated according to Univariate ANOVA.
Risk analysis and Plackett Burman design were utilized to evaluate formulation variables in two paths.
The effect of different formulation variables on LSPCs performance was evaluated using 32 factorial design.
A full factorial design was employed for the optimization of formulation variables using Design-Expert® software.
A Box-Behnken (BB) design, using Design-Expert® software, was employed to statistically optimize formulation variables.
The formulation variables; including particle size, drug entrapment efficiency (%EE), and release rate were characterized.
Our research has demonstrated that formulation variables can be exploited in order to tailor particle size.
The effects of the formulation variables on pellet properties were evaluated by analysis of variance.
The process and formulation variables were optimized by achieving maximum drug encapsulation efficiency.
Formulation variables within a double emulsion solvent evaporation technique were controlled to optimise physicochemical properties.
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