QUALITY BY DESIGN DRIVEN STATISTICAL SCREENING APPROACH TO SELECT EFFECTIVE VARIABLES FOR THE FORMULATION DEVELOPMENT OF PEGYLATED BILOSOMES FOR AN ANTIFUNGAL DRUG
DOI:
https://doi.org/10.22159/ijap.2025v17i1.52138Keywords:
Candida albicans, Pegylated bilosomes, Screening, Design of Experiments, Full factorial designAbstract
Objective: The study aimed to use a quality-by-design approach to screen out the most suitable process and formulation parameters for developing antifungal drug-loaded pegylated bilosomes.
Methods: Thin film hydration technique was used to prepare the formulations. A design experiment [Design Expert® software; Design of Experiments (DOE)] employing two levels at three factors was used to conduct eight runs to select and screen formulation and process variables. It was assessed for different response variables, such as Particle Size (PS), Polydispersity Index (PDI), Zeta Potential (ZP), and Entrapment Efficiency (%EE). The screened formulation was evaluated for in vitro drug release and kinetic model evaluation.
Results: The significance of each term in the model was evaluated using an Analysis of Variance (ANOVA). Statistical model terms with a significant P-value of less than 0.05 and graphical analysis (Interaction plot, Pareto chart, and 3D plots) generated by DOE version 13 demonstrated that Span 60, Brij C2, and amplitude of 30% were effective variables for formulating pegylated bilosomes with a desirability value of 0.965. The validated formulation showed a PS of 299.1±5.12 nm, PDI of 0.481±0.07, ZP of -36.6±0.55 mV, and %EE of 79.25±2.75. The in vitro release showed a sustained drug release of 55.53±6.75% over 24 h.
Conclusion: Statistical screening approach using a full factorial design can serve as a valuable tool in identifying and screening significant variables for developing antifungal-encapsulated pegylated bilosomes formulations.
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