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Balancing competing objectives in bigel formulations using many-objective optimization algorithms and different

Mohamed Kouider Amar1, Soufiane Rahal2, Maamar Laidi3

  • 1Biomaterials and Transport Phenomena Laboratory (LBMPT), University Dr., Yahia Fares of Medea, Medea 26000, Algeria; Department of Process Engineering, Institute of Technology, University Dr., Yahia Fares of Medea, Medea 26000, Algeria; Laboratory of Quality Control, Physico-Chemical Department, SAIDAL of Medea, Medea 26000, Algeria; Faculty of Technology, University Dr., Yahia Fares of Medea, Medea 26000, Algeria.

European Journal of Pharmaceutics and Biopharmaceutics : Official Journal of Arbeitsgemeinschaft Fur Pharmazeutische Verfahrenstechnik E.V
|December 20, 2023
PubMed
Summary

This study optimized bigel systems using many-objective optimization (MaOEAs) to balance conflicting properties like microstructural characteristics, stability, and drug release. The RSM-RVEA approach demonstrated effective convergence for complex formulation challenges.

Keywords:
BigelsDecision-making methodsDrug deliveryMany-objective optimization algorithmsResponse surface methodologyRheology

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Area of Science:

  • Materials Science
  • Chemical Engineering
  • Pharmaceutical Sciences

Background:

  • Bigel systems are crucial for drug delivery, requiring optimization of multiple properties like rheology, stability, and drug release.
  • Balancing competing objectives in bigel formulation presents significant challenges due to complex ingredient interactions.

Purpose of the Study:

  • To explore evolutionary algorithms for optimizing microstructural, rheological, stability, and drug release properties of bigel systems.
  • To address conflicting objectives in bigel formulation using many-objective optimization (MaOEAs) techniques.
  • To develop a robust framework for compromising bigel performance and stability for drug delivery applications.

Main Methods:

  • Formulation of bigel systems using structured almond oil, mixed organogelators, and carbopol.
  • Characterization of microstructural, rheological, stability, and drug release properties.
  • Application of Response Surface Methodology coupled with Many-Objective Evolutionary Algorithms (RSM-MaOEAs) and decision-making methods (WSM, WPM, NED).

Main Results:

  • Bigels exhibited non-Newtonian shear-thinning and thixotropic behaviors, influenced by excipient proportions.
  • Phase separation occurred in highly concentrated bigels under stress; lower viscosity bigels showed reduced drug release.
  • FT-IR and HPLC confirmed drug-excipient compatibility and formulation stability with minimal impurities (<4%).

Conclusions:

  • Complex interactions within lipid-based bigels necessitate MaOEAs for effective optimization.
  • The RSM-RVEA approach showed superior convergence in optimizing conflicting bigel properties.
  • The proposed RSM-MaOEAs framework offers a robust solution for bigel formulation, applicable to advanced drug delivery systems.