Design and Optimization of Hydrogel as a Drug Delivery System

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Konca S. F., Öz U. C., Bozkır A.

Materials Science and Nanotechnology for Next Generation, Kayseri, Turkey, 27 - 29 September 2023, pp.121

  • Publication Type: Conference Paper / Summary Text
  • City: Kayseri
  • Country: Turkey
  • Page Numbers: pp.121
  • Erciyes University Affiliated: Yes


10th International Conference on Materials Science and Nanotechnology For Next Generation (MSNG-2023)

27-29 September 2023 / TÜRKİYE

Design and Optimization of Hydrogel as a Drug Delivery System

S. Furkan KONCA1,2, Umut Can ÖZ3, Asuman BOZKIR3*

1 Erciyes University, Faculty of Pharmacy, Department of Pharmaceutical Biotechnology, 38039, Kayseri, TURKEY

2Ankara University, Biotechnology Institute, 06135, Ankara, TURKEY

3 Ankara University, Faculty of Pharmacy, Department of Pharmaceutical Technology, 06560, Ankara, TURKEY

*Corresponding E-mail:

Design of Experiment (DOE) is a critical tool used in the design and optimization of drug delivery systems. DOE offers a wide array of significant advantages by providing a comprehensive toolkit encompassing experimental design, data analysis, modeling, and simulation. Creating comprehensive experimental plans for optimizing the active components and production conditions of drug delivery systems is more efficient than costly trial-and-error methods in terms of time and resources. DOE also provides the ability to simultaneously statistically analyze experimental results, enabling a better understanding of data, assessing potential effects, and interpreting results reliably. Through graphical visualization capabilities, enables better data visualization and easier trend observation. Additionally, it offers specialized tools for multi-response optimization, allowing for the simultaneous optimization of multiple response variables. This study aimed to design and optimize a hydrogel formulation incorporating hyaluronic acid for local application with the intention of facilitating rapid wound healing and drug release. The results revealed that formulation parameters significantly impacted the viscosity, hardness, adhesiveness, cohesiveness and elasticity of the formulations. The developed design model demonstrated a high correlation between predicted responses and evaluated parameters.