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Article

Application of Response Surface Optimization Methodology in Designing Ordispersible Tablets of Antdiabetic Drug

Fatima Sanjeri Dasankoppa1★, Hasanpasha N Sholapur2, Andanesh Byahatti3, Zaheer Abbas4, Komal S5, Kundu Subrata6★ Corresponding author

  1. 1Department of Pharmaceutics, KLE College of Pharmacy, Vidyanagar, Hubballi, Karnataka, INDIA.
  2. 2Department of Pharmacognosy, KLE College of Pharmacy, Vidyanagar, Hubballi, Karnataka, INDIA.
  3. 3Markson Pharma Ltd, Verna Industrial Estate, Verna, Goa-403722, INDIA.
  4. 4Apotex Pvt.Ltd, Bangalore, Karnataka, INDIA.
  5. 5Department of Pharmaceutics, Dr. MGR Educational and Research Institute, Chennai, Tamil Nadu, INDIA.
  6. 6Vergo Pvt. Ltd., Goa, INDIA.

CORRESPONDENCE

Fatima Sanjeri Dasankoppa

Department of Pharmaceutics, KLE College of Pharmacy, Vidyanagar, Hubballi, Karnataka, INDIA.

fsdsankop@gmail.com

Received: 01-04-2020; Revised: 02-05-2020; Accepted: 09-06-2020.

Volume 12, Issue 2 · pp. 173–177 · PUBLISHED · DOI: 10.5530/jyp.2020.12.35

View on JYP original site ↗

ABSTRACT

Objectives:The aim of the present investigation is to study the application of Response Surface Methodology (RSM), a mathematical model and graphical representation to formulate and Optimize Orodispersible Tablets (ODTs) of sitagliptin phosphate, a class III BCS drug. Methods:ODTs were prepared by direct compression method using dibasic calcium phosphate (DCP), as diluent and croscarmellose sodium sodium (CCS) as super disintegrant. Formulation was designed using design expert software 9.0 version. RSM based 22 full factorial design, considering DCP and CCS as variables and dissolution time at 5, 15 and 30 min was taken as response. Mathematical models in the form of regression equations and graphs were developed.Results:The adequacy of the developed mathematical models was statistically checked through the analysis of variance (ANOVA). The responses were analyzed using ANOVA and polynomial equation was generated for each response using RSM. Responses were mostly affected by the specific combinations of independent variable. R2 predicted and R2 adjusted values for the constructed models, which revealed the competence for the proposed mathematical model. Based on the results obtained DF1 formulation was optimized. The developed mathematical models can be successfully used for their prediction of measured responses. Conclusion:DoE Concept in formulation could pave way for adaptation of Quality Based Design (QbD) in pharmaceutical industry RSM was successfully applied to optimize diluents and disintegrate concentration of ODTs. The variables employed in the study had a great effect on the quality of formulation. Modeling of experimental data allowed the generation of useful equations for prediction of responses.

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    Dasankoppa, F. S., Sholapur, H. N., Byahatti, A., Abbas, Z., S, K., & Subrata, K. (). Application of Response Surface Optimization Methodology in Designing Ordispersible Tablets of Antdiabetic Drug. Journal of Young Pharmacists, 12(2), 173–177. https://doi.org/10.5530/jyp.2020.12.35