A Cost Effective (QbD) Approach in the Development and Optimization of Rosiglitazone Maleate Mucoadhesive Extended Release Tablets - In Vitro and Ex Vivo - Suryaprakash Reddy Chappidi; Eranti Bhargav; Venkataranganna Marikunte; Haranath Chinthaginjala; Mallela Vijaya Jyothi; Muralidhar Pisay; Mounika Jutur; Mujahid Shaik Mahammad; Mrunalini Poura; Sailaja Yadav; Moinuddin Syed (Tabriz University of Medical Sciences, 2019)
Purpose: The purpose of the study was to develop and optimize rosiglitazone maleate mucoadhesive extended-release tablets by quality by design (QbD) approach. Based on QTPP (quality target product profile) CQAs (critical quality attributes) were identified. Methods: Failure mode and effects analysis (FMEA) method were adopted for risk assessment. Risk analysis by the evaluation of formulation and process parameters showed that the optimizing the levels of polymers could reduce high risk to achieve target profile. Drug-excipient compatibility studies by Fourier transforms infra-red and DSC studies showed that the drug was compatible with the polymers used. Design of experiment (DoE) performed by Sigma tech software, Carbopol 934P and sodium carboxymethyl cellulose (SCMC) were identified as independent variables and hardness, drug release at 12 hours and ex vivo mucoadhesion time were adopted as responses. Contour plots generated from the software were used for identification of design space. Results: Carbopol 934P and SCMC had positive and negative effects respectively on the selected responses. Higher the concentration of Carbopol 934P and lower the concentration of SCMC mucoadhesive extended release criteria could be achieved. Drug release kinetics followed first order release with Higuchi diffusion and Fickian diffusion. Ex vivo mucoadhesion test on goat stomach mucosa indicated that adhesion time increased at higher concentrations of Carbopol 934P. Optimized formula satisfying all the required parameters was selected and evaluated. The predicted response values were in close agreement with experimental response values, confirmed by calculating standard error. Conclusion: It has been concluded that the application of QbD in the optimization reduced the number of trials to produce a cost-effective formula.