Editor-in-Chief İlkay Küçükgüzel Associate Editor Esra Tatar Online ISSN 2630-6344 Publisher Marmara University Frequency Bimonthly (Six issues / year) Abbreviation J.Res.Pharm. Former Name Marmara Pharmaceutical Journal
Journal of Research in Pharmacy 2019 , Vol 23 , Issue 6
Preparation and in vitro characterization of etofenamate emulgels using quality by design
Gülşen YILMAZ1,Sakine TUNCAY TANRIVERDİ2,Buket AKSU3,Gizem YEGEN3,Özgen ÖZER2
1Turkish Medicines and Medical Devices Agency, Quality Department, Ankara, Turkey
2Ege University, Faculty of Pharmacy, Department of Pharmaceutical Technology, İzmir, Turkey
3Altınbaş University, Faculty of Pharmacy, Department of Pharmaceutical Technology, İstanbul, Turkey
DOI : 10.35333/jrp.2019.67 Quality by Design (QbD) emerged with quality guidelines issued by the International Council on Harmonization (ICH); is a concept that suggests the quality of product cannot be secured by the finish product tests; product quality should be ensured by starting from risk and scientific based work in process and product development through the whole product life cycle. Statistical studies, which are done by computer program, have important role in today’s pharmaceutical area. ANN (Artificial Neural Network) and GEP (Gene Expression Programming) are modelling techniques can be used for analyzing big amount of data, in understanding the relations between dependent and independent variables affecting product quality and optimizing the formulation variables and process parameters to get the desired product quality continuously. In this study, different etofenamate emulgel formulations were prepared, the quality characteristics determined to be critical were evaluated separately with the ANN, and GEP modeling techniques for the optimization of the formulations examined. During the modeling, the input values were oil type, oil ratio and polymer ratio and the outputs were pH, conductivity, viscosity and flow properties of the emulgels. According to results of pre-formulation studies both of the programs suggested two optimized formulations. Depending on the further studies, the viscosity and rheological behavior showed that both formulations were could apply on skin. Keywords : Quality by design; etofenamate; artificial neural networks (ANNs); gene expression programming (GEP); emulgel
Marmara University