Preparation and in vitro characterization of etofenamate  emulgels using quality by design

Sakine Tuncay Tanrıverdi; Buket Aksu; Gizem Yeğen; Kevser Özgen Özer

Makale detayları

Preparation and in vitro characterization of etofenamate emulgels using quality by design

Yazarlar:

Sakine Tuncay Tanrıverdi | Buket Aksu | Gizem Yeğen | Kevser Özgen Özer

Yayıncı:

Marmara University

Ana Başlıklar:

Basic Pharmacology

Dergi:

Journal of Research in Pharmacy Vol.23 Issue 6, pp.1033-1039

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001347951

pISSN:

2630-6344

Anahtar kelimeler:

Özet:

 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 todays 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.

 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 todays 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.

 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 todays 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.

 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 todays 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.

Makale detayları

Preparation and in vitro characterization of etofenamate emulgels using quality by design

Yazarlar:

Sakine Tuncay Tanrıverdi | Buket Aksu | Gizem Yeğen | Kevser Özgen Özer

Yayıncı:

Marmara University

Ana Başlıklar:

Basic Pharmacology

Dergi:

Journal of Research in Pharmacy Vol.23 Issue 6, pp.1033-1039

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001347951

pISSN:

2630-6344

Quality by design

etofenamate

artificial neural networks (ANNs)

gene expression programming (GEP)

emulgel

Sayı

Makale detayları

Preparation and in vitro characterization of etofenamate emulgels using quality by design

Yazarlar: Sakine Tuncay Tanrıverdi | Buket Aksu | Gizem Yeğen | Kevser Özgen Özer

Yayıncı: Marmara University

Ana Başlıklar: Basic Pharmacology

Dergi: Journal of Research in Pharmacy Vol.23 Issue 6, pp.1033-1039

Belge Tipi: Makale

Yayın Tarihi: 6/2025

Belge Dili: İngilizce

Document ID (Org No.): 2001347951

pISSN: 2630-6344

Quality by design

etofenamate

artificial neural networks (ANNs)

gene expression programming (GEP)

emulgel

Sayı

Yazarlar:

Sakine Tuncay Tanrıverdi | Buket Aksu | Gizem Yeğen | Kevser Özgen Özer

Yayıncı:

Marmara University

Ana Başlıklar:

Basic Pharmacology

Dergi:

Journal of Research in Pharmacy Vol.23 Issue 6, pp.1033-1039

Belge Tipi:

Makale

Yayın Tarihi:

6/2025

Belge Dili:

İngilizce

Document ID (Org No.):

2001347951

pISSN:

2630-6344