Quality by design approach for tablet formulations containing spray coated ramipril by using artificial intelligence techniques

Different software programs based on mathematical models have been developed to aid the product development process. Recent developments in mathematics and computer science have resulted in new programs based on artificial neural networks (ANN) techniques. These programs have been used to develop and formulate pharmaceutical products. In this study, intelligent software was used to predict the relationship between the materials that were used in tablet formulation and the tablet specifications and to determine highly detailed information about the interactions between the formulation parameters and the specifications. The input data were generated from historical data and the results obtained from analyzing tablets produced by different formulations. The relative significance of inputs on various outputs such as assay, dissolution in 30 min and crushing strengths, was investigated using the artificial neural networks (ANNs), neurofuzzy logic and genetic programming (FormRules, INForm ANN and GEP).This study indicated that ANN and GEP can be used effectively for optimizing formulations and that GEP can be evaluated statistically because of the openness of its equations. Additionally, FormRules was very helpful for teasing out the relationships between the inputs (formulation variables) and the outputs

Quality by design approach for tablet formulations containing spray coated ramipril by using artificial intelligence techniques

Different software programs based on mathematical models have been developed to aid the product development process. Recent developments in mathematics and computer science have resulted in new programs based on artificial neural networks (ANN) techniques. These programs have been used to develop and formulate pharmaceutical products. In this study, intelligent software was used to predict the relationship between the materials that were used in tablet formulation and the tablet specifications and to determine highly detailed information about the interactions between the formulation parameters and the specifications. The input data were generated from historical data and the results obtained from analyzing tablets produced by different formulations. The relative significance of inputs on various outputs such as assay, dissolution in 30 min and crushing strengths, was investigated using the artificial neural networks (ANNs), neurofuzzy logic and genetic programming (FormRules, INForm ANN and GEP).This study indicated that ANN and GEP can be used effectively for optimizing formulations and that GEP can be evaluated statistically because of the openness of its equations. Additionally, FormRules was very helpful for teasing out the relationships between the inputs (formulation variables) and the outputs

Enhancement of immune response of HBsAg loaded poly(L-lactic acid) microspheres against Hepatitis B through incorporation of alum and chitosan

Purpose: Poly (L-lactic acid) (PLA) microparticles encapsulating Hepatitis B surface antigen (HBsAg) with alum and chitosan were investigated for their potential as a vaccine delivery system. Methods: The microparticles, prepared using a water-in-oil-in-water (w/o/w) double emulsion solvent evaporation method with polyvinyl alcohol (PVA) or chitosan as the external phase stabilising agent showed a significant increase in the encapsulation efficiency of the antigen. Results: PLA-Alum and PLA-chitosan microparticles induced HBsAg serum specific IgG antibody responses significantly higher than PLA only microparticles and free antigen following subcutaneous administration. Chitosan not only imparted a positive charge to the surface of the microparticles but was also able to increase the serum specific IgG antibody responses significantly. Conclusions: The cytokine assays showed that the serum IgG antibody response induced is different according to the formulation, indicated by the differential levels of interleukin 4 (IL-4), interleukin 6 (IL-6) and interferon gamma (IFN-γ). The microparticles eliciting the highest IgG antibody response did not necessarily elicit the highest levels of the cytokines IL-4, IL-6 and IFN-γ