Abstract
According to Quality by Design (QbD) concept, quality should be built into product/method during pharmaceutical/analytical development. Usually, there are many input factors that may affect quality of product and methods. Recently, Design of Experiments (DoE) have been widely used to understand the effects of multidimensional and interactions of input factors on the output responses of pharmaceutical products and analytical methods. This paper provides theoretical and practical considerations for implementation of Design of Experiments (DoE) in pharmaceutical and/or analytical Quality by Design (QbD). This review illustrates the principles and applications of the most common screening designs, such as two-level full factorial, fractionate factorial, and Plackett-Burman designs; and optimization designs, such as three-level full factorial, central composite designs (CCD), and Box-Behnken designs. In addition, the main aspects related to multiple regression model adjustment were discussed, including the analysis of variance (ANOVA), regression significance, residuals analysis, determination coefficients (R2 , R2 -adj, and R2 -pred), and lack-of-fit of regression model. Therefore, DoE was presented in detail since it is the main component of pharmaceutical and analytical QbD.
Highlights
Since the introduction of Quality-by-Design (QbD) concepts, it has been accepted that quality of pharmaceutical products should be designed and built during the manufacturing process
According to Juran (Yu et al, 2014), most of quality problems are related to the way in which a pharmaceutical product was designed
A schematic diagram of the steps for implementation of pharmaceutical Quality by Design (QbD) is showed in Figure 1a, including the relationships among Critical Material Attributes (CMA), CPA, Critical Quality Attributes (CQA), Design Space, and Quality Target Product Profile (QTPP)
Summary
Since the introduction of Quality-by-Design (QbD) concepts, it has been accepted that quality of pharmaceutical products should be designed and built during the manufacturing process. CQA may include identity, assay, content, uniformity, degradation, products, residual solvents, drug release or dissolution, moisture content, microbial limits, Design of Experiments (DoE) applied to Pharmaceutical and Analytical Quality by Design (QbD)
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