A novel approach to establishing the design space for the oral formulation manufacturing process was investigated. A response surface method incorporating multivariate spline interpolation was applied to overcome the nonlinear problem, which is always problematic in pharmaceutical development studies, and a bootstrap resampling technique, polynomial approximation technique, and 95% confidence intervals based on a nonparametric approach were applied to estimate the reliability of the established design space derived from the nonlinear response surface model. The critical quality attributes (CQAs) of intermediate material rather than the critical process parameters (CPPs) were chosen as the causal factors for the response variables, which were CQAs of the final product to avoid scale-gap and equipment-gap. This enabled the effective use of data sets accumulated during all pharmaceutical development studies. It was confirmed that a conservative border as well as an optimistic border of the design space for practical use was obtained considering the variability of the border of the design spaces on nonlinear response surfaces. Furthermore, the nonlinear response surface model using CQAs of intermediate material derived from data sets of a laboratory scale study and pilot scale studies could predict the CQA of the final product (2.5 h dissolution of commercial-scale study) with high accuracy. Consequently, the proposed novel approach overcame all of the difficulties for the manufacturing process development of oral formulations and this is the first study to demonstrate the effectiveness of the design space using CQA of intermediate material for the oral formulation manufacturing process.Key words design space; experimental design; response surface method; multivariate statistical analysis; confidence interval; critical quality attribute In recent years, the "quality by design" (QbD) concept has been introduced by the International Conference on Harmonization (ICH) Q8 guideline. This guideline has recommended establishing a science-based rationale in pharmaceutical development studies for both formulation development and manufacturing process development. The guideline also noted that the multidimensional relationships of causal factors that have been demonstrated to provide specified target values of response variables are defined as the design space, and the establishment of the design space based on scientific understanding gained from pharmaceutical development studies and manufacturing experience provides the regulatory flexibility.
1)Therefore, the establishment of the design space is important not only to achieve a higher level of scientific understanding, but also to gain regulatory flexibility.To establish the design space, a design-of-experiments (DoE) approach was used effectively to determine the multidimensional relationships among causal factors and response variables.2,3) A response surface method (RSM) is useful for visual understanding of the derived multidimensional relationships.4-7) However, the m...