Scale-up of any pharmaceutical manufacturing process entails a skillful combination of art experience, science and engineering. Application of statistical methods is ever-increasing for design of experiments and development of empirical relationships between process parameters, material attributes and quality attributes. Advances in measurement tools (PAT) and quantitative analysis/modeling tools, from simple process heuristics to advanced modeling tools such as CFD, DEM, PBM,., enable engineers to design and scale-up pharmaceutical processes with more confidence and reliability. These advances are expected to cause a paradigm shift from “Trial&Error” to “Rational Process Design” in process scale-up within the spirit of the QbD initiative. Although use of DOE for product/process development has been well-received within the pharmaceutical community and has been demonstrated on many case studies, it is not clear how this approach can be applied to or sustained for process scale-up, or whether the pharmaceutical industry needs to develop a more innovative use of the existing tools. In this session, we seek papers that focus on the use of quantitative tools (e.g. DOE, modeling, and theory) toward scaling-up pharmaceutical processes. The session will provide a forum for open exchange of ideas or innovative use of tools for successful scale-up of the pharmaceutical processes. Papers concerning all areas of pharmaceutical scale-up, from small molecules to biologics, from drug substances to drug products, are being considered. The goal of the session is to demonstrate different scale-up approaches toward reaching a consensus for rational, pharmaceutical process scale-up as opposed to “Trial-&-Error”.

Topical i : Comprehensive Quality by Design in Pharmaceutical Development and Manufacture

Pharmaceuticals (15b)