(144d) Road to the Promised Land of QbD: Informatics and Modeling Challenges

Developing and manufacturing pharmaceutical products in a timely manner while ensuring quality is a complex process that requires handling vast amounts of varied data, information, and knowledge. The new FDA framework of PAT-QbD, and the ICH Q8R, Q9, and Q10 (step 2) guidelines, pose major modeling and informatics challenges that have not been fully appreciated by the pharmaceutical industry, and will require radically new approaches and significant investments. However, recent progress in information and knowledge management technologies offer hope. One such approach is called Ontological Informatics. An ontology is a formal and explicit specification of a shared abstract model of a phenomenon through identification of its relevant concepts.  An ontology defines and semantically describes data, information, and models. In this talk, I will discuss the use of such a framework for modeling two different types of knowledge often needed for QbD: mathematical knowledge, as in equations, and decision-making knowledge, such as decision trees and heuristics. I will discuss the challenges, opportunities and emerging trends using case studies from pharmaceutical manufacturing.