An ontological informatics approach to mechanistic mathematical model management in pharmaceutical product development

Pradeep Suresh Babu, Purdue University

Abstract

Pharmaceutical Product Development is a crucial and critical step in the drug development process. It is capital intensive, time consuming in nature and is also an extremely information and knowledge intensive process. This presents various challenges to manage the information and knowledge involved in a systematic, reusable yet user-friendly manner. The term knowledge, in this context, comprises of decision making knowledge and mathematical knowledge that captures the families of mathematical model based knowledge that exists in this domain. OntoMODEL, is an ontological mathematical model management tool that facilitates systematic and standardizable methods for model storage, use and solving. While the declarative knowledge in mathematical models has been captured using ontologies, the procedural knowledge required for solving these models has been handled by commercially available scientific computing and programming language software. Several case studies of mechanistic mathematical model families and their corresponding unit operations were captured in the form of ontologies and simulated using the proposed framework. The interactions involved are well established and the approach intuitive, therefore not requiring user familiarity with any particular programming language or modeling software. Apart from this key benefit, the fact that OntoMODEL lends itself to more advanced applications such as model predictive control, process optimization, knowledge based decision making, model based fault diagnosis, and process flowsheet simulation makes it an indispensable tool in the intelligent automation of process operations. OntoMODEL provides an easy and intuitive approach to analyze controller performance so that the novice user can plug and play with various controller configurations with minimum effort. OntoMODEL can also be implemented as part of an ontological decision making framework and two case studies where it is used in coordination with frameworks that support formulation development and regulatory compliance are shown as part of this work. The overall objective of this effort is that OntoMODEL be a one stop shop for mathematical model based applications in the domain of Chemical and Pharmaceutical process and product development.

Degree

Ph.D.

Advisors

Reklaitis, Purdue University.

Subject Area

Chemical engineering|Artificial intelligence

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