(456d) TOPS: Ontological Informatics in Pharmaceutical Manufacturing

Authors: 
Joglekar, G., Purdue University
Giridhar, A. V., Purdue University
Reklaitis, G. V., Purdue University
Venkatasubramanian, V., Purdue University


Pharmaceutical manufacturing requires the management of a large amount of process data and process knowledge. Knowledge about a pharmaceutical process include equipment parameters, material properties, mathematical models describing unit operations or the process, and models describing appropriate control strategies. Ancillary to the direct manufacturing activities are other information management tools such as ERP and LIMS systems. Tremendous benefit lies in streamlined management of knowledge within a pharmaceutical manufacturing environment: in facilitating production decisions; in relating process settings to material properties; in the selection of optimal control strategies; and in validating the knowledge residing in the knowledge management system. Enabling such decisions to be taken together reduces or eliminates the delay of iterating between them.

In this work we describe The Ontologies for Particulate Systems (TOPS), an ontological informatics framework that was developed by the Engineering Research Center for Structured Organic Particulate Systems (ERC-SOPS). TOPS is a production-oriented ontological system that draws upon our earlier research effort: POPE (Purdue Ontology for Pharmaceutical Engineering). We describe the separate ontologies that comprise TOPS, how they enable different work groups to populate and update the instances independently, but also enable combined use of the knowledge so entered.

We also describe the applications that TOPS has enabled. Particularly we show our approach in linking the TOPS framework to a distributed control system for enabling real-time process management of tablet manufacture. Further, we show how the ontologies can also handle flexible plants, whose process flowsheets can be changed quickly to accommodate new product formulations. In this work we summarize our key findings and offer some general conclusions.