The development of a pharmaceutical product requires the collection of information during pre-formulation studies, product formulation, process development, scaleup and manufacturing. A large amount of information of different types, ranging from raw data to lab reports to sophisticated math models, has to be shared, utilized and modified by humans for decision making. This functionality requires an informatics infrastructure which supports different activities by streamlining information gathering, data integration, model development and decision making (Venkatasubramanian et al, 2006). The foundation of such an infrastructure is the explicitly and formally modeled information, called an ontology.

The Purdue Ontology for Pharmaceutical Engineering is presented here. Information is captured in the form of concepts and the relations between concepts. The ontology is centered on the concepts of materials, experiments and properties and builds on previous work. Through the definition of the ontology, several functions that are difficult to perform like complicated searches, association storage and reasoning are made available.

Researchers should cite this work as follows:

• venkat; laelaf; Rex Reklaitis; pradeepsuresh (2008), "Information Representation in POPE," https://pharmahub.org/resources/90.

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1. Knowledge-based systems