To goal is to build a pharmaceutical (CMC) process ontology based on the ISA88/95 framework to standardize laboratory and plant production process recipes to establish standardized definitions, facilitate digital technology transfers, and integration with execution systems in order to capture structured process data for material lot genealogy tracking, streamlined technology transfers, and advanced process analytics, thereby enhancing efficiency and transparency throughout the pharmaceutical production lifecycle.

Why is this important?

Chemical development has been supported by the ISA 88 standard for decades.  A lot has changed in that time, and a more flexible, comprehensive representation of process data is needed. A contemporary ontology provides the data representation that is needed to facilitate data integration, data exchange and data insights. 
 

What will the project achieve?

The scope and key deliverables of this work will include:

  • CMC laboratory & manufacturing scale API & Pharmaceutical Product processes 
  • Biologics & Synthetics with an initial focus on protein and chemical processes
  • Develop domain lexicon and domain taxonomy to accomplish seamless convergence of the protein and chemical processes
  • An advanced semantic architectural design for a Process Ontology, featuring seamless integration with the established Product (IDMP-O), Analytical (AFO), and Unit of Measure (QUDT) ontologies
  • A taxonomy and controlled vocabulary based on the ISA88/95 framework for Process/Stage /Operation/Action, Process Parameters, Process Performance Indicators, and their definitions

How will the project do this?

Initially, we will work to cover the following use cases:

  • Standardize and digitize laboratory production process (stage) definitions, enabling structured process data capture. 
  • Establish digital API & Pharmaceutical Product process definitions for automated CMC dossier authoring 
  • Enable digital Process Technology Transfer from laboratory to plant (scale up) and between plants 
  • Enable advanced process analytics (process performance) across laboratory and process batches (across scale) 

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