Biopharma’s drug quality efforts are hindered by a lack of data uniformity in the supply chain according to the National Institute for Innovation in Manufacturing Biopharmaceuticals (NIIMBL), which has teamed up with Open Applications Group (OAGi) to encourage the adoption of common standards.

The partnership—announced in June—will focus on a major source of variation in drug production says Roger Hart, PhD, NIIMBL senior fellow and Big Data project lead.

He told GEN, “Biopharmaceutical manufacturers procure raw materials and consumables from many suppliers and variation among those materials can lead to variation in biopharmaceutical product quality. Regulatory agencies are aware of this impact and provide guidance to control raw material attributes used in manufacturing to manage risk; doing so requires access to data from suppliers all of whom use different data structures.”

“Similarly,” he continued, “suppliers provide their raw material products to many different biopharmaceutical manufacturers who each use a different data structure; they also produce raw material products using materials obtained from their supply chain all of whom use different data structures.”

There is also a lack of standardization when it comes to analytics according to Hart, who said that while most manufacturers use workarounds, they are far from ideal.

“The equipment used in manufacturing and analysis uses proprietary data standards from technology providers. Owing to the lack of standardization, manual intervention or software ‘patches’ are used to transfer data between the many disparate nodes in the system, which is costly and not sustainable.”


To address the lack of data uniformity, NIIMBL and OAGi will try to encourage the drug industry and its suppliers to use an ontology—or set of common standards—for raw materials.

Hart said, “By creating and adopting a canonical standard to support data transfer in this many-to-many system data can be more rapidly shared to support manufacturing control and quality deviation investigations thereby reducing costs by elimination of manual intervention and reduced failures.”

The partnership is in keeping with the OAGi’s aim of improving business process models, data standards, ontologies, documentation, tools, best practices, and training.

Most resources developed within OAGi are open-source or open standard, which is key according to Hart.

“These two important characteristics of OAGi are necessary to promote both the industry participation in the development and the adoption of the standard; thus, helping NIIMBL to reach its goal of data interoperability.”

The project will also leverage materials developed by OAGi’s Industrial Ontology Foundry (IOF) unit. Hart said, “IOF has existing reference ontologies, best practices, experts, and infrastructure that together can help the biopharmaceutical manufacturing industry accelerate and improve the quality of its ontologies,” adding that “We are advancing the use of formal ontologies as a means to increase standardization in data storage and translation and thereby lower the barriers for data sharing and use. Ontologies are available to everyone at no cost with a MIT license to lower barriers and drive consistency.”

“By creating ontologies in open-source, low-cost, easy-access approach we lower the barriers for creation, expansion, adoption, and implementation of the standardized vocabulary and relationships.”

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