The authors of this paper, all practitioners, will present the core messages, with space for discussion at webinar on 21 March.
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Digital exchange of certificates of analysis (CoAs) and related data is generally at a low maturity level in the pharmaceutical industry.
This document presents a vision for the digital transfer of quality data, especially CoAs, throughout the pharmaceutical manufacturing value stream. It identifies 11 distinct use cases from raw materials to finished product. The primary purpose of this data to support the release process is now extended to support the demand for advanced analytics across the entire supply chain. A data model that supports both the universe of certificates and deeper test result metadata could have widespread benefits to partners.
The ASTM’s E3077-17 for exchanging CoA data relating to raw materials has seen limited adoption. In 2024 the FDA will specify PQ/CMC requiring quality data to be digitized at submission. Several sponsors and CDMOs have defined their own local standards for exchanging this type of data.
The BioPhorum IT vision is for evolution to a common approach for CoAs for all use cases across the value chain at a high level of digital maturity. This is likely to be a multi-year project. What is needed is a consolidated approach, built on what has been learnt from E3077-17 and local implementations, aligned to the emerging PQ/CMC requirement, to encompass all the use cases in the value chain while also satisfying the needs for data analytics. We must converge on the model of entities and relationships, on the logical data model, data dictionary and controlled vocabularies.
Early implementations of PQ/CMC and PQ (Industry) will be critical in positioning the future shape of data structure in this domain and proving it can work for the whole value chain, not just for submission to regulators. We must harvest the learning from what has been implemented to date so that the emergent standard is holistic, robust, unambiguous, demonstrably feasible to build and deliver benefits for all parties involved.
We need a structured approach to realization of integrations which recognizes the need to support both simpler and more complex approaches, while basing it all on the same data model.
Readers of this paper are encouraged to participate in industry activities to specify and pilot mechanisms and structures for data exchange, bringing learning from their own experiences and applying the shared learning gathered in this paper.
In light of this paper, business and digital leaders are encouraged to:
- Review current strategies and plans for implementing digital CoAs, and include data scientist perspectives
- Champion the benefits of using a digital CoA, especially moving away from paper-based and PDF format and promote a future where all levels of digital maturity can be satisfied
- Identify and overcome roadblocks to progress, including a technical platform solution for sending and receiving digital CoAs as structured data.