Our vision is for a common approach for CoAs

1 March 2024
Information Technology
David Wallace
Senior Global Change Facilitator

Over the past decade, biopharmaceutical supply chains have become increasingly complex, often involving multi-enterprise manufacturing collaborations to supply lifesaving medicines.

Organizations frequently share data, but not in a way that drives agility in process analytics. Initial projects to improve digital collaboration have often involved bespoke point-to-point solutions between sponsor and contract organizations.

Without standardization, data and data structures are different from each source, vary over time/product lifecycle, and prove difficult to use for advanced purposes. For example, the digital exchange of certificates of analysis (CoAs) and related data is generally at a low maturity level in the pharmaceutical industry.

“The potential benefits of a digitalized supply chain are clear,” said Timothy Tang, IT Director at Eli Lilly. “There is enormous overhead and waste in exchanging product/quality data between supply chain partners/geographies using paper certificate processes. Industry must collaborate and co-innovate to overcome this problem; the complexity and cost are simply too enormous to solve one quality agreement at a time.”

What is needed is a consolidated approach that is aligned with the emerging pharmaceutical quality/chemistry, manufacturing and controls requirements to encompass all the use cases in the value chain while also satisfying the needs for data analytics.

Our new paper – Digital certificates of analysis and other transfers of quality test result data between organizations in the pharmaceutical supply chain – is an important step towards a digitalized supply chain.

It identifies the distinct use cases, high-level user stories, and benefits of the digital transfer of quality data, especially CoAs. It also proposes an updated entity resource model, a data dictionary to bring together several existing approaches provided by practitioners in the group, and a structured approach to integrations that recognizes the need to support simpler and more complex approaches – while basing it all on the same data model.

Our vision is for an evolution to a common approach for CoAs for all use cases across the value chain at a high level of digital maturity. To achieve this, we must converge on the model of entities and relationships, on the logical data model, data dictionary and controlled vocabularies.

“We are committed to raising efficiencies,” said Roland Kleinmaier, Senior Process Engineer Global MSAT at Roche. “The expectation is for digital transformation to be game-changing, but the staggering benefits can only be realized if standardization paves the way to implementing technological advances. Digital certificates of analysis demonstrate this situation perfectly.”

We ask that readers take part in activities to specify and pilot mechanisms and structures for data exchange, bringing learning from their own experiences and applying the shared learnings gathered in this paper.

For more information, download the paper here and contact David Wallace, Global Change Facilitator, at

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