Technology Transfer: Shifting The Paradigm To Dynamic And Persistent Process Knowledge Sharing

Product and process knowledge and various data accumulate in early R&D, development, commercial manufacturing and during clinical trials. While lab research and some product characterization data may be captured digitally, there is often a “digital data gap” that develops (and persists) after product candidate selection and prior to commercial manufacturing. This is driven by the reliance on spreadsheets and paper records prior to the adoption of digital systems such as MES, EBR and historians in a mature manufacturing IT landscape.

Effective technology transfer needs to bridge this gap in order to accelerate commercialization and meet production COGS targets and the increasing demands for data integrity and transparency throughout the supply chain.

Forward-looking companies are deploying cloud-based, Part 11-compliant, centralized data hubs as their persistent knowledge “libraries” for process, product and patient data. These collaborative data platforms even capture relevant documents and notes and provide a full audit trail of changes to specifications and target control limits. This approach eliminates the risks associated with the “transfer” of technology – as the data remains persistent and available even as staff, partners - and facilities - may change.