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Arrayo delivered a cloud-based solution comprised of the following components:
Data was extracted, cleaned, and transformed with the maximum accuracy possible.
The bulk of the documents were historic, already assembled as a document store. They needed to be processed in batch, as a one-time effort, with no human-powered workflow involved. The NLP data processing pipeline would automatically process the historical manufacturing biologics stability reports to feed into the Biologics Developability Platform. There was no substantial scalability & deployment consideration once the initial historic data was processed. If additional similarly structured documents were generated and used by the R&D processes, those new documents would be processed automatically on an ongoing basis with similar accuracy.
The project created a document data processing pipeline for extracting, cleaning, and transforming the Biologics stability data and made it available to support R&D research projects, such as building internal models for in silico Biologics Developability Prediction for early R&D projects. This solution is a good example of how cross functional collaboration efforts on the AI/ML platforms can be leveraged to support R&D.