Leveraging Compound and Therapeutic Antibody Analytical Data
Analytical methods are essential for the progression of a therapeutic molecule in the pharma research value chain. The primary purpose of analytical methods is to answer (bio-)chemical structural questions, where the data generated is often used only once. In parallel, we have data science applying machine learning and AI approaches. This requires a large amount of data in a consistent and “compatible” format, which are not usually available or accessible. This talk presents our journey on leveraging analytical data, the steps from data acquisition, capture, storage, unlocking the data through conversion, and offering it back to the lab and data scientists through a system built following the FAIR principles.