Data is needed to train artificial intelligence (AI) and drive machine learning (ML), making data management more vital today than ever before in drug discovery, development, and delivery. However, the biopharmaceutical industry faces challenges when handing Big Data, which must be findable, accessible, interoperable, and reusable (FAIR). Much data are fragmented, walled off in small pockets by proprietary formats, standalone systems, and lack of cloud access.

Download this white paper from TetraScience to discover the benefits of harmonizing data in a form that is FAIR, regulatory compliant, and actionable in the cloud for research and development, downstream manufacturing, and quality control. 

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