The latest artificial intelligence (AI) and machine learning (ML) methods are transforming the research and development process within drug discovery, delivering on the promise to accelerate the journey from laboratory insights to lifesaving therapies. But AI techniques aren’t enough on their own; AI is only as powerful as the data it consumes, and it works best with data that has the proper quality, detail, and context. While there is abundant scientific data in pharmaceuticals and biotechnology, it is often siloed, poorly modeled, and ultimately inaccessible. A meticulous approach to capturing and curating R&D data is indispensable to unlock the full potential of novel AI methodologies.
This white paper explains how optimizing data management – the ingestion, storage, organization, and maintenance of data – helps leaders in drug discovery leverage AI in their mission to deliver innovative drugs to patients in need.