In 2016, the FAIR Guiding Principles for scientific data management and stewardship were published, laying out guideposts for scholarly data producers to make their data discoverable and usable in the future. The FAIR principles seek to ensure that data is Findable, Accessible, Interoperable, and Reusable. At the time of their publication, they articulated and centralized many points…
How federated learning can enable faster, more accurate pharmaceutical-grade AI
It’s been said that data is the new oil, something pharma researchers understand well. The phrase hits especially close to home for artificial intelligence (AI) researchers who work heavily with medical images. Medical imaging is a powerful diagnostic tool in the drug development process, as it can provide the efficacy and safety monitoring required in…
5 common data management problems affecting drug discovery
Ask a pharma researcher how well they’re able to leverage their organization’s medical imaging data, and you might hear a discouraging response. While most pharma companies have massive amounts of clinical and medical imaging data, often, most of the imaging data isn’t ready for modern research processes and infrastructure. This imaging data is an untapped…