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DIA/Tufts CSDD Research: AI Saving Time in Drug Development
DIA and the Tufts Center for the Study of Drug Development mapped current use of and experience with AI and ML and their ability to reduce time in the drug development lifecycle.
Uncover expert insights through global and regional coverage of the discovery, development, regulation, surveillance, and marketing of healthcare products, including interviews with thought leaders and topical summaries from educational events.
“There were a few of her patients who were victims of substance abuse, and seeing how my aunt provided care for them inspired me to discover methods to treat victims such as these with a career in pharmacy.”
“We still have a lot of unmet medical and patient needs that can only be addressed when the community (including researchers, physicians, and policymakers) decide to work together. This is happening more and more in recent years, the outcomes of which you see in some of the most advanced medicines and healthcare systems available today.”
“The greatest challenge in my view is the lack of harmonization among global health authorities. I will moderate that statement by saying that we should not harmonize for the sake of harmonization. We should harmonize to the best practice.”
Vice President and Head, Regulatory Policy, North American Regulatory Affairs, Bayer
“There were a few of her patients who were victims of substance abuse, and seeing how my aunt provided care for them inspired me to discover methods to treat victims such as these with a career in pharmacy.”