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The winning team relied on “handcrafted” features that incorporated their own insights into drugdevelopment timelines and which dataentries should be discarded, according to MIT. The results were interesting, but the team wanted to do better. .
Drugdevelopment is already a difficult endeavor, with the vast majority of R&D efforts failing to produce a market-worthy product. Even reaching the clinical trial phase offers no guarantees, as only 12% of such drugs receive U.S. While this process is essential, it’s also slow, expensive and unpredictable.
The university and Pharos have drawn up a memorandum of understanding (MoU) to use AI technology to identify potential compounds for the rapid development of treatments. The MoU allows Pharos to collaborate with the university’s researchers and gives access to its advanced drug discovery infrastructure.
Data integrity is the term used to describe the accuracy, consistency and reliability of data throughout its lifecycle. In the pharmaceutical/life sciences industries, maintaining data integrity is crucial given its role in making critical decisions that shape outcomes from drugdevelopment to human health.
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