Can Machine Learning Save Innovation in Pharmaceuticals?

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Have the economics of investing in new drug discovery and development become so unattractive that investment in new drugs will come to a halt? GlaxoSmithKline and other bio-pharmaceutical companies are turning to machine learning as a potential solution to make the drug discovery process more efficient, with the hopes of greatly reducing both the time and cost associated with R&D.

Clinical Trial Recruitment at Acurian in a Digital Age: Lives and Millions of Dollars are at Stake

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Clinical trial delays can result in lost revenue to drug firms of $600k – $8 million per day, not to mention additional lost lives as life-saving treatments wait in the wings . Patient recruitment is the number one cause of clinical trial delays and cost overruns, and Acurian has led the digital transformation of the recruitment process. The Company better identifies and targets appropriate populations through its 17 million patient database and population mapping algorithms [8].