A space odyssey for new antibiotics: MIT's machine learning approach
Drug development is complex, expensive and comes with lousy odds of success — but in most cases, if you make it across the finish line brandishing a product with an edge (and play your cards right) it can be a lucrative endeavor.
As it stands, the antibiotic market is cursed — it harbors the stink of multiple bankruptcies, a dearth of innovation, and is consequently barely whetting the voracious appetites of big pharma or venture capitalists. Enter artificial intelligence — the biopharma industry’s cure-all for the pesky process of making a therapeutic, including data mining, drug discovery, optimal drug delivery, and addressable patient population.
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