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How Google’s using big data and machine-learning to aid drug discovery

From answering heath-related questions in its search results to a fitness data platform for developers, Google is becoming increasingly ingrained in the fabric of our daily health-and-wellbeing habits. But behind the scenes, the Internet giant is also working to expedite the discovery of drugs that could prove vital to finding cures for many human ills. Working with Stanford University’s Pande Lab, Google Research has introduced a paper called “Massively Multitask Networks for Drug Discovery” [PDF], which looks at how using data from a myriad of different sources can better determine which chemical compounds will serve as “effective drug treatments for a variety of diseases.” While the paper itself doesn’t reveal any major medical breakthroughs, it does point to how deep learning can be used to crunch huge data-sets and accelerate drug discovery. Deep learning is a system that involves training systems called artificial neural networks on lots of information derived from key data inputs, and then introducing new information to the mix. You might want to check out our guide to five emerging deep learning startups to watch in 2015.