When Google's artificial intelligence program known as AlphaGo decisively beat the reigning human champion of the ancient board game of Go in a series of high-profile matches in 2016, it was a watershed moment in the field of machine learning. And while much has been made of impressive feats of artificial intelligence (AI), like AlphaGo and self-driving cars, a lesser known fact is that the same techniques are also helping scientists explore potential new medicines. But Austin Huang, Associate Director and the Biomedical Data Science lead in Pfizer's Genome Sciences and Technologies group in Kendall Square, Cambridge, Massachusetts, explains that "the methods that companies like Google and Facebook use to study large, complex datasets can also be used to help predict disease and possible treatment outcomes in human health data." If the ultimate goal of a self-driving car is to navigate a busy city street, in pharmaceutical research, the goal is to navigate the connections between a potential treatment and its effectiveness in treating a disease. The difficulty though, is that the relationship between biology and disease symptoms in patients is complicated.
Jul-17-2017, 11:20:24 GMT