We have all heard of Big Data—capital B, capital D—and the myriad ways the life sciences industry can exploit it. Algorithms can be used to make sense of vast datasets, helping pathologists analyse tissue samples to diagnose disease, or crunching genomic data to predict a person’s risk for aneurysm. But what about “small data?” Can we apply the tools we have used for big data in situations where little or no data are available?
First things first: With the utility of big data, why are biotech companies even thinking about “small data?”
When big data was “all the rage,” many players started out by “exploiting the wealth of large databases, public repositories, patent data, [scientific] literature data”—essentially big datasets that were already out there. This work was important in getting the field started, Andrew Hopkins, CEO of Exscientia, a company using an artificial intelligence-based platform in drug design, told FierceBiotech.
Exscientia is at the forefront of artificial intelligence (AI)-driven drug discovery and design. Frontier IP Group plc (LON:FIPP) as a 5% holding in Exscientia as of 30th June 2016.