Over the past few decades, data generation has veritably exploded. However, the'Big Data paradigm' is not so much concerned with the volume of that data, but how businesses and, indeed, industries can derive meaningful insights from what has become a glut of information. With the currently popular approach to artificial intelligence (AI) focussing on the Big Data paradigm, also, pharmaphorum spoke with Adityo Prakash, CEO of Verseon, about the whys and wherefores, delving deeper into the processes for dealing with the current mountain of data and how it can be generated, as well as the purposes for which it can be dealt with constructively, and efficiently. "The fundamental underlying assumption is that an enormous amount of data is available to teach an AI programme how to handle the problem at hand," Prakash began. However, he explained, "the number of known examples to train AI is at least many thousands of times larger than the number of variables or features to be tracked."

Since the rise of modern medicine, the pharmaceuticals industry has relied on the brainpower of chemists and biologists to discover and develop new drugs. Their painstaking work has brought about dramatic advances in human health yet the slow pace of progress has prompted a search for new approaches. As in so many areas, some of the most promising ideas are coming from Silicon Valley. In the era of big data and artificial intelligence, could computer algorithms provide a short-cut to the next generation of medical breakthroughs? Among the pioneers of computer-based drug discovery is a Californian company called Verseon.