Peer Exchange: AI’s Data Advantage

Pharmaceutical Executive recently brought together a group of experts to discuss the current state of AI within the pharmaceutical industry. The technology has become a major talking point across all industries over the past year-and-a-half, but it has been around for much longer than that. The technology’s ability to collect, sort, analyze, and generate results from large data sets makes it especially interesting for the pharma industry, where experts often find themselves limited by the massive amounts of data they must work with.

The panel includes Ryan Abbott, MD, JD, MTOM, PhD, professor of law and health sciences at the University of Surrey School of Law; Thomas Lau, engagement lead at Quilt.AI; and Robert Wells, healthcare regulatory attorney, shareholder at Baker Donelson. Each expert brought their unique perspective to a wide-ranging conversation.

AI requires extensive amounts of data to work. In order to produce accurate and reliable results, the AI needs large data sets to work from. For the pharmaceutical industry, this is great news, as researchers are constantly creating mountains of data. However, this data usually includes private medical information and other pieces of proprietary data that companies may not be comfortable handing over to an AI system, especially one that isn’t an in-house system.

Despite this, the most exciting aspect of AI for the pharma industry is its ability to quickly sort and analyze massive amounts of data. Due to the nature of the industry and the work that does, data often isn’t collected in a normalized manner. This means that researchers often find themselves trying to navigate huge amounts of data that aren’t easily compatible.

AI is able to solve this problem. When discussing AI in pharma, this is often the area with the most excitement. The technology has the ability to free up researchers’ time so that they can focus on analyzing the data and moving their research forward.