New Skills for Pharmacovigilance

Emerging Professionals Must Understand Data Science and AI​

“The number one priority that I have at the moment is thinking about the PV professional of the future,” said Richard Wolf, Head of Pv Operations at CSL Behring. He joined the Safety Signals podcast for a lively discussion about improving pharmacovigilance operations through technological innovation.

According to Mr. Wolf, three things are driving innovation in pharmacovigilance: case volume increases, cost pressures on operations, and differing regulator expectations worldwide.

To advance operational efficiency and effectiveness in the context of these drivers, Mr. Wolf expects technologies such as robotic process automation, artificial intelligence, and natural language processing to gain a foothold in pharmacovigilance within the next three to five years.

He also expects case processing technologies to evolve fairly quickly, as small, agile competitors put pressure on dominant players to do better. Mr. Wolf said that operations managers and pharma CEOs dream of the day when touchless case processing becomes a reality.

For Mr. Wolf, the most difficult piece of the puzzle is intake, “because adverse event information comes in so many different forms, from so many different places and in so many different languages…How can you standardize that point of intake to the degree it’s necessary in order for it to move through the safety system?”

Balancing Real-World Evidence with Traditional Case Processing

Mr. Wolf said that he’ll keep investing in case processing improvements until real-world evidence becomes robust enough to replace it. For quite a while now, he’s been encouraging his team to learn “what’s possible with [AI], to understand where robotic process automation would make more sense, or how natural language processing can help with coding, for example.”

Mr. Wolf expects data sciences to become a core competency within safety organizations, “as opposed to something that’s nice or interesting to have.” This will be critical for consolidating data from EMR, clinical studies, and post marketing so that clinical, safety, and epidemiology leaders can work together to “concentrate all of our efforts on patient safety and making the best benefit risk profile we can for our products.”

This post is based on an episode of the Safety Signals podcast. To hear more, check us out on Apple Podcasts, Spotify, or on our website.

The views of the hosts and guests featured on Safety Signals are their own and do not necessarily reflect the views of Saama or the individual companies for which the guests may work.