Stronger together: A convergence of minds and data

It’s the early 1990s. Phil Hajduk is hunkered down in a lab in North Chicago, Illinois, where he’s focused on developing small molecule medicines that target cancer cells. It’s trial and error, with a dearth of data for this trained chemist to pore over and leverage for new technologies.

Across the state line in Wisconsin, Howard Jacob is serving as the founding director of the Human and Molecular Genetics Center at the Medical College of Wisconsin. During his nearly 20-year tenure at the university, he will be part of the first team ever to use genome sequencing, or a full DNA blueprint, to diagnose and treat a patient.

Little did they know at the time, but these two PhDs working in different states on different types of science would end up crossing paths decades later. And not just cross paths, but bring their disciplines together to lead one of the largest data initiatives in the biotech industry.

Flash forward to 2021: Hajduk has just celebrated 28 years advancing science at AbbVie, but he’s graduated from the bench and now leads the company’s IT information research team. In an office across campus, Jacob is marking four years at AbbVie overseeing genomics research and data integration.

They liken their relationship to the same way they view science data: seemingly disparate and unrelated but in reality, different yet complementary pieces of a bigger puzzle. This has become apparent over the past year, as Hajduk and Jacob came together to tackle the next piece of the digital health revolution: data convergence.

Simply put, convergence is bringing data together. But why is this important for a biopharma company?

“The challenge many industries face, including ours, is that it’s difficult to pull out knowledge as human beings,” Jacob says. “We’re limited by how we can process mass amounts of data, so instead we’re changing everything about how we leverage and generate knowledge around data.”

Data mining, machine learning, artificial intelligence. The promise of a digital health care revolution has been in the headlines for years, across industries. What’s so different now?

Well, now there’s enough data. And more importantly, a vision and commitment from AbbVie leadership to double down and create a better data infrastructure and enable knowledge sharing. The ultimate goal: to better treat disease and manage health care more broadly.

This commitment sparked a collaboration between every part of the company’s science organization that maintains, manages and analyzes data (read: all of them). Early discovery science. Chemistry. Genomics. Health economics & outcomes research team. Patient safety. Clinical trials. And on and on.

Each of these groups have built IT strategies, databases and processes that enable how they work. Now, the walls have come down. The past year, leaders focused on building the foundation, leaning on behind-the-scenes data engineering to create and populate a single internal platform with strong governance.

That’s important, but the real value comes a few steps after you bring the parts together, Hajduk says, because mass amounts of data alone won’t help scientists make better decisions.

“What we're building is distinct. It's not a data swamp. It's a knowledge platform,” he says. “Not only do we bring the data in and harmonize it, but we actually sit down with the subject matter experts and ask, what do those data mean? What’s the level of interpretation we can put on this data, and how do we scale that to our entire scientific community?”