Anastasia Christianson on Pfizer’s Approach to AI, ML, and the Digital Age

By Allison Proffitt   

May 4, 2023 | At Pfizer, AI plays a key role in every step of the drug discovery process, Anastasia Christianson, Global Head of AI, ML, Analytics, and Data at Pfizer, tells Bio-Team co-founder Stan Gloss on the latest episode of the Trends from the Trenches podcast.  

And she means it. Christianson lists the areas at Pfizer where AI is in play and for which she has AI/ML responsibility: research and discovery, clinical development, manufacturing supply chain, commercial, medical affairs, human resources, financial departments, and more. Pfizer doesn’t have a digital strategy, Christianson says, turning that buzzword on its head. “Instead, we have a business strategy for a digital world… This is our viewpoint… What we do from a digital perspective is to look at opportunities to support and accelerate our business priorities.”   

Editor’s Note: Christianson will be the opening keynote at the 2023 Bio-IT World Conference & Expo, May 16-18, 2023, in Boston.  

Christianson joined Pfizer last year, and she was impressed from the beginning with the shape of Pfizer’s data, she said. “It was actually in pretty good shape; not as siloed as one might think.” Pfizer had accelerated its AI capabilities significantly during the pandemic, Christianson says, “when we were looking to use our data most effectively and simulate what the next step is.”   

Of course the work is never done. Now, she says, “Our goal has been to ensure that we have FAIR data: findable, accessible, interoperable and reusable.” That FAIR-ification process began function-by-function, but Christianson is also thinking about it across the enterprise. “One of the opportunities that we have is the fact that we work across the enterprise. We’re not the only ones who are data scientists or AI/ML—by any stretch of the imagination,” she said. “Of course we have embedded data scientists and embedded data engineers and embedded AI experts. That means that we partner very well, and we have partners that can help us to get to where we need to get to.”   

With every group within Pfizer using data science, the questions facing these groups and the data complexity are different. Manufacturing, for example, is usually ahead of everything else at making the best use of high-quality data and model-based methods, Christianson said. “Some of the problems that they tackle are definitely amenable to advanced analytic methods.”  

But Christianson says one of the most fun parts of her job is getting to shepherd lessons learned across different company areas. “We’re always looking at the learning from one part of the organization to another part of the organization. That’s what I really enjoy about this role.”  

Christianson sees great value that data science, AI, and ML can deliver at every step of the process: early discovery, identifying potential targets for disease intervention, designing the best therapeutic agent (be it small molecule, large molecule, antibody, or cell therapy), designing and executing clinical trials, diversifying clinical trial populations and geographies, distribution of products to healthcare providers and patients, as well as support functions including preventing regrettable team losses and identifying team members ready for a new challenge.  

Across every spectrum, the biggest lesson learned from applying AI and data science, Christianson says, is the agility afforded by data. Data and technology can help you work faster, Christianson says, by identifying and eliminating obstacles. “The mindset makes a lot of difference,” she says, “thinking about how to remove obstacles and when you need to bring others in, how to work in a larger team, a high-performing team, and be prepared for anything.”