AI and the COVID-19 Vaccine: Moderna’s Dave Johnson

**Sam Ransbotham** (0:02)
What role did artificial intelligence have in helping combat the coronavirus pandemic? Find out today when we talk with an innovative company that used artificial intelligence to help solve the critical problems society faced in the last year.
Welcome to Me, Myself, and AI, a podcast on artificial intelligence in business. Each episode, we introduce you to someone innovating with AI. I'm Sam Ransbotham, Professor of Information Systems at Boston College. I'm also the Guest Editor for the AI and Business Strategy Big Idea Program at MIT Sloan Management Review.

**Shervin Khodabandeh** (0:36)
And I'm Shervin Khodabandeh, Senior Partner with BCG, and I co-lead BCG's AI practice in North America. And together, MIT Smr and BCG have been researching AI for five years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities across the organization and really transform the way organizations operate.

**Sam Ransbotham** (1:05)
Today we're talking with Dave Johnson, Chief Data and an Artificial Intelligence Officer at Moderna.
Dave, thanks for joining us. Welcome.

**Dave Johnson** (1:13)
Thanks, guys, for having me.

**Sam Ransbotham** (1:14)
Can you describe your current role at Moderna?

**Dave Johnson** (1:18)
I'm Chief Data and AI Officer at Moderna. In my role, I'm responsible for all of our enterprise data functions, from data engineering to data science integration. And I also manage the software engineering team, building, you know, unique custom applications to curate and create new data sets, but also to then take those AI models that are created and build them into processes.
So it's kind of end-to-end, everything to actually deploy an AI model, to build, deploy, and put an AI model into production.

**Sam Ransbotham** (1:45)
How did you end up in that role? I know you have physics in your background. That's not...
I didn't hear any physics in what you just said.

**Dave Johnson** (1:52)
Yeah, no, it's a good point. So I have my PhD in what's called information physics, which is a field closely related to data science, actually. It's about the foundations of Bayesian statistics and information theory, a lot of what is involved in data science. My particular research was in applying that to a framework that derives quantum mechanics from the rules of information theory. So that part, you're right, is not particularly relevant to my day-to-day job. But the information theory part and the Bayesian stats is completely on target for what I do.
In addition to that, I spent many years doing independent consulting and kind of a software engineering data science capacity. And when I finished my PhD, you know, I realized academia wasn't really for me. I wanted to do applications. And I ended up with a consulting firm doing work for large pharmaceutical companies. So I spent a number of years doing that. And it turned out to be a real great marriage of my skill sets, you know, understanding of science, understanding of data, understanding of, you know, software engineering. And so I did one project in particular for a number of years in research at a pharmaceutical company around capturing data in a structured, useful way in the preclinical space in order to feed into kind of advanced data and advanced models. So very much what I'm doing today. And about seven years ago, I moved over to Moderna. At the time, we were a preclinical stage company and the big challenge we had was producing enough small scale mRNA to run our experiments.
And what we were really trying to do is accelerate the pace of research so we can get as many drugs in the clinic as quickly as possible.
And one of the big bottlenecks was having this mRNA for the scientists to run tests in.
And so what we did is we put in place a ton of robotic automation, put in place a lot of digital systems and process automation and AI algorithms as well. And what went from maybe like about 30 mRNAs manually produced in a given month to a capacity of about a thousand in a month period. So without significantly more resources and much better consistency and quality and so on. So then I just kind of from there grew with the company and grew into this role that we have now where I'm applying those same ideas to the broader enterprise.

**Shervin Khodabandeh** (4:02)
That's great, Dave. Can you comment a bit on the spectrum of use cases that AI is being applied to here and is really making a difference?

**Dave Johnson** (4:13)
For us, what we've seen a lot of is in the research space and particularly in Moderna, that's been because that's where we digitized early.