Data Science @ Moderna: Accelerating Regulatory Communication with Natural Language Processing


Advanced AI and machine learning methods were critical to Moderna’s ability to rapidly produce one of the first mRNA COVID vaccines at the height of the pandemic. As the first “Digital Biotech Company”, Moderna is working to expand the use of such methods to address problems across the enterprise, from pre-clinical research to clinical trial operations to regulatory affairs and more. In this presentation, I will discuss some of the ways Moderna has embedded AI-fueled technology into our business processes. We will explore one solution for Regulatory Operations in detail that uses natural language processing to accelerate our communications with health authority organizations. The first release of this solution, called RegBot, has sped up our intake and archiving of health authority questions (HAQs) by approximately 20x. Planned releases incorporate generative models to draft responses to HAQs for our regulatory experts to review and edit, further speeding up our regulatory correspondence. By using AI to make regulatory communications more efficient, we can accelerate the delivery of powerful mRNA medicines to patients.


Rebecca Vislay-Wade is a Principal Data Scientist at Moderna, where she leads a team of scientists developing AI applications for clinical operations, regulatory science, and pharmacovigilance. Prior to Moderna, she worked as Senior Research Data Scientist at Highmark Health. Rebecca holds a PhD in biochemistry from Harvard University and did postdoctoral work in neuroscience at the NIH and Children’s National Medical Center in Washington, DC. She currently lives in the Boston area with her family.

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