
PNNL Chief Data Scientist Participates in the National Academies Forum Workshop
Lauren Charles, chief data scientist at Pacific Northwest National Laboratory (PNNL), showcased the vital research coming out of her program at The National Academies Forum workshop in Washington, D.C., January 15–16, 2025.
The forum’s workshop, titled “Understanding the Introduction of Pathogens into Humans – Preventing Patient Zero,” delved into the emergence and transmission of pathogens, focusing on close contact with pathogens, human-animal interactions, and laboratory research involving the propagation or manipulation of pathogens.
Ultimately, it underscored the critical need to bolster biosecurity in these interactions and environments. Throughout the workshop, thought leaders discussed how policy structures, emerging technologies, and actionable research can strengthen biosecurity and pave the way for a healthier future for all.
Charles is a veterinarian with a diverse background that includes a bachelor’s degree in mathematics, a master’s degree in plant pathology, and a PhD focused on the impacts of climate and weather on wildlife movements and zoonotic transmission. She delivered her presentation on the AI-Driven One Health Security program during the panel entitled, “Forecasting, Surveillance, and Early Warning.”
She explained how the motivation for her current program involving multiple data scientists and engineers focused on integrating multimodal data into complex models to advance biosurveillance and early warning was “strengthened by the pandemic outbreak, which highlighted the need for change in the way we approached health security due to siloed information, limited collaboration, and impeded data sharing."
Underscoring current and past pathogenic threats and the ongoing issues with detection and response, Charles emphasized the intimate connection between human, animal, plant, and environmental health.
“We have discovered that AI methods can actually detangle these intricacies, which are nearly impossible for our minds or traditional methods to comprehend,” she said.
By using AI to analyze complex data relationships, the program has effectively enhanced the ability to monitor, predict, and mitigate health risks. Charles emphasized that one of the major reasons for the program’s success has been the focus on “building trusted partnerships with data providers and federal sponsors.”
Charles closed by highlighting a few of the tools they have developed, including Biofeeds, “a data harvester that pulls in hundreds of thousands of open-source news and reports focused on identifying health threats to humans, animals, and plants,” and MedINT, a “platform for medical intelligence that assists medical operations through the early warning of health threats.” Through the development of such tools, her program increases the likelihood of improving early warning systems and preventing health threats from escalating into pandemics.
To learn more about the workshop, listen to Charles’s full presentation, or view her slides, visit here.
One Health Action Collaborative
It is through her expertise in applying emerging technologies that Charles was extended the opportunity to join the One Health Action Collaborative. The collaborative is supported by the Forum on Microbial Threats at the National Academies of Sciences, Engineering, and Medicine. In this position, Charles will collaborate with other experts on research related to human, plant, and animal health to explore One Health strategies in the field, leveraging the various disciplines and integration of healthcare systems, disease surveillance networks, and public awareness.
Expected contributions by Charles include One Health Action Collaborative-related meetings and delivering on key objectives through publications and webinars aligned with her specific expertise and interests. Her actions aim to further educate and implement the One Health approach to enhance prediction, detection, and responses to emerging infectious disease threats and ultimately improve strategies to save lives.

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