Dr. Natasha Martin, professor and associate chair of the Division of Global Public Health in the Division of Infectious Diseases and Global Public Health at the University of California, San Diego School of Medicine, has been awarded the five-year, $5.6 million Avant-Garde Award from the National Institute on Drug Abuse (NIDA), one of the most prestigious and competitive NIH research awards. This funding will support the development of innovative artificial intelligence tools aimed at improving the public health response to human immunodeficiency virus (HIV), hepatitis C virus (HCV), and overdoses among drug users across the United States.
For too long, the data guiding responses to HIV, hepatitis C, and overdose have lacked drug users’ preferences for local interventions. This project combines a community perspective with cutting-edge AI tools to help health departments better understand local needs, allocate resources more effectively, and ultimately save lives. The project is called ‘AMPLIFY’ because it is designed to amplify the voices of people who use drugs and ensure their priorities shape the interventions provided in their communities. ”
Natasha Martin, DPhil, Professor and Associate Chief of Global Public Health, Department of Infectious Diseases and Global Public Health, University of California, San Diego School of Medicine
The NIDA Avant-Garde Prize supports highly creative scientists pursuing bold, high-impact research that has the potential to transform research into HIV and substance use disorders. The award is awarded to only one to three researchers each year and is designed to support innovative ideas that have the potential to open entirely new areas of scientific research.
Bringing AI to public health decision-making
Despite significant advances in HIV prevention and treatment, including long-acting therapies, the United States continues to face persistent challenges in preventing overdoses among people who use HIV, HCV, and drugs. One obstacle is that public health agencies often lack timely information about the preferences, needs, and behaviors of their target populations, especially in communities with limited surveillance and research infrastructure.
Martin’s project aims to address that gap by creating realistic, community-informed “digital twins” – AI-powered simulations that reflect the intervention preferences and decision-making patterns of drug users. Using data from multiple cohorts and a community-based participatory approach, the research team will train large-scale language models to produce digital twins that can represent people in different regions and settings across the country.
The digital twin is then integrated into advanced models that simulate HIV and HCV infection, overdose, and related health effects. Researchers use these models to test different prevention and treatment strategies before they are implemented in the real world, helping public health leaders identify approaches that provide the greatest benefit at the lowest cost to communities.
“Applying AI to predict drug users’ preferences could be transformative,” Martin said. “Beyond this project, this approach could help us design new health services, identify barriers to care, and tailor interventions to populations whose needs are poorly understood.”
From research to real-world impact
The project builds on years of collaboration between UC San Diego researchers and public health agencies, including work conducted through the Resilient Shield Initiative, a Centers for Disease Control-funded center led by Martin and Elia Aronoff Spencer, MD, professor of medicine at the UC San Diego School of Medicine, that provides outbreak analysis and modeling support to health departments. Through that study, researchers observed that successful strategies in one location may not translate effectively to another, as intervention preferences differ, highlighting the need for a more individualized and locally informed approach.
A central element of the new project is involving people with lived experience of substance use to help develop AI models. Community members play a critical role in shaping how digital twins are designed, tested, and applied, helping to establish safeguards, build trust, and ensure the technology addresses the needs and priorities of the communities it will serve.
The team will ultimately develop an interactive dashboard that public health departments can use to evaluate prevention strategies, evaluate resource allocation options, and more effectively respond to emerging health challenges. The platform is designed to deliver data-driven insights quickly, allowing decision makers to direct limited resources where they can achieve maximum impact.
In addition to Martin, the project includes collaborator Dr. Ravi Goyal from the University of California, San Diego. Eli Aronoff Spencer, MD. Dr. Stephanie Strathdee. Dr. Annick Volquez. Dr. Laramie Smith. Dr. Britt Scarsan. Dr. John Ayers of the Division of Infectious Diseases and Global Public Health at the University of California, San Diego School of Medicine, and Dr. Angela Bazzi of the Herbert Wertheim School of Public Health and Human Longevity Sciences.
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University of California San Diego
