NIH Backs $12.8M Multi-University Project to Model How Female Hormones Alter Drug Processing
核心洞察
The NIH has awarded a first installment of $4.6 million, part of up to $12.8 million over three years, to a multi-university team modeling drug-hormone interactions in women.
Thirteen researchers from Michigan State, Rutgers, Emory, Tulane, and other institutions will build computational models integrating age and reproductive cycle stage into drug predictions.
The project targets metabolic drugs such as metformin, insulin, and GLP-1 agents, whose effects may vary with shifting female hormone levels.
The National Institutes of Health has awarded a multi-university research team a first installment of $4.6 million — part of an award worth up to $12.8 million over three years — to build computational models predicting how a woman's shifting hormone levels affect how medicines move through and act within the body. The project, led by Michigan State University with Rutgers University and collaborators at Emory, Tulane, University of Colorado Anschutz (搜索), University of Michigan and University of Utah, aims to correct a long-standing gap in how drugs are developed and prescribed for women.
Clinical trials often fail to account for the unique ways female hormones change throughout life — during menstrual cycles, pregnancy, birth control use, menopause and hormone replacement therapy. According to the project's investigators, this oversight can lead to treatments that are less effective or cause more severe side effects in women than in men.
"Developing computational models that provide insights into women's health — including the consequences of disease, efficacy and side effects of medicines — and integrate age and reproductive cycle stage is a moon shot," said Teresa K. Woodruff, the lead investigator on the project and president emerita of MSU. "Our world-class team is taking on this project to enable a generation of healthier women."
A National Initiative in Hormone Homeostasis
The award is part of the Computational Modeling of Hormone Homeostasis Initiative, a joint effort by the NIH Office of Research on Women's Health and the Division of Program Coordination, Planning and Strategic Initiatives. The program is leveraging advances in computer modeling to deepen understanding of sex-specific hormonal biology, with a total of $21 million being awarded to expand national research. The award number is 1OT2OD042764.
Thirteen researchers are collaborating on the project. "Empowered by AI, novel assays and legacy human data, we will develop mechanistically based computational models of female physiology that can make translational, quantitative predictions for women's responses to metabolic therapies," said Qiang Zhang, associate professor in the Rollins School of Public Health at Emory University.
Five Goals Spanning Data, Modeling and Validation
The team will use advanced computational and modeling frameworks to accomplish five main goals:
- Artificial intelligence will digitize and organize over 40 years of hormone research data, creating a free, publicly accessible database.
- A standard computer model will map out a normal 28-day menstrual cycle alongside how key organs — such as the liver, muscle and fat tissues — are regulated by hormones to process nutrients.
- Real-world patient data will expand the standard digital model to account for groups such as women going through menopause or taking birth control, and for specific health conditions like diabetes and obesity.
- Lab-grown organ testing will use human-relevant three-dimensional tissue models and mini lab-grown organoids, including liver, muscle and ovarian tissue, to inform, test and verify the computer predictions.
- Personalized treatment tools for specific medications, including metformin, insulin and GLP-1 drugs, will be predicted by the computer models to help doctors prescribe ideal doses and avoid dangerous side effects.
"We'll supplement the project's computer models with lab-grown biological models, known as new approach methodologies, or NAMs, that mimic hormone levels in multiple organs during key moments in women, like ovulation, menstruation, pregnancy, menopause or the onset of a hormone-altering disease," said Shuo Xiao, associate professor in the Department of Pharmacology and Toxicology at the Ernest Mario School of Pharmacy at Rutgers. "We'll expose each of these wet-lab NAM models to common metabolic drugs and measure responses to inform the development of computer models that can help improve women's medication use." Jiyang Zhang, research assistant professor at the Rutgers school, is also on the team.
Metabolic Disease and the Case for Precision Dosing
Metabolic conditions such as obesity (搜索), type 2 diabetes (搜索), cholesterol imbalances and thyroid disorders (搜索) are widespread in women and frequently co-occur with reproductive conditions like polyendocrine metabolic ovarian syndrome (搜索), or PMOS. Because energy metabolism and female reproductive hormones directly influence each other, widely prescribed drugs — including insulin and GLP-1 weight-loss and diabetes medications — can produce different results in women depending on their individual hormone levels.
"Because female hormone levels are constantly shifting, precision medicine allows us to map out these complex interactions," Woodruff said. "This NIH-backed initiative will create the first computationally driven clinical tool designed to guide medical care across every stage of a woman's life."
Nanette Santoro, E. Stewart Taylor Professor in the Department of Obstetrics and Gynecology at the University of Colorado Anschutz (搜索) and president of the Endocrine Society, framed the hormonal variability at stake: "Women experience large shifts in reproductive hormones at several points in their lifespan: puberty, pregnancy and menopause. During reproductive years, women also undergo profound day-to-day changes in reproductive hormone levels, giving them a markedly different endocrine backdrop than men. Using state-of-the-art computational technology to examine how these changes interact with commonly used medications is a critical pathway toward supporting life-course women's health."
Dismantling a Historic Data Gap
A central aim of the effort is to consolidate decades of fragmented research into structured resources. "By systematically and automatically extracting and curating decades of fragmented public research and clinical data, we are finally dismantling a historic data gap in this research project," said Hao Zhu, professor of biomedical informatics and genomics at the Tulane University School of Medicine. "Transforming these raw, disparate datasets into structured, actionable insights enables modelers and informaticians to accelerate precision health and disease models tailored specifically to women's biology. This critical data-driven computational infrastructure elevates women's health from an understudied niche to a central scientific priority, paving the way for more equitable, life-saving outcomes worldwide."
The project also incorporates engineered human tissue models to validate computational predictions. "This award allows us to bring new approach methodologies directly into the modeling loop," a team member noted. "We will incorporate engineered human ovarian follicles and tissues that generate dynamic hormone and secretome data through measurements taken over time, under conditions that mimic a woman's changing endocrine state. This data will validate, enrich, and optimize hormone models built from clinical data."
Open-Access Platform and Regulatory Reach
The final open-access computer platform is intended to give healthcare providers practical tools to anticipate drug efficacies, prevent harmful side effects and tailor prescriptions for female patients. The findings will directly inform NIH guidelines, national safety standards and clinical protocols for testing new treatments.
"Sharing open and reproducible computational models extends the impact of this team's work, providing resources that the broader research community can reuse to further advance women's health research," said Rance Nault, assistant professor in the Department of Pharmacology and Toxicology, Institute for Integrative Toxicology and College of Veterinary Medicine at MSU.
Brian P. Johnson, assistant professor in the MSU Department of Pharmacology and Toxicology and Department of Biomedical Engineering, added: "Some of the most important challenges in women's health are also among the most complex. This project unites researchers with expertise spanning hormone biology, engineering and computational modeling to tackle questions that no single field could solve alone. Together, we can make these complex biological systems more approachable and generate new insights that ultimately benefit women's health."
All computer models and data produced through the NIH initiative will be freely available to researchers and healthcare professionals worldwide upon completion. Additional researchers on the team include Sudin Bhattacharya, Brian Johnson, Rance Nault and Timothy Zacharewski from MSU; Shuo Xiao and Jiyang Zhang from Rutgers; Ariella Shikanov from the University of Michigan; Corrine Welt from the University of Utah; and Mary Sammel from the University of Colorado Anschutz (搜索).