Researchers from Rutgers, Emory, Tulane, University of Colorado Anschutz, University of Michigan and University of Utah are collaborating with the MSU team to accomplish this goal, which the lead scientist describes as a moon shot.
U-M BME’s Ariella Shikanov, Professor, Biomedical Engineering and Obstetrics and Gynecology, is part of a multi-university team led by Michigan State University and backed by a new $4.6 million award from the National Institutes of Health, or NIH, to launch a novel project to transform how medications are developed and prescribed for women. This is the first installment of an award worth up to $12.8 million over three years. Researchers from Rutgers, Emory, Tulane, University of Colorado Anschutz, University of Michigan and University of Utah are collaborating with the MSU team to accomplish this goal, which the lead scientist describes as a moon shot.
Clinical trials often fail to account for the unique ways female hormones change throughout life — such as during menstrual cycles, pregnancy, birth control use, menopause and hormone replacement therapy. This oversight can lead to treatments that are less effective or cause more severe side effects in women than in men.
To bridge this gap, 13 researchers are collaborating to build advanced computer models that will predict how a woman’s natural hormonal changes affect how medicines move through and act within the body. Their findings are expected to result in stronger research studies, advances in precision medicine and better real-world outcomes for women.
“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 this project, president emerita of MSU and an MSU Research Foundation Distinguished Professor in the Department of Obstetrics, Gynecology and Reproductive Biology at the MSU College of Human Medicine and in the Department of Biomedical Engineering at MSU’s College of Engineering. “Our world-class team is taking on this project to enable a generation of healthier women.”
This award is part of a national program, the Computational Modeling of Hormone Homeostasis Initiative, which is a joint effort by the NIH Office of Research on Women’s Health and the Division of Program Coordination, Planning and Strategic Initiatives to leverage advancements in computer modeling to deepen the understanding of sex-specific hormonal biology. A total of $21 million is being awarded to expand national research and high-impact science. The award number is 1OT2OD042764.
Research teams across the country will be developing the next generation of human-based data-driven tools that advance understanding of hormone-related health and improve care for people and communities.
“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
Closing the gap in women’s metabolic health
Metabolic conditions such as obesity, type 2 diabetes, cholesterol imbalances and thyroid disorders are widespread in women. They also frequently co-occur with reproductive conditions like polyendocrine metabolic ovarian syndrome, 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.”
The team will use advanced computational and modeling frameworks to accomplish five main goals:
Public health impact
The final open-access computer platform will give healthcare providers practical tools to anticipate drug efficacies, prevent harmful side effects and tailor prescriptions for female patients.
“Women experience large shifts in reproductive hormones at several points in their lifespan: puberty, pregnancy and menopause,” said Nanette Santoro, E. Stewart Taylor Professor, Department of Obstetrics and Gynecology at the University of Colorado Anschutz and president of the Endocrine Society. “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.”
Additionally, the findings will directly inform NIH guidelines, national safety standards and clinical protocols for testing new treatments.
“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.”
All computer models and data produced through this NIH initiative will be freely available to researchers and healthcare professionals worldwide upon completion.
Additional researchers include Sudin Bhattacharya, Brian Johnson, Rance Nault and Timothy Zacharewski from MSU, Shuo Xiao and Jiyang Zhang from Rutgers University, Ariella Shikanov from the University of Michigan, Corrine Welt from the University of Utah, and Mary Sammel from the University of Colorado Anschutz.
Additional researcher remarks:
“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.”
—Rance Nault, assistant professor, Department of Pharmacology and Toxicology, Institute for Integrative Toxicology and College of Veterinary Medicine at MSU
“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.”
—Brian P. Johnson, assistant professor in the MSU Department of Pharmacology and Toxicology and Department of Biomedical Engineering
“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. 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.”
—Shuo Xiao, associate professor, and Jiyang Zhang, research assistant professor, in the Department of Pharmacology and Toxicology at the Ernest Mario School of Pharmacy at Rutgers University
“This award allows us to bring new approach methodologies directly into the modeling loop. 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.”
—Ariella Shikanov, professor in the Department of Biomedical Engineering at University of Michigan