The National Institutes of Health (NIH) has awarded an initial $4.6 million grant to a multi-university research team to develop computational tools that aim to transform how medications are developed and prescribed for women's health. This award is the first installment of up to $12.8 million over three years and is part of the larger Computational Modeling of Hormone Homeostasis Initiative, a national program jointly supported by the NIH Office of Research on Women’s Health and the Division of Program Coordination, Planning and Strategic Initiatives. The broader initiative will distribute a total of $21 million in awards; the specific award number reported is 1OT2OD042764.
The project is led by Teresa K. Woodruff, PhD, president emerita of Michigan State University (MSU) and an MSU Research Foundation Distinguished Professor. Investigators from Rutgers, Emory, Tulane, University of Colorado Anschutz, University of Michigan and University of Utah are collaborating with the MSU team. The article identifies additional researchers from MSU and partner institutions by name and role.
The team highlights that women undergo significant hormonal transitions across the life course — puberty, pregnancy, menstrual cycles, use of contraception, menopause and hormone replacement therapy — and that hormone levels also fluctuate day-to-day during reproductive years. These dynamic changes create an endocrine environment that differs from that of men and can alter how medicines are processed and how they act, including efficacy and side-effect profiles.
Clinical trials frequently do not account for these sex-specific and life-stage–specific hormone dynamics. According to Endocrine Society President Nanette Santoro, MD, and project leadership quoted in the source, this oversight has contributed to treatments that may be less effective or associated with more severe adverse effects for women.
The team will use advanced computational and modeling frameworks to achieve five primary goals described in the source article:
Use artificial intelligence to digitize and organize more than 40 years of hormone research, creating a free, publicly accessible database.
Develop a standard computer model that represents a normal 28-day menstrual cycle and how hormones regulate key organs involved in nutrient processing (for example, liver, muscle and adipose tissue).
Expand the standard digital model with real-world patient data to represent diverse groups, including women in menopause, women taking hormonal contraception, and those with conditions such as diabetes and obesity.
Inform, test and verify computational predictions using human-relevant three-dimensional tissue models and mini organoids (for example, liver, muscle and ovarian tissue) grown in the laboratory.
Produce personalized treatment tools to predict medication responses and optimal dosing for specific drugs (the source lists metformin, insulin and GLP-1 agents as examples) to help clinicians prescribe safer and more effective regimens for female patients.
The initiative will pair in silico modeling with in vitro validation. The team plans to use 3D human tissue constructs and organoids to test and verify computer-generated predictions. These laboratory models are intended to provide human-relevant experimental data that inform and refine the computational frameworks described above.
When complete, the project will deliver an open-access computer platform designed to help healthcare providers anticipate drug efficacy, prevent harmful side effects and tailor prescriptions for women across different reproductive stages. The article states that results will also inform NIH guidelines, national safety standards and clinical protocols for testing new therapies. Tulane University professor Hao Zhu is quoted describing the effort as systematically extracting and curating decades of fragmented public research and clinical data to create structured, actionable resources that advance precision health for women.
Named contributors include Teresa K. Woodruff and Endocrine Society leaders quoted in the article, plus additional investigators: Sudin Bhattacharya, Brian Johnson, Rance Nault, Timothy Zacharewski (MSU); Shuo Xiao and Jiyang Zhang (Rutgers); Ariella Shikanov (University of Michigan); Corrine Welt (University of Utah); Mary Sammel (University of Colorado Anschutz); and Hao Zhu (Tulane). The source states that all computer models and data produced through this NIH initiative will be freely available to researchers and healthcare professionals worldwide upon completion.
The article indicates that the content was provided by Michigan State University’s MSU Newsroom. The details above reflect the facts and quotations reported by that source; no additional outcomes, timelines or unpublished data were reported beyond what the source presented.