Build an AI-powered health-economic model to quantify the societal value of delaying menopause and improving ovarian healthspan for women's longevity.
The aging of the ovaries is a fundamental biological process that drives menopause, a tipping point in a woman's health that accelerates the risk for major diseases like heart disease, osteoporosis, and dementia.
A woman's age at natural menopause is strongly correlated with her overall longevity and healthspan. Ovaries age faster than nearly every other organ and serve as a 'canary in the coalmine' for overall aging.
Despite this profound impact, research into extending ovarian healthspan is critically underfunded, partly because its full economic and health consequences remain unquantified.
Your mission is to build a tool that synthesizes research findings and calculates the net benefit of delaying menopause, with a focus on those women who experience an earlier-than-average transition.
Using AI to synthesize published literature and public datasets, you will produce a balanced, evidence-based model that quantifies the societal value unlocked by improving ovarian healthspan.
This project sits at the intersection of AI, health economics, and longevity science. Using modern AI tools, your team will systematically review published literature and datasets to build a comprehensive model.
Build a robust pipeline to systematically review scientific literature and build a structured dataset of risks associated with earlier menopause. Your goal is to find studies that link the timing of menopause to specific health outcomes.
Implement a validity scoring system to extract only high-quality data:
Develop a model that calculates the annual change in disease cases per 100,000 women (in the U.S. and/or U.K.) resulting from a therapeutic 5-year delay in menopause. Focus on women undergoing menopause earlier than average (~50-51 years).
Create a version with a variable time scale, allowing for analysis of 2-year, 10-year delays, or other timings.
Your analysis must model both benefits and risks of prolonged estrogen exposure:
Translate your health impact findings into a clear economic case.
Convert the "net cases averted/added" from your model into a dollar value:
A robust, data-driven visualization that demonstrates the net benefits of delaying ovarian aging, including appropriate sourcing and rationalization.
This can take the form of a report, a tool, or an interactive dashboard for educational purposes. This analysis will serve as a compelling justification for investors, policymakers, and researchers to increase focus and funding in women's health.
Example Ideas:
Excellent estimate of the economic costs of women's healthcare gaps, including during menopause. Provides robust framework for calculating economic and productivity losses.
Landmark study on relationship between CVD risk and the menopausal transition, with ample sourcing.
Study on association between age at menopause, bone matter density, and risk of fractures.