Building A Translational Research Organization to Decode Female Biology in the Age of AI
AI is poised to compress decades of biomedical discovery into years, but to meet the ambitious timelines in which it could cure disease, we need to focus on one of the central problems faced by AIxBIO: access to the right data. We currently lack biomarkers, endpoints, and sufficient biological data in female health, which will become a huge roadblock to progress. Even as we begin discovering cures for diseases with AI, sex-specific data will be lacking, so the future will be interrupted by this blind spot. Epistemic opacity will take a new meaning.
Ischaemic Heart Disease (IHD), for instance, is among the top causes of DALYs (Disability-Adjusted Life Years) in women in both the Global South (Philippines) and the Global North (USA). DALYs are the main unit by which we measure disease burden, one DALY equals one year of healthy life lost. IHD is driven substantially by hormonal fluctuations and menopause. One can easily find that the downstream effects of not being able to address this condition stem from the fact that the underlying biology of the ovary is poorly understood. By not studying it, we will fail to address a triggering factor for IHD.
To go after this challenge, we propose a new type of organization with an ambitious 5-year field-building plan that involves IP identification, data collection and analysis, and infrastructure to develop robust models to study all diseases related to ovarian health.
Why the ovary? It is a unique organ. By studying it, we can go after the downstream effects of dysregulation in female aging biology, discover more about the microbiome, the ovary-brain connection, and tackle new methods of fertility preservation, something that ultimately benefits humanity at large. Studying ovaries is limited by the fact that collecting biological data is difficult both technically and ethically. By every metric, this is a "handle with extreme care" organ. That is precisely why the new institution meant to close this gap must be built as a public good rather than a siloed private enterprise, existing outside both academia and legacy institutions (even when collaborating with the best academics), so that the sole focus is achieving a goal rather than academic prestige.
Like the Arc Institute and Convergent Research's FROs, we are built to tackle a foundational problem, one that can unlock an area of research with massive ROI. Our solution takes into account the realities of “women’s health” and the types of bets and commitments the market is willing to make on it.
Here is our thesis, alongside a curation of exploratory articles on the subject, on what needs to happen in the next five years to match the predictions of what AI will be able to do - and towards maximal impact.
Read the Thesis