At this point, wearable devices - such as the Oura Ring, Apple Watch, WHOOP - have become so commonplace, you might not even notice them anymore. Your friends wear them. Your coworkers wear them. Your sisters wear them. It seems like maybe … everyone does these days? While I’ve used my Apple Watch mainly for tracking my daily steps (10K, rain or shine), the use case for these wearables is increasingly powerful. This past year, my friend’s Oura Ring tipped her off that she might be pregnant (to satisfy your curiosity - yes, she was!).  

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At this point, you may have seen a few women in your life decide to swap their IUDs and birth control pills in favor of mobile apps (Natural Cycles, Flo). Yes, you heard me right - apps. Ever since Natural Cycles received FDA clearance as a method of contraception (after a clinical study with 15,570 women showed a 93% effective rate), we’ve seen a major shift in the reliance on data and algorithms for personalized health care. In July 2024, the fertility tracking app Flo raised $200M at a $1Bn+ valuation, largely driven by the value of its massive dataset from 70+ million monthly active users. If anyone in your life is trying to conceive, you may even be familiar with the rise of at-home hormone testing & tracking devices (Mira, Inito, to name a few) which draw on physical data + user data to predict cycle behavior. A big thanks to Mira for helping me conceive my now 8-month old daughter, Harper. 

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The rapid consumer adoption of tech enabled solutions have generated novel datasets and insights that are driving new personalized care solutions for women. 

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This trend has also manifested itself in the rise of data-focused key opinion leaders, such as Emily Oster (and her best-seller Expecting Better). Emily took her PhD in economics and pointed it at women’s health, reviewing and analyzing the data from studies to guide pregnant women (and parents) in navigating a wide range of decisions (from “can I have that sushi roll” to “is an amniocentesis necessary”).

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Thankfully, the data that Emily Osters and others can draw from is growing. Why? First, an important ban was lifted in 1993 that prevented women of child-bearing age from participating in clinical trials. Second, with growing public awareness of women’s health, more research dollars have been pointed at understanding female biology specifically (examples: NIH Women’s Health Initiative (WHI) and The Million Women Study). Finally. This research is providing a better understanding of female-specific health conditions. Why does this matter? The biological understanding is critical to unlocking new treatments and solutions for women. We’ve already seen some cool exciting things happen in the past few years: studies uncovered a hormone responsible for extreme morning sickness (hyperemesis gravidarum), the FDA approved approved the first blood test to predict which pregnant patients are at risk for developing pre-eclampsia, and the first postpartum depression drug Zurzuvae hit the market. 

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Capital is following suit in a big way. The public and private sectors are enthusiastic. ARPA-H launched a $100M “Sprint for Women’s Health and First Lady Jill Biden announced a $500M annual commitment from the DoD for women’s health research. Investment in women’s health companies has surged in recent years, rising from ~$400M in 2018 to ~$3.3Bn in 2022 (albeit still only 2% of overall health care VC investment (BCG)). Firms like Avestria Ventures, SteelSky Ventures, FemHealth Ventures and Pivotal Ventures are dedicating entire pools of capital to women’s health. 

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But there is a lot going on behind the scenes - the bio and deep tech scenes - that most people aren’t seeing that has the power to truly transform this space. 

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In the biotech world, advances in genetic sequencing and lab-grown human tissue modeling have vastly improved our understanding of female biology. Why is this? Two important things happened alongside the research and dataset gains: (1) things got cheaper and (2) tools got better. Since 2000, the costs of reading and writing DNA have dramatically declined. The cost to sequence a human genome went from $1Bn+ to less than $1K. At the same time, advances in AI, ML, and automation dramatically improved methods for designing with DNA - making it faster, cheaper, and more sophisticated.  

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How has this translated? Gameto has designed novel ovarian cell lines (i.e. lab-grown cells for research) to drive therapeutic innovation across the IVF, menopause, and ovarian disease markets. Oviva Therapeutics is using advanced genetic engineering to create a recombinant form of anti-mullerian hormone (AMH), which could prevent ovarian decline and delay the onset of menopause.  Matrubials is developing antimicrobial peptides (tiny proteins) from breast milk (!) to treat bacterial vaginosis (which, low key, affects 1/3 of women). Concerto Biosciences is using its high throughput platform and AI models to identify the right combinations of microbes to more effectively treat yeast infections (it’s about time!). Axena Health has a FDA cleared and insurance-reimbursed pelvic health treatment. 

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Today, we can not only detect, predict and model using improved data and technology but we can now treat, address, and support using advanced biotechnology tools. ‍The intersection of these developments is, in my belief, where the magic really happens and why the moment is now. We have all the pieces of the puzzle, they just need to be put together.