Editor’s Note: This article is based on a September 2023 virtual panel, “How AI & Web3 are Reshaping Women’s Health." Listen to the full recording.
Web3 is "dead" — but long live artificial intelligence (AI)? While many view these two technologies as competing, they can, in fact, work together and compliment each other to innovate industries and spaces that desperately need it. (And neither, as builders in the space know, are actually “dead” despite cyclical news headlines…)
One of those areas needing support is scientific research — in particular, women’s health research. It may come as a surprise research into women’s health is currently characterized by short history, disparate data and lack of funding. In fact, it has only been 30 years since women were mandated into clinical trials. All of this impacts on new drug development and evolution of treatment.
When it comes to women’s health, numbers just don’t stack up: only 10% of US government funded research budgets goes towards female specific research and when it comes to big pharma R&D budgets allocated to female specific conditions (excluding oncology), that number drops to 1% according to a report by McKinsey&Co. A strong dissonance to 50%, or the number representing the rough percentage of the population that is female. This disparity is particularly astonishing given that 80% of healthcare decisions in US households are made by women.
Fertility issues, endometriosis, polycystic ovary syndrome (PCOS), menopause, ovarian cancer may be some of the conditions that come to mind when one thinks about women’s health, but in fact this field extends much further. For example, treatment of common conditions like diabetes can be very different in women than it is in men, and in order to understand those differences better we need more data, more research and more funding.
In September, BFF had the opportunity to meet three pioneering women, using the power of Web3 and AI to change these stats. We wanted to understand what challenges can be tackled using this technology and how they are moving the dial when it comes to women’s health research.
Women’s health sector has a distinctive challenge with data. Its lack and disaggregation are due to the fact that historically women's health wasn't recognized as its distinct industry, and women were often excluded from clinical trials. As a result, there's a scarcity of meaningful historical data. This poses challenges not only for researchers but also for technologies dependent on extensive datasets, such as AI models, which are trained on large datasets.
The little data that we do have tends to be disaggregated, adding another layer of complexity. Taking fertility as an example, data is often compartmentalized within individual IVF clinics across the world. Each clinic's dataset is relatively small, making it tricky to harness independently. Moreover, accessing data from these scattered sources is not straightforward due to strict data privacy laws and concerns about the protection and consent of patient data.
Attempting to solve these layers of complexity is the concept of federated AI. “We've built a really unique federated, or decentralized, AI platform that essentially allows us to connect disaggregated data sets that are distributed globally,” says Dr Michelle Perugini, CEO and co-founder of AI-enhanced healthcare company Presagen.
Dr Perugini describes her company as the social network for healthcare. The company's primary focus is to harness the existing fragmented data from diverse clinical environments worldwide. “Instead of bringing all that data together to one central location, we're now able to send the AI out to learn remotely on each of those distributed data sources without ever moving or seeing the data and without breaching data privacy,” she explains.
Presagen sets up local cloud servers and clinical data portals in various regions, so when a particular AI for a specific product is developed, Presagen solicits specific data. Clinics upload this data in a standardized format to these portals. The AI then visits each portal, extracting insights and amalgamating them into a central model. The outcome is an AI product that can serve clinics worldwide, all while keeping individual patient data localized and preserving patient’s privacy.
An example of such an AI product by Presagen, which is already in the market, is Life Whisperer, an egg-assessment AI, aiming to gauge egg quality before storage for patients considering egg freezing. Collaborating with roughly 200 clinics globally, Presagen established clinical and data collection protocols, secured informed consent, and sourced data from regions like India, Southeast Asia, Australia, the US, Europe, Japan, and Canada. The goal is to construct a generalizable AI that, by accessing diverse datasets, can be applied universally, regardless of demographics or clinical settings.
“I guess what we've built is the factory or the infrastructure to be able to tap the data and remotely access it, for particular use cases, whilst protecting that data privacy and security,” explains Dr Perugini.
What this means in real life is that Life Whisperer analyzes embryos during the IVF process, helps doctors pick the healthiest embryos with the highest likelihood of achieving pregnancy and being genetically normal and essentially helps patients to become pregnant quicker, preventing them from having to go through multiple, painful, costly IVF treatment cycles.
Presagen’s innovation demonstrates the transformative potential of AI, especially for sectors where data fragmentation has been a long-standing barrier.
In the evolving landscape of women's health, AI and Web3 is becoming transformative not only with respect to data but also how research is organized and funded. One of the big challenges for women’s health is the lack of research funding.
The late inclusion of women in clinical trials has resulted in a major knowledge gap, creating a "massive black box" when it comes to women’s health data, explains Laura Minquini, founder and core lead at health-research funding collective Athena DAO.
“If you're not funding researchers, if you're not funding clinical studies, then you're not getting the data or the research that translates science into potential therapeutics or treatments,” says Minquini.
Athena DAO aims to bridge this funding gap through Web3 technology and the concept of decentralized science (DeSci). Unlike traditional funding methods, Athena DAO operates as both a research institute and a funding mechanism, bringing together researchers, funders, patients and the wider community.
It works like this: the DAO issues a call for submissions with respect to a particular area of research such as ovarian aging or PCOS for example, the submissions are evaluated and then governance token holders get to vote on research proposals. The proposal is linked to a smart contract and if the researcher meets certain milestones, the contract is fractionalized and research is funded. The goal is a cyclical and sustainable approach, with research potentially yielding profitable ventures that reinvest back into the DAO, ensuring the continuity of the funding cycle.
“The ultimate vision is for these biotech DAOs to transform scientific research into tangible treatments,” explains Minquini. Athena’s recent token launch raised over $300,000 demonstrating the economic potential of this model.
Importantly, Minquini believes in the transformative potential of Web3. Beyond just a technological tool, blockchain offers transparency, engagement and empowerment. As more people come to understand the possibilities of using blockchain for societal good, projects like Athena DAO could reconstruct how we approach medical research funding. And in a field that has been historically underfunded, this convergence of technology and community has the potential to define the future of women's health.
The decentralized science (DeSci) movement is fast emerging as the disruptor of traditional research, democratizing and shifting the scientific narrative from behind closed doors into an open forum.
Dr. Pearl was driven by a mission to make the academia and industry facets of science more transparent and universally accessible. With a vision to create a “web lab” the DAO is democratizing access to cutting-edge tools, ensuring that anyone, irrespective of their location, can engage in computational life science research. Its platform, Plex, is designed to make distributed computation straightforward and user-friendly, allowing people to work on new drug development collectively, globally and remotely to advance new treatments.
Dr. Pearl is convinced that DeSci is one of the best use cases of Web3 technology: “It allows us to also reconsider traditional incentive structures, which are currently broken, and it allows us to think creatively about how to fix those incentive structures,” she explains referring to how inaccessible a lot of the published research and broader scientific work currently is, due to paywalls within academia and large biotech companies.
Through Lab DAO, Dr. Pearl and her co-founders set out to build a community where people working on drug development are incentivised to share results, where they can get the tools to work on drug development and connect with other scientists working towards similar goals.
Bridging the historical gaps in women's health research requires more than just technological solutions. It calls for a collaborative approach that embraces some of the core tenets of Web3 — transparency, decentralization, and open access.
As we step into a future shaped by AI and Web3, these technologies will be pivotal in redefining women's health research. By encouraging ecosystems where knowledge is openly shared, and solutions are collaboratively built, we are set to see an unprecedented acceleration in the innovation tailored to the unique needs of women's health that have long been underserved.
Liya Dashkina is a VC, contributor to a number of DAOs, Web3 consultant, chapter lead at the Australian DeFi Association and an advocate for women in Web3.
This article and all the information in it does not constitute financial advice. If you don’t want to invest money or time in Web3, you don’t have to. As always: Do your own research.