The world of women’s health is undergoing a fundamental transformation thanks to technology.

Breast cancer risk prediction, digital birth control, arousal tracking, computer aided cervical mapping and fertility planning are all possible with artificial intelligence.

Femtech, which includes AI platforms, diagnostic tools and devices for women’s health that are primarily being used via computer-aided mapping and algorithms based on large date sets, poses a major opportunity both in the traditional health care space and with consumer products. McKinsey & Co. reports the growing market ranges from $500 million to $1 billion depending on the scope, noting funding in the category reached more than $2.5 billion in 2021. 

“What it’s [AI technology] starting to allow businesses in this space to do is pair what has before been kind of stagnant, unusable data and drive greater understanding around predictability and outcomes that will allow us to move towards a much more preventative mindset in terms of how we get in front of folks’ health and well-being,” said Taryn Jones Laeben, president and founder of IRL Ventures, a go-to-market think tank.

Within traditional women’s health care, AI and computer aided systems play a major role, specifically in terms of earlier and easier diagnosis. For example, Dysis, which is covered by major insurances, is a computer-aided colposcopy that provides cervical mapping for doctors to determine what areas may be abnormal for biopsy. This approach also makes it a more active experience for the patient. 

“It has a large screen so the patient can be a participant and watch and be shown what’s going on, but also, it eliminates that human error.…It’s increased the probability that you are biopsying the correct area,” said Dr. Somi Javaid, board certified OB-GYN physician/surgeon and founder of HerMD, a comprehensive women’s health care center. 

Computer aided detection has been a key technology within breast cancer diagnosis, too. In fact, the computer assisted mammogram patented product was approved by the FDA in 1998, according to Dr. Constance Lehman, an investigator at the Breast Cancer Research Foundation. Now, AI is being used to compile data and provide risk assessment. 

“What it allows us to do is take advantage of the huge amount of data we are now collecting that we haven’t been able to process,” she said, referring to genomics and proteomics as two key areas they are looking at. “There’s just so much data and how to make sense of it is where these super fast computers and artificial intelligence can come in, sometimes seeing patterns that we humans can’t recognize.”

AI also plays a role within fertility treatment research.

“It’s largely still experimental, but there’s a lot of effort research going on to figure out ways to include the machine learning algorithms in the decision making process,” said Dr. Eric Flisser, a board certified OB-GYN and medical director at Reproductive Medicine Associates of New York, a fertility center. “The goal right now with AI is to optimize patient care by using this massive amount of data that has been collected in the past.” 

Reproductive Medicine Associates of New York is working with Alife Health, a platform that offers providers AI insights, to determine a patient’s best fertility journey based on similar profiles. 

“We’re doing some research projects on utilization of medication, timing of procedures and looking at the outcomes to see how good the models are at predicting the final endpoints,” Flisser said, noting the goal is “to reduce the the physical and emotional burden on patients by decreasing the time to pregnancy and increasing the safety practice.” 

However, AI is not perfect, especially as it pertains to individual planning, according to Flisser. For example, an AI-driven software might recommend immediate family building when in reality, egg freezing is best based on a patient’s desired timeline. 

“We’re not saying it’s a replacement for providers. There’s going to still be a need for interpretation and validation,” Javaid said. 

A recent study from the University of California San Diego and Johns Hopkins University showed that nearly 80 percent of ChatGPT responses to medical questions were better in quality and empathy compared to real doctors. However, time, burnout and resources play a critical role in these findings, and the study discussed chatbots as an assistant tool to clinicians. 

While many of these technologies provide valid diagnosis, they are not widely accessible. Javaid identifies two key issues: funding and time. There is an overwhelming lack of research funding within women’s health care — excluding oncology less than 1 percent of research funding goes to women’s health care. Furthermore, implementing these new technologies is expensive, and according to Javaid insurance reimbursements have gone down and appointment times have become shorter for many medical systems.

An array of consumer-facing brands are also harnessing the power of machine learning, making certain technologies more accessible. 

Lioness, founded by Liz Klinger and Anna Lee, is a sexual wellness brand that offers a vibrator that uses sensors and AI technology to track a user’s arousal on an app. The algorithm compiles more than 100,000 anonymous sessions to highlight specific moments, while the device’s sensors detect pelvic floor muscle movements. 

“The benefit for people is that they’re able to see their own physiological response in a way that hasn’t really been possible before. You’re able to see different nuance changes over a period of time,” said Klinger, chief executive officer of Lioness. “If you talk to a sex therapist about how people can improve their own sexual pleasure or get a better understanding of it, usually the advice has been keeping a journal.…Practicality speaking that can be kind of difficult sometimes because with something like masturbation or sexual pleasure, you want to be more in the moment.” 

For Javaid, this technology also marks a major shift in understanding women’s sexual health. 

“We’ve been teaching the same orgasm model since the ’60s or ’70s, and so this is really nice because it’s teaching us about orgasm so much more. We don’t know nearly as much about women’s sexual health as we do men’s sexual health,” she said. 

Natural Cycles has also targeted women’s health with its FDA-cleared birth control app, which recently closed a $7 million funding round led by Samsung Ventures. By tracking a user’s daily temperature combined with the brand’s machine learning and equation-based algorithm, Natural Cycles can detect fertility levels.

“Today, Natural Cycles is a mixture of equations and machine learning, so we’ve managed to replace some parts with machine learning where it started performing better than the equation,” said Natural Cycles CEO and cofounder Elina Berglund, noting the AI tech has progressed since the brand’s founding in 2013. Therefore, Natural Cycles’ algorithm- and equation-based approach periodically changes based on the evolution of machine learning. 

Natural Cycles can now also be synced with the Oura Ring, so users don’t have to take their temperature every day at a specific time. A new ring, Evie by Movano Health, is expected to hit the market later this year with similar computer aided tracking abilities, specifically for women. Just as L’Oréal also previously partnered with menstrual tracking app Clue, McKinsey & Co. cites femtech as an area for heritage brands to get involved in, in order to push the industry forward. 

Several other technologies are innovating within the category. Next Gen Jane is a start-up developing a smart tampon collection system that detects reproductive disease. Digital platform Gabbi, which IRL Ventures has invested in, uses an AI model to predict a person’s risk for breast cancer. 

As new technologies and consumer-facing brands come to market, McKinsey & Co. reports growing opportunity within the category and several gaps that require innovation, such as clinical diagnostics for menopause or innovative contraception services. However, as the category has experienced a major boom, investors and consumers will be seeking out brands that successfully address a specific need, according to Laeben. 

“What is important, and you’re starting to hear this more and more from venture investors, is AI for a true purpose and evaluating opportunities and use cases on an individual basis, not just integrating AI blindly for the sake of it,” she said. It’s “understanding how it can be deployed towards problems that investors and humans in general are interested in solving.”

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