Generative AI is definitely the word we will remember 2023 by. Knowing that administrative burden is among the key reasons for physician burnout, the idea that AI could tackle this challenge, became a little bit more tangible with the raised awareness and public understanding of generative AI. But where are we exactly, and how is generative AI utilized for clinical use cases, administration, patient care, and in biotech? 

2023 Rock Health Report for first 6 months of 2023, showed a significant decline in digital health startups funding:

We’re where we were in 2017. But it’s not that this year or last year were anomalies, 2020 and 2021 were, due to the pandemic, says Partner at GSR Ventures Justin Norden.

GSR Ventures and Maven Ventures are two health technology-focused VC firms that analyzed 145 startups across healthcare delivery and life sciences with generative AI solutions. They highlighted their innovations, challenges, and market potential. Collectively, the startups have earned more than $20 billion in funding and have 47,000 employees.

In Generative AI in Healthcare, Investors Are Betting On:

• Entrepreneurs going after new markets - problems that haven’t been addressed yet, 

• Companies that have found an area where technology is able to provide 10x improvement over the status quo (administration!), 

• Companies and founders able to find differentiated go-to markets, investors want to know how do they build strategic partnerships and alliances that enable them to enter the market more pace, and not slog through the typical 12 to 36-month sales cycles.

INVESTMENT SO FAR:

• Life Sciences ($6.5B raised, nine-year median age, 22 companies)

• Patient-Facing ($2.3B raised, eight-year median age, 12 companies)         

• Clinician-Facing ($6.0B raised, seven-year median age, 49 companies)    

• Administrative ($2.7B raised, five-year median age, 43 companies)           

• Analytics & IT ($2.5B raised, six-year median age, 19 companies)

”Life sciences companies that have been using AI, these companies have, in general, been around for longer. So these are older companies that have taken on very ambitious targets to basically reinvent the whole drug discovery process. And then the pursuit of that has raised giant sums of money again over the past many years,” comments Justin Norden.

While generative AI is making new leaps in what’s possible, it’s not necessarily going to be that easy to get it adopted in clinical practice. Trust will be the main thing innovators will have to gain to be successful, says Justin Norden. “Healthcare has been burned so many times by over promises and technology. We've seen the Watson AI failures, a lot of physicians see EMRs really holding healthcare back. We've over-promised time and time again, digital transformation has failed in healthcare. And so I think there's a big resistance and lack of trust for a new technology company saying it's gonna be different.”

Where to begin?

According to Norden, the first widely adopted use cases of generative AI in healthcare will be seen in solving administration burdens. Clinical decision-making and support will come later, and personalized medicine will be the last to see broader adoption.
”Robotics and automation, things like fully automated surgeries and things like this. are exciting and fun to think about from a research perspective, but we’re still years away from a truly automated robotic surgery business model. On the other side of the spectrum, things like note-taking and medical coding are already being implemented,” Justin Norden says.

This is just an excerpt, tune in to the full discussion on Spotify: