Lily Lyman, managing partner at Underscore VC, discusses how AI will help supercharge discoveries in life sciences and healthcare with the possibility of unlocking $4 trillion in value. She joins Caroline Hyde on "Bloomberg Tech."

Artificial intelligence is driving significant transformation in the life sciences and health care sectors, with experts estimating up to $4 trillion in potential value unlocked through improved efficiency and data utilization. The integration of AI is shifting biology from traditional laboratory work to a data-driven industry, often referred to as 'tech bio.'

Major pharmaceutical companies are adopting AI solutions to address rising research and development costs and looming revenue losses from patent expirations. Partnerships between established firms and startups, such as Takeda's collaboration with Tetra Science, are enabling faster workflows and higher productivity, while both incumbents and new entrants seek opportunities for collaboration in the evolving landscape.

AI to boost scientific discovery

You really think Boston though is going to potentially be a winning trade when you think about the compliments of what's going to win out of health care is super charged by AI. Well Caroline thanks so much for having me here in the studio. It's great to be back. And look as investors are always looking for a clear why now in a market opportunity. And we are certainly seeing a signs of transformation in life sciences and AI. What's changed is that we now have the data. We have the sophistication of the models and we have real industry pull to unlock this potential. And what it could do is unlock four trillion dollars worth of value across life sciences and health care. What's changed is that biology is no longer just a wet lab discipline. It is now a data and information industry. Many people are calling it tech bio. And we had underscores precede and seed investors and particularly based in Boston are incredibly excited about this because it's opened up a whole new world of software investing opportunities in the world of science. Can I go to that four trillion number. Yes. What's that pegged upon. What is it that we're seeing that will be fueled and to garner four trillion dollars of worth. Well if you think about what the life science the combination of life sciences and actually honestly all of scientific data and health care it's across the gamut of how this gets done today. I mean today it takes two to three billion dollars per drug and decades to develop these therapies. Think about if that can get cost. You know if that can get changed to be a fraction of the cost in a fraction of the time. The economic and the human impact of that is absolutely enormous. So the option we see is across the entire value chain in life sciences. So whether it's research and discovery whether it's in preclinical and clinical trials and services manufacturing development and deployment you put all that together and it's not hard to see how there could be a four trillion dollar opportunity coming out of this. And you said you're seeing signs. What are the signs and what are the software companies that are leveraging those signs. We're seeing across science across all the different players in the market. So the major pharma companies are certainly making moves in this space. They are under enormous pressures. I mean the cost of R&D is rising. It basically doubles every nine years. They are facing issues with their margins. They're facing a potential 260 billion dollar revenue cliff as some of their patents expired. And so that's creating the market pull for AI solutions. They are partnering with often many time startup companies. So for example Takeda just launched their partnership with Tetra Science which is a company we're invested in. Think of Tetra Science like the snowflake but specifically for scientific data. And what it's doing is it's partnering with all the major technology players. NVIDIA Google Microsoft Databricks Snowflake and rallying the tech stack around this opportunity to unlock scientific data so it can actually be used by models. And so in this one what they're able to do is working with Takeda on hundreds of use cases so I can sit on top and use this data. And it's driving 90 percent faster workflows 40 percent increase in productivity. So we're seeing that type of adoption and partnership across the major pharma players and startups. How does a portfolio company compete with an anthropic who's getting into a similar space. People always love to ask that question. How do how do the how do startups compete with the incumbents. And I always think that yes incumbents have the advantage of data and distribution. But startups have the advantage of focus and speed. And so we're seeing those opportunities across the board. I mean there's a company we're invested in called Terraflow which is automating the analysis and data around flow cytometry. And again I mentioned Tetra Science. These are opportunities that require very specific domain focus very specific types of people who can do it. And the ability to build in an A.I. native way from from the ground up the anthropics of the world. Open A.I. is also launched in this space. They also are going to need to do the practical implementation. And so they're going to need partners along the way to do it. So I think it's not a zero sum game. I think there's an opportunity for collaboration.

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