NewLimit, a 1.5-year-old, San Francisco-based, 17-person company that aims to increase the number of healthy years each person lives by epigenetically reprogramming cells, is today announcing that it has raised $40 million in Series A funding from Dimension, Kleiner Perkins, Founders Fund, and other investors to further its mission to extend humans’ health and lives.
We talked with two of the companies’ four cofounders yesterday, including Coinbase CEO Brian Armstrong and VC Blake Byers, who has a Stanford PhD in bioengineering. During that chat, we got more insight into the round, which also counts Coinbase cofounder Fred Ehrsam, Y Combinator President Garry Tan, and founder-investor Elad GIl as backers; we talked with them about how NewLimit can differ itself from rival companies. We also asked Armstrong about the inevitable jokes centered on billionaires trying to escape death by throwing money at it.
TC: Brian you have a job as Coinbase CEO. Blake, you have a job running Byers Capital. Who is running NewLimit?
BA: There are four cofounders of the company. I’m really just an investor and a board member. There two other cofounders, Greg [Johnson] and Jacob [Kimmel] are really operating the business day to day.
Are they co-CEOs or is the company’s bringing on a full-time CEO?
BB: The company doesn’t have a technical full time CEO right now.
What why is that?
BA: It’s early stage and the current founding team is working really well, so we haven’t defined that yet.
But you’ve now raised $150 million to date, is that right, and are you talking about the valuation of the company at this point?
BB: The $110 million from Brian and myself is a commitment over the lifetime of the company so it’s not fully funded yet, then this $40 million is another commitment from VCs. So we have access to that capital over time, but it’s not necessarily the amount that’s in the bank. We’re not [talking about the valuation].
An earlier news release said that you’re going to start by interrogating epigenetic drivers of aging and developing products that can regenerate tissues to treat specific patient populations. First, just to be clear, what are the specific drivers of aging you’re talking about? Diet? Exercise? Sun damage? Toxins?
BB: There are likely many drivers of aging. And we’re not here trying to elucidate all of them. We’re more saying like, hey, we think that epigenetics alone are a major contributing driver to aging. And so by kind of reprogramming the epigenetics of a cell, you can reverse a significant amount of the functional decline that we see with age. And our proof point of that is you can take an old skin cell from an animal and you’re going to turn that into a newborn animal with an entirely normal life ahead of it. And then you can actually wait for that animal to grow up and be old and take one of its old skin cells and turn that into a newborn animal with an entirely normal life ahead of it, with entirely healthy skin.
There’s actually one lab that did that for more than 13 generations [of mice] over 22 years, just serially, one after the other after the other, all descended from that one parent cell — an old skin cell. And the mice all lived normal lives. We don’t know if this is going to hold up in humans and in different cell types, but it kind of shows you like there’s there’s something very potent and powerful about the ability to just reprogram the skin cell or neuron or the heart cell using epigenetics, even though we’re not tackling what could be other contributing factors to aging.
It brings to mind artificial-egg technology and this idea or hope that even same-sex male couples might be able to have children if we can figure out how to turn any cell into an egg, which has been done with male mice. What exactly is on your roadmap?
BB: For right now, it’s very basic research stage of a company. We’re trying to figure out how these mechanisms work and how we can control the epigenetic state of the cells and find these sets of transcription factors that can turn old cells into young cells. So that’s what we’re doing right now before we can make a product, and we’re starting in an immune cell called T cells. The idea is one day if we’re successful, you could make old people’s immune systems younger, and so more functional. We’ll also add some other cell types. We don’t know exactly what those will be yet, but an example would be liver cells, which are called hepatocytes, or brain cells, like neurons, where you could restore function in these age cells.
NewLimit says it will use machine learning models to understand how these cells change with age. How you develop a moat around something like this, where you’re talking about troves of information about human cells, which is not a proprietary data set?
BB: I’d say the big difference of developing these general AI models on public data is, like, everyone has access to the public data, including these large language models. For us, we’ve already trained on public data and within two months, our models had saturated how good they were going to be, and now we have to generate the data ourselves to improve the models even further. So a lot of the cost and complexity [centers on] how you generate huge amounts of data in house while still being very efficient.
How exactly are you generating your own data in-house?
BB: We’re generating new scientific data ourselves by running experiments in our lab. What those experiments look like is we insert human transcription factors into human cells like T cells, and then we monitor that cell and to see how it changes after we introduce that transcription factor. It’s called an over-expression experiment. Then we do that with 100 different transcription factors, then with combinations of different transcription factors. And we measure everything we can about the cell, including how it changes the gene expression to the cell and how it changes the epigenetics of the cell. And we use all that information to feed into our machine learning models that then tell us what to test next. So we have a bunch of human immune cells growing in the labs that we’re inserting these transcription factor sets into, and that’s what’s generating the data to train the models.
Where are these donor cells coming from?
BB: T cells you just can get from blood draws, so it’s pretty easy to access these kinds of donor draws.
Are you working with a hospital system?
BB: I don’t want to go into who [the sources] are exactly, but it’s very standard in the industry. There are various groups that help provide blood draws to groups that are working on research projects to make medicines. And it’s all consented donors who are aware of what their specimens are being used for.
Is it possible to explain at what point the data becomes meaningful?
BA: Well, there are something like 1700 transcription factors in the human body. And so if you were to take how many combinations of five transcription factors there are out of 1700, it would be about 10 to the 10. So it’s a very large number. You could imagine that as being the search space of different potential combinations. Is that helpful?
To some readers, hopefully! Before letting you both go, Brian, invariably people are going to comment that billionaires keep trying to extend life because they can’t take their billions with the. What’s your reaction?
My high level thought is that if you’ve made money in software, it’s good to put money back into society in ways that can help improve the human condition, and biotech research is one of those really important areas. I don’t think it gets enough funding. If you look at all the major diseases out there that kill people — heart disease, cancer, diabetes, dementia — they’re highly correlated with aging. Generally speaking, these are not diseases of younger people. So it makes sense to me that we should try to go after big ambitious problems in the world. And I think there’s actually a generation of tech billionaires — Sam Altman, Patrick Collison and a bunch of them — that are putting real capital toward some of these hard problems in the world, and I think that should be celebrated.
One billionaire who thinks anti aging research is dangerous is Elon Musk. He has said it could lead to rapidly aging populations that would lead to further declining birth rates and a very ossified society where new ideas cannot succeed. What do you think about the potential downsides of people living longer?
BA: I think it’s important that if people are going to live longer — which, by the way, that’s a big if; there’s a lot of work ahead of us to see if that is even possible — that their minds remain plastic and they remain open to new ideas and things like that as well. So in an ideal world here in the future, there’s a way for us, our bodies and our minds, to stay young.
BB: I’d also point out like we basically have doubled the average human lifespan over the last 100 years. And I think everyone would agree that’s a good thing. Do we really want to go backwards? Do we think this is actually optimal? Or do we want to keep improving it for people? I think the world is very resilient. It’s a beautiful thing to let people express themselves over longer periods of time and to spend more time with the people that they actually love in life.