Founder & CEO of @medra_ai. Let's eradicate disease. Prev. phd @StanfordAILab, robotics @nvidia, propulsion @SpaceX. Loosely hinged.
San Francisco, CA
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Welcome to the scientific revolution. 100s of robots. Zero coffee breaks. America’s largest autonomous lab, open today.
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Michelle Lee retweeted
How is AI accelerating scientific progress?
On October 7, I'm moderating a conversation with three founders and leaders working on that question:
• Michelle Lee, CEO of @medra_ai
• Andy Beam, CTO of @LilaSciences
• Gleb Kuznetsov, CEO of @ManifoldBio
@AnthropicAI and @nvidia are bringing together founders, researchers, and builders at Claude Founder House during #SFTechWeek to talk about AI for science and drug discovery.
We’ll start with a short panel, then continue the conversation over drinks. If you’re building in this space, we’d love to see you there.
October 7 · 5–7:30pm PDT · San Francisco
Request to join: luma.com/claude-ai-for-scien…
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Michelle Lee retweeted
PSA: ~50% of pharma’s outside R&D dollars are now going to China.
Annie Lamont says the US is now facing an “existential threat”
“We found out during Covid—you don't want them producing 90% of all the ingredients for antibiotics.”
“We have an existential threat in this country & an industry that is being co-opted, & we need to, through technology & tools & investment & a complete re-engineering of our FDA & processes, fix that rapidly.”
BREAKING: Only 10% of AI companies are worth their valuations. The other 90% aren't.
Annie Lamont, Co-Founder & Managing Partner of @OakHCFT
#1 healthcare investor on the Midas List, 40+ years investing, 70+ exits, 15 IPOs, & $7B+ firm that just closed $2B Fund VI
FULL INTERVIEW
We sat down at the @NYSE to talk AI drug discovery, China's rise in pharma research, Devoted Health as the leading example of AI in healthcare, & frontier labs as the next healthcare acquirers.
We cover:
› Pharma now sends 50% of its outside research spending to China, a shift from the last 4 years
› @chaidiscovery's AI makes antibody design labs 100x more productive
› @DevotedHealth tripled in size in the last year
› Oak committed $100M on day 1 to Auger, ex-Amazon exec Dave Clark's AI supply chain startup
› Oak’s latest investment in Halluminate, a data research lab building reinforcement-learning environments for financial services
𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒
(00:00) Annie Lamont, Co-Founder & MP at Oak HC/FT
(00:56) How AI reshaped Healthcare & Fintech
(05:35) Why AI in biotech is finally exploding
(08:35) The China threat to American drug development
(17:03) Are Hospitals actually at risk from AI?
(23:26) How AI will transform your healthcare experience
(26:32) How the AI shift changed the way Oak evaluates companies
(32:58) How M&A is changing in Healthcare
(35:43) What a great acquisition looks like
(50:26) Halluminate
(53:20) Augur
(58:49) What's kept Annie Lamont going for four decades
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Maybe we can organize a debate next year at Unlock 2027, or we just have speakers show real results. Agreed with Ron here, debate won’t cure cancer, science will
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Growing up my life goal was to get an obituary on The Economist. Too bad print is now irrelevant and even if I got it, I’d never find out 😐
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In our 24/7 running lab, we never sleep, never get tired… we’re gonna make it, you and i, we’re gonna save the world tonight 🎵🎶🎸
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363 days out of the year I tell everyone our office on Folsom St is the best location to run an autonomous lab and a growing startup.
2 days out of the year we need to instruct our team to sanitize our doors… just in case.
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What an honor to be named an Endpoints11.
More importantly, honored to be trusted by the most ambitious pharmas & AI co’s using autonomous labs to find new cures. Medra is committed to partner closely to achieve our customer’s most ambitious vision of AI-driven discovery. LFG🦾
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Read more on how we partner with customers (we even encourage them to build themselves 😉) @endpts:
endpoints.news/endpoints-11-…
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What was so incredible about visiting Neko as a robotics and AI researcher was recognizing the underlying technologies yet being completely blown away by the level of details, engineering, and execution.
An example: Computer vision models can recognize moles on your skin from camera images for over a decade now.
But to build a scanner that can identify every mole on your body in less than a minute meant Neko not only had to invent an entire new scanner with 17 cameras, they even had to design and build NEW CAMERAS from scratch because commercially available off the shelf cameras were not up to spec. Then they had to get FDA approval, which is probably a more annoying problem than the engineering one tbh.
What a triumph.
Robotics and AI will completely transform human health in all kinds of ways. The underlying technology is all there. It’s about executing, scaling, and applying the technologies to even bigger applications.
And there is no more ambitious application than our health and disease eradication. To all my fellow roboticists: take a break from training robots that fold laundry and go to NYC to get scanned at Neko. Be inspired. Then go build the most ambitious version of the future. It doesn’t have to be at Medra. But it should be fucking amazing.
Heyo! After 8 years of R&D and learnings from 100,000+ scans in Europe, @Neko is finally live in the US!
Our clinic in NYC features our new scan room, fitted out with the latest generation of our medical devices (FDA cleared) ✌️
The Neko Lab can now analyze 50+ blood biomarkers with every scan, with results delivered within the same 1 hour visit.
25,000+ people are already on the waitlist and we just started inviting our earliest supporters to book.
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“Having more demand than you have supply for is a good problem to have”
Good problems are still problems yknow 😭😭😭
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Went all the way to London to try Neko. It blew my mind. Can’t wait for the clinic to open in SF.
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LFG 🚀 can’t wait for this to drop
I'm excited to take you all behind the scenes at 776 co @medra_ai where @michellearning is building the infra layer to eradicate disease. LFG.
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Come work at Medra if you want to solve the brittle lesson for robotics and the bitter lesson for biology
Robotics companies have all accepted The Bitter Lesson and we now see awesome demos, but most have no idea about The Brittle Lesson and boy are they in for a surprise when trying to productize.
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I was joking with my academic friends that I approach my career with a kind of naive idiocy.
Before Medra, I could have spent a year as a professor while working at NVIDIA. Just one year would have left me both financially secure and reputationally set. And honestly, I’m not sure starting Medra a year later, or delaying it for a year, would have made that much of a difference.
Sometimes I look back and think: why didn’t I just do the obvious, rational thing? The thing that most smart professors I admire do — start a company while remaining an academic.
My friends reminded me of something: the person who would have thought that way probably wouldn’t have started Medra in the first place. And maybe wouldn’t have been the kind of person crazy enough to believe they could eradicate disease. Fair enough. 😅
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We had 10 interns this summer. Half are dropping out of school to join Medra full time right now. They got the full time jobs I would have killed to have when I was 20, so I can’t tell who’s luckier — them or Medra. Probably us cause these kids are so mindblowingly cracked 🤯
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Don’t just hope. Build. Help us build the infrastructure layer necessary to eradicate disease.
Assume that models are going to get increasingly good at drug discovery (lots to unpack there but let's leave that in the hands of the dozen+ labs working on this) - to get a drug to production you're always going to need to run experiments in a lab.
If that infrastructure layer doesn't also get faster, we could find ourselves in a world where we have all these amazing potential discoveries at our fingertips but can only tackle them at the speed of a human-run lab.
Hence why @medra_ai is building a robot physical scientist.
@michellearning imagines a world where drug discovery can be hyperpersonalized, if the cost and velocity of lab experimentation can also accelerate.
"once the AI models get good enough and we can all get access to it, what's missing then is that infrastructure layer to be able to run experiments at scale so that you yourself can actually become a drug discovery person."
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If you’re excited about solving disease and physical AI, watch this and DM me. We are absolutely slammed with demand and expanding our team across all roles: eng, science, ops, recruiting.
One of the most exciting (and challenging) applications of physical AI is thinking about how it can accelerate scientific discovery. Imagine a robot that can pipette, handle stem cells, operate existing lab machinery, 24/7 - a physical AI scientist.
This is what the new episode of @GreylockVC Change Agents is all about, featuring @michellearning, founder and CEO of @medra_ai. We talk about building an AI-powered lab, how accelerating physical AI lab experimentation is the key to unlocking drug development, and how Medra is automating experimentation today inside pharma companies.
00:00 Teaser
00:56 Medra’s founding mission
04:17 Hypotheses are not enough
13:27 Medra’s differentiation
20:22 The experimentation bottleneck
27:06 Refining the agent harness
29:05 The role of the physical lab
33:23 Managing context across different customers
34:59 Working with models
40:26 Towards personalized medicine and drug discovery
43:15 AWS for life sciences
Thank you for joining @michellearning
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