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Today we’re announcing $106M in new funding led by Altimeter Capital and Bezos Expeditions. This brings our total to $150M to scale our frontier AI models which make biology programmable.
Our frontier models have generated functional proteins (Nature Biotech, 2023), created the first CRISPR system designed from scratch (Nature, 2025), and showed clear scaling behavior (NeurIPS spotlight, 2025).
The opportunities ahead are unimaginable. If you’re excited by shaping the future of biology – join us in pushing the science forward.
Forbes: forbes.com/sites/amyfeldman/…
Press Release: businesswire.com/news/home/2…
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Nature Biotech, 2023: nature.com/articles/s41587-0…
NeurIPS spotlight, 2025: biorxiv.org/content/10.1101/…
Nature, 2025: nature.com/articles/s41586-0…
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Stephen Nayfach, our Head of Bioinformatics and Platform R&D, is at @CSHL this week for the Genome Engineering: CRISPR Frontiers event. Find him and say hi if you're there! 👋
He's giving a talk on using our AI models to design CRISPR-Cas9 variants for base editing ("Programming PAM Specificity for Mutation-Specific Base Editor Design") and also chairing the session "CRISPR Technologies I"
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More on the event: meetings.cshl.edu/meetings.a…
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Profluent retweeted
Heading to Summer RosettaCon next week to share my work from my time at @ProfluentBio
Come listen to my talk about the encoder model Profluent-E1 on Thur at 1:30pm (“E1: Retrieval-Augmented Protein Encoders for Fitness and Structure Prediction”) and let’s chat after!
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The Profluent team is heading to Summer RosettaCon next week! Find @jeffruffolo, @richardwshuai, @ShiakiMinami, and Alex Hoffnagle and say hi 👋
You can hear Richard talk about E1, our encoder model, on Thur at 1:30pm (“E1: Retrieval-Augmented Protein Encoders for Fitness and Structure Prediction”) and Alex share his work on our AI-designed base editors on Mon at 7:30pm (“Design of Programmable Base Editors with Protein Language Models”).
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Profluent retweeted
The government is backing us for a moonshot to design *personalized curative* medicines. Excited to be partnering with GemmaBio and be in the elite company of the best medical centers in the world.
Each word has significance.
Personalized = bespoke to each patient [this is where programmable biology with AI can directly play a role]
Curative = lasting solutions that cure not just manage disease. This is what we at Profluent live for, real cures to disease.
Let's go build!
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A suite of AI-designed base editors, all from one scaffold. The only piece unique to each patient is the guide RNA.
That's the shift AI unlocks: rare disease moves from 'one drug at a time' to a platform, built to bring cost down and reach more patients.
More on our work with GEMMABio, now backed by @ARPA_H's THRIVE program, below.
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Read the PR here: prnewswire.com/news-releases…
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The bottleneck in rare disease is design: too many mutations, one editor at a time. AI unlocks that.
Proud to be building GemmaBio's platform with them under @ARPA_H 's THRIVE program. We're bringing our frontier AI models and base editors to the work to design modular gene editors that scale across many mutations.
95% of rare diseases have no approved treatment.
When your child is getting sicker, waiting isn’t an option.
ARPA-H is investing $160 million through THRIVE to accelerate personalized genetic cures for the kids who need them most.
A rare diagnosis should never mean no hope for a cure.
@broadinstitute @ChildrensPhila @igisci @StJude @Stanford #GEMMABio #MassachusettsGeneralHospital
arpa-h.gov/news-and-events/a…
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The Profluent team will be at ICML in Seoul next week. Find us to chat, grab a coffee, or join us for dinner!
We’d love to talk shop (protein language models, protein optimization, sequence-first methods vs structure-first). Basically, anything at the intersection of AI and biology.
Want to grab coffee? Let us know here: forms.gle/yWQpAvLiQ1KfM85u7
Or want to hang out and chat over dinner? Reserve a spot at our table: luma.com/qpc1mfw9
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And here's a few places you can find us during the conference:
— Oral talk: @thisismadani with collaborators from NVIDIA and Microsoft Research: "FLIP2: Expanding Protein Fitness Landscape Benchmarks for Real-World Machine Learning Applications" (Tue, Jul 7 @ 10:15am, Hall D2)
— Workshop: Join @jeffruffolo, @AadyotB, and the Profluent team: "E1: Retrieval-Augmented Protein Encoder Models" (Sat, Jul 11 @ 2:25pm, Room S317)
— And our very own @park_jungy will be presenting work from his PhD: "Discovering Symmetry Groups with Flow Matching" (Wed, Jul 8 @ 5pm, Hall A #3010) and "Smoothness Errors in Dynamics Models and How to Avoid Them" (Thu, Jul 9 @ 2:30pm, Hall A #2200)
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P.S. Yes, we are hiring!
job-boards.greenhouse.io/pro…
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We're still in the GPT 1.5 era of AI × biology
The early models already work (signal: our $2.25B Lilly partnership) but we're nowhere near the ceiling
We're speedrunning to GPT 5 as fast as we can
@thisismadani with @nathanbenaich @airstreet
it's been a huge few weeks for ai in bio: a $2.25b @profluentbio x @elilillyandco deal on ai-designed gene editors, verve's base-editing data, new scaling results on protein models from @czbiohub, @isomorphiclabs' haul.
@thisismadani and i recorded a pod diving into all of it
we get into taking biology from discovery to design, sequence-first vs structure-first, and why he calls this the "gpt-1.5 era" of biology...
enjoy!
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Biology is no less complex than text and (in our biased opinion) way more impactful. Yet a fraction of the world's AI talent and compute is pointed at it.
The field is wildly undersaturated.
Watch @thisismadani chat with @nathanbenaich @airstreetcapital about the opportunity.
it's been a huge few weeks for ai in bio: a $2.25b @profluentbio x @elilillyandco deal on ai-designed gene editors, verve's base-editing data, new scaling results on protein models from @czbiohub, @isomorphiclabs' haul.
@thisismadani and i recorded a pod diving into all of it
we get into taking biology from discovery to design, sequence-first vs structure-first, and why he calls this the "gpt-1.5 era" of biology...
enjoy!
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OpenCRISPR was the first demonstration that AI could design a genome editor from scratch. We used our AI model to build a protein that doesn't exist in nature for a specific function and it worked.
Watch @thisismadani chat with @nathanbenaich @airstreetcapital about where we’ve gone from there (and where we’re going)
it's been a huge few weeks for ai in bio: a $2.25b @profluentbio x @elilillyandco deal on ai-designed gene editors, verve's base-editing data, new scaling results on protein models from @czbiohub, @isomorphiclabs' haul.
@thisismadani and i recorded a pod diving into all of it
we get into taking biology from discovery to design, sequence-first vs structure-first, and why he calls this the "gpt-1.5 era" of biology...
enjoy!
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Our partnership with Eli Lilly carries up to $2.25B in milestones. The bigger story is the unlock behind it: large gene insertion, a problem AI makes solvable for the first time.
Watch @thisismadani in conversation with @nathanbenaich @airstreet.
it's been a huge few weeks for ai in bio: a $2.25b @profluentbio x @elilillyandco deal on ai-designed gene editors, verve's base-editing data, new scaling results on protein models from @czbiohub, @isomorphiclabs' haul.
@thisismadani and i recorded a pod diving into all of it
we get into taking biology from discovery to design, sequence-first vs structure-first, and why he calls this the "gpt-1.5 era" of biology...
enjoy!
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Profluent retweeted
it's been a huge few weeks for ai in bio: a $2.25b @profluentbio x @elilillyandco deal on ai-designed gene editors, verve's base-editing data, new scaling results on protein models from @czbiohub, @isomorphiclabs' haul.
@thisismadani and i recorded a pod diving into all of it
we get into taking biology from discovery to design, sequence-first vs structure-first, and why he calls this the "gpt-1.5 era" of biology...
enjoy!
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Profluent retweeted
can AI scale it?
at ASGCT this month, we showed AI can ~10x the addressable coverage when designing base editors (the molecules behind the Verve/Lilly announcement), among other benefits.
that translates to an unlock for patients by dramatically expanding addressable targets for therapeutic gene editing
we don't want a world where this is a one off breakthrough. we want a repeatable engine.
Eli Lilly has done it.
They've gone and made what seems to be a powerful, permanent gene therapy for LDL cholesterol.
That means they'll be able to effectively prevent most heart disease with a single infusion!
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Profluent retweeted
we live in the future - the next step is designing large gene insertions and fine scale editing with AI 👀 @ProfluentBio
“One dose of VERVE-102 (in vivo base editor) led to dose-dependent, substantial, and sustained reductions in PCSK9 and LDL cholesterol levels.”
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Profluent retweeted
cool to see 3 nature papers published in one day on AI for science.
contrary to AI replacement doomerism, i firmly see the future being defined by the scientist. incredible time to build
previous decades focused builder energy on social media or enterprise SaaS. this is insanely more exciting and impactful.
drug discovery clearly is one of the largest impact areas. i hope it will extend beyond that as well
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At PEGS Boston? Don't miss our Lead Protein Design Scientist Jeliazko Jeliazkov presenting "Designing Optimal Proteins at Scale"
Generating proteins that are simultaneously optimal across many properties (affinity, stability, developability, and beyond) is a hard problem. Jeli's sharing our work on alignment of our foundational AI models as a path to multi-parameter protein optimization, with applications from gene editors to antibodies.
Interested in learning more about our multi-parameter optimization work? Shoot us a DM.
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