Lexi Rovner

co-founder & ceo @64xbio | @ycombinator S18 | prev @ucberkeley, @yale, @geochurch lab, @wyssinstitute, @harvard | musician, runner, skier

[Lexi Rovner @lexrovner]

We’re launching AAV Apex Suite today — a new product line to support gene therapy drug developers and CDMOs.

AAV gene therapies have incredible potential to cure disease, but cost and scale limitations have held them back. At @64xbio, we’re on a mission to solve these challenges for advanced therapies. AAV Apex Suite is a meaningful step toward that goal for gene therapies — helping our partners improve yields and bring these medicines to more patients.

AAV Apex Suite is a major milestone for us, an initial demonstration of what our VectorSelect platform can do, and there’s more to come. Built on genome-scale screens, our growing cell map reveals genetic and metabolic perturbations that drive yield, and is continuing to guide the development of our future products. Huge credit goes to our team today — their incredible work made this possible.

Learn more by reading our press release and visiting our fresh new website at https://t.co/kfohYjfNSp (thanks Bunsen)!

[64x Bio @64xbio]

Today we’re announcing AAV Apex Suite, a powerful suite of tools for end-to-end AAV production.

The future of medicine is taking shape, but scaling it remains a challenge. Some of the biggest breakthroughs in gene therapy continue to be held back by manufacturing constraints. Overcoming this barrier will be a key step in moving the field forward.

AAV Apex Suite includes engineered suspension-adapted HEK293 clonal cell lines and robust, transfer-ready processes built around commercially available consumables. Our cell lines have been independently confirmed by partners across multiple scales, serotypes, and therapeutic payloads at high titer and quality.

As an initial demonstration of our VectorSelect platform, AAV Apex cell lines already achieve unconcentrated bioreactor titers over E15 viral genomes per liter.

Read our press release: https://t.co/gOEOwJXNe7

Learn more about AAV Apex Suite, our VectorSelect platform, and how to work with us, on our new website at https://t.co/EeI6pui6Rc, developed in collaboration with the talented team at Bunsen!

[Gleb Kuznetsov @glebkuz]

Last week, I was invited to present at @AnthropicAI'e Boston Tech Week event.

Since the Claude Code moment at the end of last year, the way we do science at @ManifoldBio made a quantum leap overnight. But really, it just came full circle.

Manifold was founded by “hybrid scientists” and most of our first few hires could and did both code and do wet lab experiments. This was critical to invent and build the foundational molecular barcoding tech that lets us do the million-scale experiments no one else in the world can do, including interrogating drug candidates directly in vivo.

Soon, the form of most of the data generated at Manifold became next-gen DNA sequencing data. (At the Anthropic forum, I live vibe-analyzed a summary that showed we’ve now done 525 NGS runs generating over 70 tera-bases — 10,000 human genomes worth).

Engineering biology through this NGS lens is both a feature and a challenge. A feature, because this is how Manifold unlocks massive parallelism (a.k.a. GPU-ification of biology). A challenge, because for many scientists this was the first time they couldn’t easily analyze their own data, and became bottlenecked by a dedicated computational counterpart to help turn around insights, which still took weeks.

Over night, that bottleneck has evaporated, aided by a strong data integration layer and an agentic interface we’ve built on top.

Once again, everyone at Manifold Bio has become a hybrid scientist, just in time as the in vivo engine has achieved both scale and richness that have not been possible before.

Even before this, we had already started making immensely valuable discoveries, including shuttles exploiting novel portals to deliver medicines to the brain – a high value problem that led to our first landmark deal with Roche last fall.

Now that the loop is closed for scientists (and agents) at Manifold Bio, the pace of these discoveries is accelerating and we’re about to sweep through many more of the grand challenges in medicine.

Thanks again to the Anthropic team for the opportunity.

[NewLimit @newlimit]

Following breakthrough results, we’re bringing longevity medicine to human trials.

We’ve raised a $435M Series C led by @foundersfund to make it happen.

Reprogramming cell age has the potential to create more healthy years for everyone. We're closer than ever to realizing it.

[Sam Altman @sama]

We want to help the world get a head start on biodefense:

https://t.co/gDQfOZrLA4

[Seth Bannon @sethbannon]

Can't we do better?

First short film from @fiftyyears.

[Sam Rodriques @SGRodriques]

We live in a golden age of biology. So why are people still dying from disease?

Because discovery and development move slower than they should.

Today, we’re partnering with Incyte to change that.

Kosmos is now the first agent that can compress months of drug development into weeks, from the earliest stages of scientific discovery through to FDA approval. @Incyte will be the first company to deploy it across their pipeline.

Work that used to take a team of scientists months now happens in weeks.

Patients can't wait, and neither can we.

[george church @geochurch]

https://t.co/iDtrYONBim

[Jared Friedman @snowmaker]

"Make something agents want"

[Demis Hassabis @demishassabis]

I’ve always believed the No.1 application of AI should be to improve human health.

That work started with AlphaFold, and now at @IsomorphicLabs with the mission to reimagine drug discovery and one day solve all disease!

We are turbocharging that goal with $2.1B in new funding.

[Josh Kopelman @joshk]

Beginnings Matter.

Who you are is a reflection of how you were raised. I am a reflection of how my parents raised me. And all of the founders I’ve been privileged to work with are a reflection of how they were molded by their parents.

On Mother’s Day, @firstround thought we’d give some of our founders the opportunity to acknowledge the impact their mom had on them.

@martabralic’s mom came to the US from Serbia without knowing anyone, learned English and programming languages to pick up new jobs to support the family. She gave Marta the confidence that she, too, could do hard things, like building @pomelocare.

@kareemamin's mom modeled grace under pressure (even when Kareem once crashed her car). That’s probably why Kareem has an insane ability to remain calm under pressure, which he uses every day at @clay.

@celinehalioua's mom pursued her PhD and instilled a love of research in Celine, which inspired her to start @loyalfordogs.

Happy Mother's Day!

[Jason Kelly @jrkelly]

RIP to one of our few ballers in biotech.

I hope we use Craig's memory to not be afraid to go big in biotech. The world needs our tech and it's a loss to not have his voice pushing everyone.

[Harris Wang @harriswangnyc]

1/ Excited to share our new paper in Science: “Toward life with a 19-amino acid alphabet through generative artificial intelligence design.” @ColumbiaSysBio @ColumbiaBME @Columbia
https://t.co/ZT3Ygw9tiG 🦠🧬🛠️🖥️💥

[Sajith Wickramasekara @sajithw]

In the AI era, the traditional biopharma industry is the underdog. Big tech and AI labs are building wet labs. China has overtaken Europe in molecules produced. But the tools available to the industry discuss science, not do it.

The hard problem in AI for science is at the interface between the physical and digital worlds.

We built an AI Scientist at that seam. It wires together the digital and physical worlds of R&D. Predictive models, data infrastructure, wet lab execution feed into a single loop that reasons, acts, and improves with every experiment. Our ambition: get molecules to the clinic twice as fast.

Last fall I wrote about why biotech needs to be rebuilt for the AI era. Today I'm sharing the next chapter: what the AI Scientist is, a blueprint for how it works, and why even Richard Feynman couldn't hack it in a wet lab.

[Anthropic @AnthropicAI]

Our Long-Term Benefit Trust has appointed Vas Narasimhan to Anthropic's Board of Directors.

Vas brings more than two decades of experience in medicine and global health, including as CEO of Novartis.

Read more: https://t.co/DSvtZUTone

[Patrick Collison @patrickc]

Maybe a very obvious point, but it only just struck me that, so far at least, intelligence seems to require four valence electrons.

[Gleb Kuznetsov @glebkuz]

Multiplexing can be thought of as "GPU-ification" of a complex biological system

Serial measurement becomes massively parallel

To turn biology digital, you need data at *scale* and *relevance*

The power of multiplexing is you get both.

[Eric Kelsic (he/him) @ekelsic]

We tested Claude Mythos on @Dyno_Tx's take home interview challenge, in collaboration with @AnthropicAI

This marks a new era for machine-guided design of biological sequences

Only a decade after we first began exploring how deep neural networks could help humans better understand and engineer proteins

Read more: https://t.co/4WxmWFLw09

[Eric Kelsic (he/him) @ekelsic]

Big news today from Dyno, licensing a muscle capsid to @AstellasUS . And amazing progress by the Dyno team solving gene delivery to skeletal muscle, one of gene therapy’s greatest challenges.

Way back in 2021, with great foresight, Astellas bet on the power of AI innovation by partnering with Dyno. This milestone in our collaboration is especially meaningful to me because it signals how AI-designed capsids can enable more effective and potentially safer therapeutic delivery to skeletal and cardiac muscle tissues, all at lower doses than existing AAV capsids.

By unlocking gene delivery for partners like Astellas, we move closer to a future where patients everywhere have access to the genetic medicines they need.

[Matthew Herper @matthewherper]

Anthropic Acquires Startup Coefficient Bio for About $400 Million https://t.co/jexMXFr094

[Jason Kelly @jrkelly]

Agree, this is an important point from @baym. A Waymo is an autonomous car even if a human is in the back seat telling it where to go. Same for an Autonomous Lab, scientists can tell it what protocols to do -- quick autonomous lab explainer in this video. It's really about solving for variable lab work, not about taking the scientist out of the loop.

[Patrick Boyle — e/🦀 @p_maverick_b]

I'm still obsessed with making better products with biology. Looking forward to sharing more of what we're working on soon!