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Tahoe Therapeutics (formerly Vevo)
Biotechnology Research
Mapping how chemistry perturbs biology to build a virtual model of the human cell. Used to be called Vevo Therapeutics.
About us
Tahoe Therapeutics is a biotechnology company using its in vivo drug discovery platform and next generation AI models to uncover better drugs for more patients. The company’s Mosaic platform is the first to make in vivo data generation scalable, with single-cell precision, to capture in vivo context of disease at the first step of drug discovery and to better represent patient diversity in drug response over current in vitro assays. Tahoe is using Mosaic to build the world’s largest in vivo atlas of how drugs interact with patient cells and training AI models on its data to find novel targets and drugs undetectable by other technologies. Located in South San Francisco, CA, Tahoe was founded by a team of inventors and thought leaders who have discovered drugs for “undruggable” targets and invented novel methods in genomics, computational biology, and chemistry. Learn more at www.tahoebio.ai.
- Website
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https://www.tahoebio.ai/
External link for Tahoe Therapeutics (formerly Vevo)
- Industry
- Biotechnology Research
- Company size
- 11-50 employees
- Type
- Privately Held
- Founded
- 2022
Employees at Tahoe Therapeutics (formerly Vevo)
Updates
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Tahoe Therapeutics (formerly Vevo) reposted this
Wonderful to host our friends from across the pond for our #TahoeDeepDive Hackathon!
Lots of people have been asking, so I thought I’d share some updates here: What am I doing in San Francisco? It’s basically a very lucky coincidence: Antoine Argante and I had just started working on a ML model that tries to predict the effect of some drugs on a cell - a virtual cell - using a new, huge dataset of single-cell mRNA measurements. Just to then, while doomscrolling Twitter (usually a much more negative experience), see that the startup that had published said dataset (Tahoe Therapeutics (formerly Vevo)) was hosting a hackathon, getting together a lot of like-minded researchers. So of course we had to apply, did so, and got in! They’re even paying for our travel costs, thanks! The hackathon starts in a few hours, and the winner gets 25.000$ in AWS credits. Wish us luck!
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Wonderful to host our friends from across the pond for our #TahoeDeepDive Hackathon!
Lots of people have been asking, so I thought I’d share some updates here: What am I doing in San Francisco? It’s basically a very lucky coincidence: Antoine Argante and I had just started working on a ML model that tries to predict the effect of some drugs on a cell - a virtual cell - using a new, huge dataset of single-cell mRNA measurements. Just to then, while doomscrolling Twitter (usually a much more negative experience), see that the startup that had published said dataset (Tahoe Therapeutics (formerly Vevo)) was hosting a hackathon, getting together a lot of like-minded researchers. So of course we had to apply, did so, and got in! They’re even paying for our travel costs, thanks! The hackathon starts in a few hours, and the winner gets 25.000$ in AWS credits. Wish us luck!
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Welcome to our newest addition Harper Green 👏 Harper will be joining our onsite lab, as a Research Associate. The Tahoe team is growing 🚀 👀
I am excited to share that after graduating from the University of Pennsylvania this spring, I will be joining Tahoe Therapeutics (formerly Vevo) as a Research Associate! I am incredibly grateful for the opportunity to continue pursuing my passion for oncology and drug discovery research as a member of the Mosaic team. Thank you to everyone who has supported me throughout this process-especially Johnny Yu, Nima Alidoust, Jesse Zhang, and Airol Anne Ubas. I can't wait to get started in San Francisco in July!
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Tahoe Therapeutics (formerly Vevo) reposted this
After the release of Tahoe-100M dataset we decided to dive deep and use this dataset for drug discovery. In only two months of experiments we've found a tremendous amount of insights that inform new programs, existing drugs, and new ways to use this data. Today we're launching the blog and in particular a story around Saquinavir - a Roche HIV antiviral that had been approved by the FDA and used for almost 30 years before being discontinued. Ultimately - it had cardiac toxicity, and the FDA acknowledged that the source of that tox was unknown. Until today. We show how and why it was toxic to the cardiovascular system. Because it was 1/~400 drugs in our Tahoe-100M, we were able to immediately understand the MOA in a way the field and biopharma had missed entirely. Read the full story at our blog! 👇
Today we’re launching The Tahoe Blog from Tahoe Therapeutics (formerly Vevo). In the same open-source spirit that led us to release Tahoe-100M—our gigascale, perturbative single-cell dataset—we’re now sharing many of the discoveries it has enabled (see link to the blog and the inaugural post in the comments). Tahoe-100M isn’t just a large dataset powering next-generation AI models in biology. It’s a new modality of data for discovery. Instead of designing a new experiment for every question, you can now ask hundreds—across thousands of perturbations and cancer models—using high-content, single-cell data already in hand. This changes the game. You can answer questions you weren’t even asking. Discoveries emerge before the hypothesis. It’s part of a larger shift: from hypothesis-driven to hypothesis-generating science. From narrow to panoramic views of biology. Think of it like the transition from RNNs to Transformers in AI. On the surface, they might look similar—but their ability to process all contexts at once unlocked entirely new capabilities. Tahoe-100M does something similar for biology. Measuring how a handful of cancer models respond to a drug is common. But scaling that to thousands of cancer models and drugs—with the resolution of single-cell data—reveals mechanisms and relationships you’d otherwise miss. That’s what makes this data more than the sum of its parts. In this blog, we’ll highlight discoveries that surprised even us—insights hiding in plain sight, enabled only by this new scale and structure of data. We’re sharing them to spark new questions, inspire new therapeutic directions, and ultimately help patients. We begin with one such finding: We uncovered previously unknown mechanisms associated with Saquinavir—mechanisms that could have predicted the cardiovascular toxicity that was only detected during clinical use. The drug, developed by Roche, was later discontinued in the US.
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Tahoe Therapeutics (formerly Vevo) reposted this
Today we’re launching The Tahoe Blog from Tahoe Therapeutics (formerly Vevo). In the same open-source spirit that led us to release Tahoe-100M—our gigascale, perturbative single-cell dataset—we’re now sharing many of the discoveries it has enabled (see link to the blog and the inaugural post in the comments). Tahoe-100M isn’t just a large dataset powering next-generation AI models in biology. It’s a new modality of data for discovery. Instead of designing a new experiment for every question, you can now ask hundreds—across thousands of perturbations and cancer models—using high-content, single-cell data already in hand. This changes the game. You can answer questions you weren’t even asking. Discoveries emerge before the hypothesis. It’s part of a larger shift: from hypothesis-driven to hypothesis-generating science. From narrow to panoramic views of biology. Think of it like the transition from RNNs to Transformers in AI. On the surface, they might look similar—but their ability to process all contexts at once unlocked entirely new capabilities. Tahoe-100M does something similar for biology. Measuring how a handful of cancer models respond to a drug is common. But scaling that to thousands of cancer models and drugs—with the resolution of single-cell data—reveals mechanisms and relationships you’d otherwise miss. That’s what makes this data more than the sum of its parts. In this blog, we’ll highlight discoveries that surprised even us—insights hiding in plain sight, enabled only by this new scale and structure of data. We’re sharing them to spark new questions, inspire new therapeutic directions, and ultimately help patients. We begin with one such finding: We uncovered previously unknown mechanisms associated with Saquinavir—mechanisms that could have predicted the cardiovascular toxicity that was only detected during clinical use. The drug, developed by Roche, was later discontinued in the US.
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Wonderful coverage of our team's work by Forbes. And huge gratitude to our friends at Parse Biosciences and Ultima Genomics who partnered with us in generating Tahoe-100M. Alex Rosenberg, Charles Roco, Gilad Almogy, Eric Jaschke, CFA, Julie Gerardi, David Peoples
It's not every day that you wake up to a Forbes article covering the great work of your team. We at Tahoe Therapeutics (formerly Vevo) open sourced Tahoe-100M to start a movement in open data in biology. Thanks Amelia Palermo, PhD for taking note of that and the thoughtful piece. "By providing unprecedented access to high-quality, large-scale single-cell data, Tahoe is promoting a more open, collaborative approach to scientific discovery. ... The release of Tahoe 100M may represent a first step towards creating the “internet of biology”, laying the foundation for the development of truly transformative AI models to integrate and understand cellular biology and drug development at high speed."
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We are now Tahoe Therapeutics! See our new website: tahoebio.ai
Vevo Therapeutics is now Tahoe Therapeutics. We loved our old name, Vevo, and chose it for its allusion to vivo, life. But a (much, much, much) bigger company was also using the name for something unrelated and twisted our arm to change it. We could have fought; but, instead of paying lawyers, we opted to use the money for what actually matters: generate data, build AI and cure cancer. Tahoe was the natural choice. Our Tahoe-100M set a new standard in scale, catalyzed a new movement for open source data in biology, and helped create a new push towards building virtual cell models. This fully captures our essence: Shoot for the moon and build openly. That’s why we are proud to adopt it as our insignia going forward.
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Last day to apply for the #TahoeDeepDiveHackathon! Sign up now: https://lnkd.in/gr2ATiNc 📅 May 9-11th in SF. 📢 Winners will be announced April 9th. 👥 40 will be selected, $400 voucher for 10 to travel to SF. 🏆 $25K AWS credit to the winner, $10K and 5K to 2nd and 3rd.
Many asked us to extend the deadline for our Hackathon to build on Vevo Therapeutics Tahoe-100M dataset. The new deadline is April 7th to give folks the weekend for submissions. And thanks Lambda for generously offering to provide participants even more compute, adding to the generous contribution from Hugging Face. Details in comments.
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Thank you to all the judges & mentors participating in our #TahoeDeepDiveHackathon 💙 If you're interested in attending, the deadline to apply is Apr 4, 2025! Sign up sheet: https://lnkd.in/gukZUhgM Participants will be announced on April 8th.
Meet the judges & mentors for the Tahoe Deep Dive Hackathon. And thanks Amazon Web Services (AWS) for offering the prize: $25K AWS credits to winner, 10K & 5K to 2nd and 3rd. A short DM with Clem Delangue 🤗and now an entire community coming together! Deadline to apply: Apr 4th, Link in comments. Join us! We will select 40 participants, provide compute and a $400 travel voucher for 10 travelers.
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