Latest news with #TahoeTherapeutics
Business Wire
a day ago
- Business
- Business Wire
Tahoe Therapeutics Raises $30M to Build World's Largest Dataset for Training AI Models of Human Cell
SAN FRANCISCO--(BUSINESS WIRE)-- Tahoe Therapeutics today announced $30 million in new funding to build the definitive foundational dataset for training Virtual Cell Models. With this, the team will generate one billion single-cell datapoints, mapping one million drug-patient interactions, a scale previously impossible. The dataset will support the discovery of new precision medicines for cancer and beyond. Tahoe will also select a single partner to share the data and accelerate translation to clinical outcomes. The round was led by Amplify Partners, joined by a distinguished group of investors including Databricks Ventures, Wing Venture Capital, General Catalyst, Civilization Ventures, Conviction, Mubadala Capital Ventures, and AIX Ventures. The raise follows the release of Tahoe‑100M, the world's first gigascale perturbative single-cell dataset, which has become foundational for teams building virtual cell models, ranging from major AI labs to focused research institutions. Open-sourced just a few months ago, Tahoe-100M has been downloaded nearly 100,000 times. The dataset and the models trained on it have already led to the discovery of promising new therapeutic candidates for major cancer subtypes as well as novel targets across multiple modalities. Tahoe is now expanding on that foundation: the company plans to generate one billion single-cell datapoints, mapping how tens of thousands of drug molecules interact with human biology. This new dataset will expand the boundaries of biological foundation models, aiming to reduce clinical trial failure rates and accelerate the development of precision medicines. 'Building Tahoe-100M required us to invent new ways to generate single-cell data,' said Nima Alidoust, co-founder and CEO of Tahoe Therapeutics. 'Now, we're applying that superpower to go 10x further. This next phase is about using these massive datasets to bring about the GPT moment for AI models of human cells, translating insights to clinical readouts, and developing new medicines with much lower clinical failure rates.' With the new capital, Tahoe is advancing its own therapeutic programs toward the clinic, while also launching a new model of strategic collaboration. The company will select a single partner, a pharmaceutical or AI company with complementary strengths, to access the forthcoming dataset. Together, the goal is to develop the first medicines powered by virtual cell models, combining Tahoe's data with the partner's clinical or modeling expertise. 'While structural models have accelerated molecular design, they rarely translate to clinical success — a problem that remains one of the biggest challenges in drug development,' said Sunil Dhaliwal, General Partner at Amplify Partners. 'Tahoe Therapeutics is uniquely positioned to move the industry past this bottleneck by generating massive drug-patient datasets and training high-dimensional, cell-based AI models. We're proud to back this exceptional team as they combine biology and computation to accelerate clinical impact.' Tahoe founders, Nima Alidoust, Johnny Yu, Hani Goodzari, and Kevan Shokat hold deep experience in single-cell genomics, ML, and drug discovery. The company's platform makes large-scale, single-cell drug screening across diverse patient contexts not only possible, but scalable. Built on scientific breakthroughs at UCSF, Tahoe is creating the raw materials needed to train disease-relevant foundation models of human cells and chart a new course for precision medicine. To learn more, visit: About Tahoe Therapeutics Tahoe Therapeutics is building AI-powered models of the human cell to design better drugs for more patients. Its technology platform generates large-scale, perturbative single-cell datasets that enable a new generation of biological foundation models. Based in South San Francisco, Tahoe was founded by a team of scientists and technologists advancing the frontiers of drug discovery, genomics, and machine learning.
Forbes
a day ago
- Business
- Forbes
Biotech Startup Tahoe Therapeutics Raised $30 Million To Build AI Models Of Living Cells
Tahoe cofounders (L-R): Kevin Shokat, Nima Alidoust, Johnny Yu and Hani Goodarzi Tahoe Therapeutics O ne of the holy grails of biology is digitally simulating a living cell. If researchers can use computers to more accurately understand how new medicines would react in the body, that could give them greater confidence when they're tested on animals and humans. But while large language models have led to breakthroughs in modeling how proteins act, applying the same technology to simulating all the complexities of an entire cell hasn't been as fruitful. There's simply not enough data. But in February of this year, a startup named Tahoe Therapeutics got one step closer to that goal with the release of Tahoe-100M, a collection of 100 million different datapoints showing how different kinds of cancer cells responded to interactions with over 1,000 different molecules. This type of data–called pertubations–is crucial to training AI models, because information on how cells respond to various molecules improves an algorithm's ability to predict how they'll be affected by others. 'We believe that the Tahoe-100M was a Mars landing moment for single-cell datasets,' Tahoe CEO Nima Alidoust, 39, told Forbes . The company was able to build this dataset less than three years after it was founded thanks to its Mosaic platform, which lets the company take 'cells from many different types of patients, from all different organs and then put them together,' rather than the conventional techniques, which test cells from only one individual at a time, explained CSO and cofounder Johnny Yu. 'So every time we run an experiment, we're generating massive single cell atlases of which drugs affect which patients.' 'Our core superpower is the ability to generate the massive datasets required for virtual cell models,' Alidoust said. The ability to scale that data production quickly, he added, is Tahoe's 'distinguishing factor' compared to other companies working on AI for drug discovery. It's also foundational to the company's own goal of building virtual cell models and using them to find new treatments for cancer and other diseases. Today, Tahoe announced it has raised $30 million in new venture funding, led by Amplify Partners. Other investors include Databricks Ventures, Wing Venture Capital, General Catalyst, AIX Ventures, Mubdala Ventures, Civilization Ventures and Conviction. The investment brings the company's total funding to $42 million and its valuation to $120 million. Poor AI predictions have been a source of constant frustration in biotech, said Krish Ramadurai, a partner at AIX Ventures who also sits on Tahoe's board. 'These AI algorithms keep recommending stuff, and then when you go to test it in the wet lab, it all sucks,' he said. The data Tahoe can generate, he said, makes a crucial difference for the accuracy of new models. Just a few months after Tahoe published its 100 million point dataset, the non-profit research organization Arc Institute released an open-source virtual cell model, State, which used Tahoe-100M as part of its training data. When benchmarked, Arc found that it has twice the accuracy of other AI models–and also beat out the simpler machine learning programs that had previously trounced other foundation models. That's a testament to nearly a decade's worth of work for Tahoe cofounder Yu, 34, who developed the underlying technology for Mosaic, while working in the lab of biochemistry and biophysics professor Hani Goodarzi at the University of California San Francisco. Alidoust first met Goodarzi, 41, when they were classmates at Princeton. The pair reconnected in 2022 to discuss the idea of founding a company to build virtual cell models. Goodarzi said that an essential piece of such a company would be large-scale data collection, so he brought in Yu. A month later, the three of them cofounded Tahoe–then called Vevo Therapuetics–along with UCSF researcher Kevin Shokat, 60. The company raised a $12 million seed round in December 2022. The name was changed from Vevo to Tahoe in April of this year after a legal challenge. With new capital in hand, Tahoe is now focused on building a dataset with over a billion single-cell datapoints to power its own virtual cell models. Armed with its own models and proprietary data, the company is accelerating the development of new medicines to fight cancer. Alidoust said Tahoe currently has a drug candidate against 'a major cancer subtype' with which it's conducting the studies required by the FDA to start testing on humans. Additionally, Alidoust said, although the company intends to keep its larger datasets proprietary, it does plan to select either a major pharmaceutical company or AI company to share data with. The idea would be to collaborate on either developing new medicines or new drug discovery AI models, giving Tahoe 'more shots on goal' for gaining revenue. That partner hasn't been selected yet, he said, but it is currently working with different companies on smaller projects. In the meantime, he said, the company will keep working on generating more data for its AI models and proving out its technology. 'We say in the company that this is morning in biology,' he said. 'We are building. And we hope others are going to build with us as well.' MORE AT FORBES: Forbes How AI And Mini-Organs Could Replace Testing Drugs On Animals By Alex Knapp Forbes MIT Spinout Strand Therapeutics Raises $153 Million To Make Cancerous Tumors Light Up By Amy Feldman Forbes This AI Founder Became A Billionaire By Building ChatGPT For Doctors By Amy Feldman Forbes As Trump Cuts Cancer Research Funding, Billionaire Sean Parker Wants To Scale It Up By Alex Knapp
Forbes
25-04-2025
- Health
- Forbes
This Dataset can Ignite An AI Revolution In Cancer Research
Imagine accelerating the discovery of new therapeutics through the development of AI models for mining drug-cell interactions at unprecedented resolution. Tahoe Therapeutics (formerly Vevo) new release may have redefined the race to map the human cellular landscape in cancer. AI and data driven drug-discovery. getty In an unusual move, Tahoe Therapeutics has released 'Tahoe 100M', a massive open-source dataset encompassing 100 million single-cell data points and 60,000 experiments, mapping 1,100 drug treatments across 50 cancer types. Tahoe 100M brings a 50-fold increase in publicly available perturbational single-cell data, positioning itself in the world's largest single cell repository. Tahoe 100M includes what researchers call 'single cell transcriptomics profiles', i.e., a comprehensive list of gene expression data for each individual cell. These 'profiles' provide a snapshot of each cell and how it responds to drug perturbations, portraying a more accurate mosaic of tumor cell interactions. Thus, researchers can use the mosaic to understand the behavior of individual cells and define the impact of cancer heterogeneity on the development of effective treatments. Dr. Johnny Yu, co-founder and technology platform developer at Tahoe, describes the company's unique 'Mosaic Platform', used to generate the dataset, as 'a technology that creates a 'mosaic tumor' that allows testing drugs across multiple cancer types simultaneously and at high throughput'. The 'Mosaic Platform', combined with single-cell resolution, yields 'approximately 20,000 measurements across all protein-coding genes per assay" he continues, 'offering a unique level of cellular granularity'. Using this approach ensures the dataset's immediate practical value, making it a precious resource for AI modeling. Tahoe Therapeutics and the Arc Institute have recently partnered in the launch of the Arc Virtual Cell Atlas: the most comprehensive and diverse public database of single-cell level transcriptomic data across a wide range of perturbations. These data can be obtained for free and used for further analysis and AI modeling. Just in the last month, the dataset has been downloaded almost 11,000 times on Hugging Face, a data sharing platform. Dr. Hani Goodarzi, Tahoe's scientific co-founder, Core Investigator at the Arc Institute and UCSF Professor, puts the dataset into context: 'Tahoe's 'Mosaic Platform' helped minimize 'batch effects', which can make single cell data difficult to compare, offering a more consistent and reliable resource for modeling'. While recent technological advances in using AI, such as the AlphaFold 3 model, have fundamentally unlocked the ability to predict protein structures and drug interactions, understanding patient biology complexity remains a critical challenge. At this intersection, the potential impact of single-cell perturbation datasets on drug discovery can be profound. 'Tahoe 100M enables the building of comprehensive models that can predict drug interactions across diverse patient populations,' states Dr. Nima Alidoust, co-founder and CEO at Tahoe. To develop effective cancer treatments, we need to understand biological interactions beyond simple protein binding. Datasets such as Tahoe 100M account for patient complexity from the earliest stages of drug discovery, thus, having the potential to unlock novel 'AI-first' approaches to drug discovery. Dr. Bo Wang, chief AI scientist for the University Health Network in Canada and among the leading experts in AI for biology and healthcare, believes that the release of this dataset is 'a big deal for the field'. His lab developed the single-cell GPT model (scGPT), one of the first attempts to apply AI large language modeling to single-cell data. This model was trained using 33 million human cells from tissues such as heart, brain, blood, etc. and allows accurate cell type classification in single-cell studies. He believes that 'the Tahoe 100M dataset significantly extends our ability to train AI models to learn more nuanced, dosage-dependent cellular responses in perturbation studies across different cancer types, which help portray more generalizable AI models for drug development'. He is confident that such models will provide more accurate means for early patient stratification and for in silico screening of patient response for precise treatment selection. AI modeling of single cell networks. getty The generous release of Tahoe 100M is a potential turning point for deciphering cancer vulnerabilities at scale and can trigger an open-source data sharing momentum in cancer research. By providing unprecedented access to high-quality, large-scale single-cell data, Tahoe is promoting a more open, collaborative approach to scientific discovery. This is important as recent reports warn about thousands of 3D protein structures and other disease-relevant big datasets held within the vaults of private companies. 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.
