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Today we release Rhaister, an elegant statistical model that predicts drug phenotypes in new contexts w/ accuracies comparable to experimental assays. And dropping Emerald Bay, a 2M cell dataset measuring long time-course phenotypes across 1000s of drug-cell line interactions.

62,258 次观看 • 1 个月前 •via X (Twitter)

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To replace animal testing with AI, we need MASSIVE human datasets. Today, we're thrilled to share Axiom's new data exploration tool, providing the ability to visually explore the world's largest primary human liver toxicity dataset. Built with Axiom's proprietary wetlab protocols, our dataset includes detailed liver toxicity profiles for over 100,000 distinct molecules. The key to this dataset is our ability to do high-throughput, multiplexed high-content screening with primary human liver cells. Traditionally, toxicity assays either sacrifice throughput or sacrifice biological relevance (using easy-to-grow immortalized cell lines instead of real human cells). We managed to combine throughput, physiological relevance, and multiplexing in one platform. The assays run in a high throughput format using automation, meaning thousands of compound-dose conditions can be tested in one experiment. We achieved this using pooled primary human hepatocytes, which are often fragile and expensive. By systemizing our automation and quality control processes, we were able to run over 120+ batches on the same donor pool with incredible reproducibility and consistency. We did this while integrating many readouts per well, whereas many existing toxicity assays only do a single readout. Our multiplexed approach provides far more data per experiment enabling us to measure 10-20 different toxicity phenotypes such as apoptosis, necrosis, mitochondrial fission, endoplasmic reticulum stress, stress granule formation, microtubules, and more all from a single well on a 384-well plate! The combination of scale, high content information, and data quality is exactly what is needed to train highly accurate AI models in biology. If you're interested, please explore the dataset in the comments below and let me know if you want to chat about the details!

Brandon White

25,117 次观看 • 1 年前

HOLY CRAP! I can't tell you how big this is for the medical community and drug discovery: Google Announces AlphaFold 3 AI. Details: Enhanced Molecular Prediction: AlphaFold 3 predicts the structure and interactions of all life's molecules, including proteins, DNA, RNA, ligands, and more, with unprecedented accuracy. Improved Interaction Accuracy: For protein interactions with other molecule types, AlphaFold 3 offers at least a 50% improvement over existing methods, and doubles the accuracy for some critical interactions. Transformative Potential for Science and Medicine: The model aims to deepen our understanding of biological processes and significantly advance drug discovery efforts. Accessibility for Researchers: AlphaFold 3's capabilities are largely accessible for free via the AlphaFold Server, providing an essential tool for scientific research. Drug Design Innovation: AlphaFold 3 is utilized by Isomorphic Labs in collaboration with pharmaceutical companies to accelerate drug design, potentially leading to new treatments for various diseases. Foundation in AlphaFold 2: Building on the breakthroughs of AlphaFold 2, this version extends its scope beyond proteins to a wide range of biomolecules, enhancing its utility in scientific research and application. Global Accessibility and Educational Support: The AlphaFold Server is a free platform for non-commercial research worldwide, supported by educational resources to foster wider adoption and innovation. Empowering Rapid Scientific Advancements: By making detailed molecular interactions easily accessible, AlphaFold 3 enables faster hypothesis testing and could reduce the time and cost typically associated with experimental protein-structure prediction. Responsible Development and Deployment: DeepMind has engaged with domain experts to assess the impacts and potential risks of AlphaFold, ensuring its responsible use in the scientific community. Broad Implications for Biology:AlphaFold 3 helps reveal complex cellular mechanisms and interactions, offering insights that could lead to improved agricultural crops, enhanced understanding of diseases, and novel therapeutic strategies.

Brian Krassenstein

258,615 次观看 • 2 年前

The most detailed 3D reconstruction of a cell ever created. Blows my mind every time. But what exactly are we looking at here? The average human cell contains: ~ 15-20 total distinct organelle types, totalling between ~1-10 million working together per cell. All these nano-machines in the cell are made up of proteins. ~ 8,000-10,000 distinct types of unique proteins, adding up to between 40 million - 10 trillion total proteins making up all those cellular systems. ~ 10,000 - 15,000 distinct types of RNA shuttling information around the cell, totalling up to ~10 million RNA molecules moving around the cell simultaneously. ~ Billions of Lipid molecules packed together into the cell membrane, which is also packed tightly with millions more protein-based nano-machines. And let's not forget billions of lines of DNA information to build and run it all. That's TRILLIONS of of individual molecular pieces working together to make a single cell function. That means there is more complexity in a single cell than humanity's largest cities. And people still believe this wasn't Divinely Designed. This is God's Glory on Display. But to make the point. A cell couldn't have evolved from some nebulous simpler "protocell" because even the simplest cells still require massive complexity. The "simplest" cell ever created was engineered by scientists knocking out pieces of a functional cell until it stopped functioning. Here is what they found is the absolute necessary minimal requirements of a cell to function: - Over ~531,000 lines of coded DNA information - 473 total genes to create hundreds of unique protein products (they later added 19 genes back in because the cell was so weak) - Hundreds of thousands of total proteins all working together - Extensive regulatory networks guiding all these interactions If the cell doesn't have all these systems in place, from the start... it doesn't live. Cell rely on an intricate network of complex systems, which are themselves built from complex interconnected pieces woven together into an incomprehensibly complex web of functionilty. Only intelligence has ever been observed creation vast interconnected systems like this. Life was clearly Created. It couldn't happen any other way.

Divinely Designed

165,561 次观看 • 1 个月前