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Introducing #mBER: our open-source AI library for de novo, format-aware antibody design. Paired with in vivo multiplexed screening, mBER forms Manifold Bio's direct-to-vivo drug discovery platform, bridging the gap between AI-guided design and biological translation.

Manifold Bio

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15,504 просмотров • 11 месяцев назад •via X (Twitter)

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We recently released a technical report highlighting how Isomorphic Labs’ drug design engine is achieving a step change in how we model complex biological mechanisms, consistently outperforming industry benchmarks. Read our blog to discover how we’re bridging the gap between structure prediction and rational drug design. You can find the link in the comments.

We recently released a technical report highlighting how Isomorphic Labs’ drug design engine is achieving a step change in how we model complex biological mechanisms, consistently outperforming industry benchmarks. Read our blog to discover how we’re bridging the gap between structure prediction and rational drug design. You can find the link in the comments.

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One of the biggest unsolved problems in making medicines is what comes after AI design. Gleb Kuznetsov, cofounder and CEO of Manifold Bio, is tackling the in vivo bottleneck. Screening hundreds of thousands of antibody designs in a single animal changes what’s possible in drug discovery. I’ve known Gleb since he was my TA at MIT, so it was really fun to have him on Transcribed. We talked about: - Why he left Google to start over in biology (literally showing up at george church’s lab and asking how he could be useful) - How 3 companies came out of his grad school lab bay - What it takes to build a true platform company - Where AI-driven drug discovery is actually headed

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10,659 просмотров • 7 месяцев назад

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45,399 просмотров • 6 дней назад

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14,618 просмотров • 6 месяцев назад

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61,608 просмотров • 3 месяцев назад

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Today marks a pivotal moment for Isomorphic Labs. We have secured $2.1 Billion in our second external funding round, led by Thrive Capital. They are joined at the table by Alphabet, GV and new investors MGX, Temasek, CapitalG and the UK Sovereign AI Fund. This milestone accelerates our ability to build the pioneering novel AI models that power our AI drug design engine (IsoDDE) and deploy them at scale: delivering scientific breakthroughs with a precision previously thought impossible, accelerating and expanding our pipeline of therapeutic programs toward the clinic. All with the ultimate goal of delivering life-changing new medicines to patients. Moving forward, we will scale our drug candidate pipelines across multiple therapeutic areas, expand our global footprint, and push the boundaries of frontier AI research to power our drug design engine. Deeply grateful to everyone sharing our vision to solve all disease with AI. Let’s build the future of medicine. Read the full announcement here:

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308,936 просмотров • 4 месяцев назад

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16,872 просмотров • 1 год назад

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Nabla Bio

180,030 просмотров • 3 месяцев назад

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Anindyadeep

23,484 просмотров • 1 год назад

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Alex Barashkov

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Web3 and AI are both hitting an inflection point at the same time. AI is redefining intelligence, automation, and how people interact with technology. Crypto is building the economic rails for that intelligence to coordinate, transact, and operate in open networks. Diksha Arden in conversation with nick (Co-Founder, Allora) on why the overlap between AI and crypto may become one of the biggest design spaces of the next decade — and why we’ve barely scratched the surface.

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BlockLayer Podcast

31,171 просмотров • 4 месяцев назад

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LinqAI

31,288 просмотров • 1 год назад

This is WILD! Nvidia just launched something that could compress the most expensive process in medicine from 12 years to 12 months. BioNeMo Agent Toolkit is an open, agent-ready platform that turns AI agents into autonomous scientific workers, giving them the ability to run real drug discovery workflows instead of just generating ideas. And more than 50 companies are already using it, including Anthropic, OpenAI, Eli Lilly, Databricks, Snowflake, Dassault Systèmes and Schrödinger. Here is what it actually does. Traditional drug discovery costs an average of $2.6 billion per drug and takes over a decade. Most of that time and money goes into screening millions of compounds, designing proteins that bind to disease targets and running countless lab experiments to validate whether something works. BioNeMo agents now do all of that computationally before a single lab experiment begins. The demo Nvidia shared makes the speed impossible to ignore. An agent was asked to design 10 protein binders for PD-L1, a critical cancer immunotherapy target and it completed the full design, co-folding, scoring, and 3D structural analysis on GPU in under 90 seconds. What used to require weeks of wet lab work and PhD-level expertise now runs as a callable tool inside an AI workflow. The four core capabilities are virtual drug screening, protein binder design, genomic analysis, and medical imaging each one compressing tasks that previously took weeks into minutes. The institutional validation behind this is unusually strong. Nvidia and Eli Lilly announced a joint investment of up to $1 billion over five years to build a co-innovation lab running entirely on BioNeMo. The University of Washington's Institute for Protein Design is already running RosettaFold3 at 2x faster performance than the prior generation. And the market this unlocks is enormous, and Nvidia is sitting right at the center of it. The AI drug discovery market is projected to grow from $2.9 billion in 2026 to $13.8 billion by 2033 and McKinsey estimates generative AI could deliver $60 to $110 billion in annual economic value to pharma. Bullish on drug discovery!

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Milk Road AI

23,215 просмотров • 3 месяцев назад

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claire vo 🖤

92,220 просмотров • 4 месяцев назад