🏳️🌈 🧬AIxBio @EdisonSci, formerly @FutureHouseSF @broadinstitute @HSCRB, @MITdeptofBE, @GeorgiaTech. he/him
Boston, MA
Joined December 2018
- Tweets196
- Following656
- Followers526
- Likes1.7K
Blake Lash retweeted
Writing an Investigational New Drug (IND) application is a major hurdle for drug developers. It can take a team of specialists three to four months, and mistakes can trigger protocol amendments or clinical holds.
In June, we started working with Population Health Partners (PHP) to leverage specialized Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
Blake Lash retweeted
At FutureHouse, we focused on scientific discovery. However, if we want to actually accelerate progress in medicine, we need to work across the entire R&D stack. We are now deploying specialized Kosmos agents for Clinical Protocol Design and Regulatory Authoring to several of our partners, which can cut months off the amount of time needed to get molecules into the clinic, save companies tens of millions of dollars, and dramatically reduce the likelihood that submissions get stuck at the FDA. Super excited to be able to share this story now, thanks to our work with Population Health Partners, one of the best drug developers in the world and a fantastic development partner for us.
The AI-native pharma stack is here now, and the future of medicine is around the corner. Read more:
xitter.cf/EdisonSci/status/21053…
Writing an Investigational New Drug (IND) application is a major hurdle for drug developers. It can take a team of specialists three to four months, and mistakes can trigger protocol amendments or clinical holds.
In June, we started working with Population Health Partners (PHP) to leverage specialized Kosmos Clinical Protocol Design (“CPD”) and Kosmos Regulatory Authoring (“RA”) products to support PHP’s process of IND preparation.
Since then, specially trained Kosmos products produced a first acceptable draft of the Nonclinical Overview in 4.2 hours, against 100 hours of expert time, flagged an error that roughly fifteen human reviewers missed, and authored 70% of the text in a Pre-IND Briefing Meeting Request submitted to FDA.
PHP is now bringing Kosmos products to a second program and expects to complete IND preparation in as little as 1 month, instead of the 4 month industry standard.
PHP's experts can spend their time reviewing and deciding, not just drafting. The time recovered by Kosmos products means that drugs could make their way to patients faster.
Blake Lash retweeted
ʙɪɴᴅᴄʀᴀꜰᴛ2 is out, and we're not waiting for the paper. The full code drops today, free for academic and industry use.
We're releasing it early so you can start designing right now, and bring its full power to the current Adaptyv competition.
github.com/PacesaLab/BindCra…
Blake Lash retweeted
Join the Edison team at our AI Biotech Block Party, co-hosted with @multiplylabs!
The evening will include a fireside chat with @FredParietti, CEO of Multiply Labs, and @andrewwhite01, CTO of Edison, on the future of AI across drug discovery, development, and manufacturing.
Plus food, drinks, lab tours, and demos!
Blake Lash retweeted
Introducing BixBench3, our latest eval for language models in science and the first eval to measure the ability of models to produce the analyses underpinning entire biology papers from raw data.
BixBench3 evaluates 13 frontier models on 20 paper-derived tasks, using datasets up to 241 GB.
Each task mirrors how scientists often use agents today: setting a research objective and designing a methodological plan, then delegating implementation to the agent.
The best model reproduced 48% of the requested artifacts on average.
Agents are starting to approach research study-scale capabilities, but there is still plenty of work to do.
Blake Lash retweeted
Edison is officially in New York!
We opened the doors to our new SoHo office this week, and we’re so excited to give our rapidly growing NYC team a place to call home.
We’re hiring in New York, San Francisco, and beyond. Come join us!
Blake Lash retweeted
We are hiring @FutureHouseSF! We're looking for an AI engineer that can support our fellowship program and the non-profit mission. Great opportunity to work with the FutureHouse team!!
jobs.ashbyhq.com/Edison%20Sc…
Blake Lash retweeted
Data that still lives rent free in my head after CSHL AI in Bio:
In silico prediction of the ten-subunit complex that appears to control sperm-egg fusion. Done with AlphaFold Multimer. Absolutely stunning.
This complex is so gnarly that this group hasn't been able to empirically validate the structure yet, but every single line of experimentation supports this structural model being correct.
It's like the AI model is a molecular microscope that can see what we can't even detect.
For me, it reframed the upper bounds of where molecular machine learning is going in next ~2-3 years. We're just getting started!
Blake Lash retweeted
We've released a new open-weights vLLM for reading chemical structure patents. This is a hard problem. These "Markush" structures are like graph regex: patterns that match many molecules. We used autoresearch and I expect many new models like this to emerge soon in science 1/4
Blake Lash retweeted
Today, we're announcing Edison Advances, a home for our research announcements, engineering blogs, open-weights models and benchmarks.
At Edison, we’re building Kosmos, an AI Scientist, to solve foundational research problems and make truly novel discoveries across scientific domains.
Alongside that work, we’re developing better ways to measure and evaluate AI scientists, push their ability to work on long-horizon tasks, and identify gaps in their reasoning.
Edison Advances brings our existing work together in one place and we will use it to publish new work as our research progresses.
Follow along as the work develops, and get in touch if you’re interested in contributing.
Blake Lash retweeted
At Edison, we are on a mission to leverage AI to prevent or cure all diseases.
Today, we are announcing a critical step: our first partnership using our AI scientist, Kosmos, to launch new biotech companies.
Many of the most transformative new medicines begin life in biotech companies rather than big pharmas.
We are partnering with Population Health Partners (PHP) to deploy Kosmos across their company creation pipeline. Kosmos will assist in the creation of PHP’s companies, allowing us to bring more medicines to patients.
PHP has an outstanding track record of incubating successful biotech companies like @MetseraInc (acquired by @pfizer in a $10B deal), and The Medicines Company (acquired by @Novartis for $9.7B), to name just two. With PHP, we will focus on biotechs treating population-scale diseases like cardiovascular disease and obesity.
If we can scale up the process of launching Metsera-style companies, we have an opportunity to transform medicine in the coming years.
Blake Lash retweeted
AI is incredible for speeding up science, but in an outbreak response, one data error can have life-or-death consequences.
Super proud to share our work showing how deterministic retrieval layers bridge this gap to guarantee 100% reliable workflows for global health security!
New Science Blog: Why has AI advanced faster in coding than in biology?
To agents, bio databases are like cities built before cars—maddening to drive in because they're designed for different traffic.
How do we build infrastructure agents can use?
anthropic.com/research/agent…
Blake Lash retweeted
I wrote up some thoughts on AI agents and biological databases for the @AnthropicAI Science blog. 🚗🧬
Based on research with @ferbsx and @PardisSabeti
New Science Blog: Why has AI advanced faster in coding than in biology?
To agents, bio databases are like cities built before cars—maddening to drive in because they're designed for different traffic.
How do we build infrastructure agents can use?
anthropic.com/research/agent…
Checkout this blog post by the fantastic @NeuroLuebbert where she discusses why agents have such a hard time accessing databases meant for human users, and what the implications are as model capabilities grow.
1/
New Science Blog: Why has AI advanced faster in coding than in biology?
To agents, bio databases are like cities built before cars—maddening to drive in because they're designed for different traffic.
How do we build infrastructure agents can use?
anthropic.com/research/agent…
I particularly like her point "Still, even if an agent can do it, that doesn't mean the task should be handled (and reinvented) by an agent every time." Just because an agent CAN write code to do something, doesn't mean it should need to.
2/
Spent my PhD on delivery and it’s still the hardest unsolved problem in therapeutics. Great to see @deliverome go after it! Congrats to the team!
AI has transformed how we design therapeutics.
But targeted delivery is still an expensive guessing game.
Today @BobbyHollings and I are launching @deliverome with @beckypferdehirt and @radialscience at @AsteraInstitute, to fix that. 🧵
Blake Lash retweeted
A big day for multi-agent AI to accelerate biomedical discovery, hypothesis generation, designing experiments with proof points of new candidate drugs (cancer, fibrosis, macular degeneration, antimicrobial resistance, and more)
2 @Nature reports @GoogleDeepMind @FutureHouseSF
nature.com/articles/s41586-0…
nature.com/articles/s41586-0…
Blake Lash retweeted
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.
