OpenAI Foundation science!
San Francisco, CA
Joined June 2015
- Tweets2.1K
- Following1K
- Followers8.6K
- Likes6.9K
Jacob Trefethen retweeted
We are also looking for a (remote optional) podcast producer to take Hard Drugs with @salonium and @JacobTref to the next level.
If you’re eager to turn long, deeply researched discussions on medical innovation into a full-fledged podcast listened to by some of the smartest people around, DM me as well!
Jacob Trefethen retweeted
John Urschel just showed that the growth factor for Gaussian elimination with partial pivoting is ~n^{1/2} with high probability, resolving a long-standing conjecture of Nick Trefethen! arxiv.org/abs/2610.06785
Jacob Trefethen retweeted
Hear, hear! Let's switch off misbehaving genes and kick some diseases' butts over the next decade
I believe that 1) siRNA will change medicine, with new treatments for tens of diseases, 2) tens of millions of people will take an siRNA drug in the 2030s, with some chance of >100M people, and 3) I will have taken at least one siRNA drug within a decade.
I have never worked on siRNA, and I also don't think of myself as a hypester. So, why the confidence? There's the technical answer, then the structural answer.
The technical answer is that siRNA has several attractive properties as a drug modality, and enough of the chemistry problems have been solved that I'm confident more drug approvals are on the way (though there are many important unsolved problems left, e.g. in delivering siRNA to organs other than the liver). The four most attractive properties are that with siRNA you can reduce production of previously undruggable proteins by going after the RNA that codes for them; they’re “programmable” to a gene/protein you’re going after; siRNA can last long, with slow release inside cells; and siRNA drugs have the potential to be relatively cheaply made and self-administered.
The structural answer, I believe, is biotechnology’s combination of long timelines with particularly un-juicy, hard-to-remember concepts. If something takes 20 years, you can often spot it 10 years in -- but when it’s an acronym and involves chemical conjugation steps, it’s hard to remember to care. Many important ideas in biology are messy and technical and, unless you've caught the bug (intellectual or literal), boring. That means there are many important secrets lying in plain sight, as per @nayafia's last book.
While disagreements and unknowns remain, it is not particularly controversial among scientists that siRNA holds a lot of promise (alongside some realised promise already!) -- and, yet, most people who will benefit from siRNA drugs in the 2030s have never heard of it.
(PS: given my job involves stewarding charitable dollars related to science, I don’t invest in individual pharma/biotech stocks personally; this post isn’t about the financial prospects of particular companies.)
Jacob Trefethen retweeted
I am very siRNA-pilled. Looking forward to seeing forthecoming data on intranasal siRNA for the prevention of infection by respiratory pathogens.
PS - siRNA is also very promising for biosecurity! It's well-suited for sequence-to-antiviral approaches and has many advantages over traditional antivirals and vaccines.
I believe that 1) siRNA will change medicine, with new treatments for tens of diseases, 2) tens of millions of people will take an siRNA drug in the 2030s, with some chance of >100M people, and 3) I will have taken at least one siRNA drug within a decade.
I have never worked on siRNA, and I also don't think of myself as a hypester. So, why the confidence? There's the technical answer, then the structural answer.
The technical answer is that siRNA has several attractive properties as a drug modality, and enough of the chemistry problems have been solved that I'm confident more drug approvals are on the way (though there are many important unsolved problems left, e.g. in delivering siRNA to organs other than the liver). The four most attractive properties are that with siRNA you can reduce production of previously undruggable proteins by going after the RNA that codes for them; they’re “programmable” to a gene/protein you’re going after; siRNA can last long, with slow release inside cells; and siRNA drugs have the potential to be relatively cheaply made and self-administered.
The structural answer, I believe, is biotechnology’s combination of long timelines with particularly un-juicy, hard-to-remember concepts. If something takes 20 years, you can often spot it 10 years in -- but when it’s an acronym and involves chemical conjugation steps, it’s hard to remember to care. Many important ideas in biology are messy and technical and, unless you've caught the bug (intellectual or literal), boring. That means there are many important secrets lying in plain sight, as per @nayafia's last book.
While disagreements and unknowns remain, it is not particularly controversial among scientists that siRNA holds a lot of promise (alongside some realised promise already!) -- and, yet, most people who will benefit from siRNA drugs in the 2030s have never heard of it.
(PS: given my job involves stewarding charitable dollars related to science, I don’t invest in individual pharma/biotech stocks personally; this post isn’t about the financial prospects of particular companies.)
Jacob Trefethen retweeted
It’s true but but I’d drop the “si” and say RNA drugs will change medicine since this criteria applies to mRNA already, and likely will apply to other forms of RNA medicine in dev
I believe that 1) siRNA will change medicine, with new treatments for tens of diseases, 2) tens of millions of people will take an siRNA drug in the 2030s, with some chance of >100M people, and 3) I will have taken at least one siRNA drug within a decade.
I have never worked on siRNA, and I also don't think of myself as a hypester. So, why the confidence? There's the technical answer, then the structural answer.
The technical answer is that siRNA has several attractive properties as a drug modality, and enough of the chemistry problems have been solved that I'm confident more drug approvals are on the way (though there are many important unsolved problems left, e.g. in delivering siRNA to organs other than the liver). The four most attractive properties are that with siRNA you can reduce production of previously undruggable proteins by going after the RNA that codes for them; they’re “programmable” to a gene/protein you’re going after; siRNA can last long, with slow release inside cells; and siRNA drugs have the potential to be relatively cheaply made and self-administered.
The structural answer, I believe, is biotechnology’s combination of long timelines with particularly un-juicy, hard-to-remember concepts. If something takes 20 years, you can often spot it 10 years in -- but when it’s an acronym and involves chemical conjugation steps, it’s hard to remember to care. Many important ideas in biology are messy and technical and, unless you've caught the bug (intellectual or literal), boring. That means there are many important secrets lying in plain sight, as per @nayafia's last book.
While disagreements and unknowns remain, it is not particularly controversial among scientists that siRNA holds a lot of promise (alongside some realised promise already!) -- and, yet, most people who will benefit from siRNA drugs in the 2030s have never heard of it.
(PS: given my job involves stewarding charitable dollars related to science, I don’t invest in individual pharma/biotech stocks personally; this post isn’t about the financial prospects of particular companies.)
Jacob Trefethen retweeted
You’re wrong in this case. OpenAI Foundation is funding @iskander and I to do genomics, immunopeptidomics, antigen-specific T cell response measurement, TCR profiling of antigen-specific T cells, and TCR-T performance comparison on samples from 200 cancer patients. All data will be made freely available and anyone will be able to use them to train better models of peptide presentation by HLA and immunogenicity in vivo. They are also funding a clinical trial which is a comparison of neoantigen vaccine formulations , with immunological potency across standard assays as the endpoint, a trial that biotech/pharma will never do because they don’t want their proprietary method(s) to lose. This is both serious and rigorous.
Jacob Trefethen retweeted
It was a pleasure working with @asteriskmgzn on this piece, which looks at a case study where regulatory reliance works well. Thank you @chengela and @clarabcollier for making the editing process wonderful!
Zambia approved a new HIV drug in just 12 days, far outpacing the average of 4-7 years in sub-Saharan Africa.
How did they do it? Most countries spend years reviewing drug applications that have already been approved by the FDA or EMA. Zambia decided to do things differently, building a system that treated prior approvals from trusted agencies as a starting point.
@EnlliMcA dives into Zambia’s process, and what we can learn from their experience:
Jacob Trefethen retweeted
I really like how this is thought out
Here's more on our initial strategy behind these grants, and other grants we're investigating in Public Data for Health, that may be of interest to researchers:
Our starting hypotheses for areas OpenAI Foundation support can be most useful are: connected data, scarce data, and direct data. Datasets we fund will usually have one or two of these properties, described in more detail in the next tweets, and in rare cases will share all three properties.
Across all datasets, we believe making data broadly accessible, while ensuring privacy whenever that relates to patient data, will become increasingly important. This will allow researchers to build on each other’s work, and scientific progress to emerge from unexpected places.
Jacob Trefethen retweeted
A drug dev regulatory knowledge base, cancer vaccines, and hill climbing ADMET. Good list of practical problems and ambitious awardees!
At the OpenAI Foundation, we believe breakthroughs against disease will come from pairing intelligence with more observations of the world – in other words, more data.
Today, we're announcing over $125M in grants, launching our second science program:
openaifoundation.org/news/pu…
Jacob Trefethen retweeted
Excited to partner w/ @FoundationOAI to build (w/ OpenADMET) better HT methods to measure physicochemical properties and Distribution to enable the next set of AI model improvements through blinded competitions. Thanks @JacobTref & @owl_posting!!! xitter.twitterapi.xyz/JacobTref/status/20999…
Here are some of the projects we're supporting:
OpenADMET will create open datasets, benchmarks, and blinded competitions to test whether AI models can be trained to predict how small molecules are absorbed and distributed across the body, to make drug development more predictable and reduce the failure rate of new drugs.
90% of drug candidates fail in clinical trials. That is often due to the difficulty of predicting how they will be absorbed and move around the body – their “ADMET” properties.
Unsolved prediction challenges like this can be a good fit for AI, when paired with high quality data to ground the accuracy of predictions from different models. For example, AlphaFold2 transformed protein structure prediction using data from the Protein Data Bank, in a competition against other modeling approaches run by CASP. Protein structure prediction is now integrated into many drug discovery programs that will likely go on to benefit patients.
To better predict ADMET properties of drug candidates, the OpenADMET team will develop high quality datasets to ground new predictive models, and run open challenges that researchers around the world can enter:
openadmet.ghost.io/mapping-t…
Jacob Trefethen retweeted
impossible to overstate how cool this is. tl;dr: what if we could make rapid personalized cancer vaccines work reliably? alex and ben are going to take a crack at building that future for us. we're standing at the frontier of a golden era in biotechnology and human health
Starting a new thing at UNC with @BenjaminGVincen to figure out which tumor-specific pMHCs are actually on tumor cells & which vaccine platforms are more immunogenic.
Lots of long-read WGS/scRNA, targeted mass spec, tumor-specific TCRs coming your way in the near future
Jacob Trefethen retweeted
VERY excited about this first batch of OAIF grants in Public Data for Health. Great choices @owl_posting and @JacobTref 💪
At the OpenAI Foundation, we believe breakthroughs against disease will come from pairing intelligence with more observations of the world – in other words, more data.
Today, we're announcing over $125M in grants, launching our second science program:
openaifoundation.org/news/pu…
Jacob Trefethen retweeted
Starting a new thing at UNC with @BenjaminGVincen to figure out which tumor-specific pMHCs are actually on tumor cells & which vaccine platforms are more immunogenic.
Lots of long-read WGS/scRNA, targeted mass spec, tumor-specific TCRs coming your way in the near future
Jacob Trefethen retweeted
More inspiring, excellent work from the OpenAI Foundation.
At the OpenAI Foundation, we believe breakthroughs against disease will come from pairing intelligence with more observations of the world – in other words, more data.
Today, we're announcing over $125M in grants, launching our second science program:
openaifoundation.org/news/pu…
Jacob Trefethen retweeted
Amazing to see the @FoundationOAI funding the CTD Commons, a project that came out of @RuxandraTeslo's Launch Sequence proposal!
The CTD Commons will purchase the FDA filing documents and clinical trial results from failed biotech companies to create an open-source library that will accelerate FDA approval timelines, lower compliance costs, and help unbottleneck AI's progress in the life sciences.
Full project proposal: ifp.org/biotechs-lost-archiv…
At the OpenAI Foundation, we believe breakthroughs against disease will come from pairing intelligence with more observations of the world – in other words, more data.
Today, we're announcing over $125M in grants, launching our second science program:
openaifoundation.org/news/pu…
Jacob Trefethen retweeted
I've often noted the difference between the "cure cancer" rhetoric and what they're actually doing. This closes some of that gap. 👊
At the OpenAI Foundation, we believe breakthroughs against disease will come from pairing intelligence with more observations of the world – in other words, more data.
Today, we're announcing over $125M in grants, launching our second science program:
openaifoundation.org/news/pu…
Jacob Trefethen retweeted
@owl_posting putting in the work!!! So many incredible initiatives funded
Today we’re excited to launch Public Data for Health, with more than $125M in initial grants to nonprofits and universities creating and opening up high-quality scientific datasets.
AI is getting dramatically better at analyzing biology, but accelerating medical discovery depends on researchers having high-quality data to work with.
Our goal is to make more valuable scientific data broadly available so researchers can build on each other’s work and accelerate discoveries that help prevent and treat disease.
Learn more: openaifoundation.org/news/pu…
Jacob Trefethen retweeted
Today, we are announcing our third cohort of residents! Each resident will receive up to $2M to work on a high impact scientific problem, with the governing principle being that they build something people actually use and build it openly.
Jacob Trefethen retweeted
Extremely excited to announce our first grants for the Public Data for Health program at the OpenAI Foundation, amounting to $125M+ across a wide range of fields. More here + characteristics of datasets we are most excited about:
openaifoundation.org/news/pu…
