Anthropic just said it's running its own drug discovery, with Claude doing much of the scientific work.
AI models need good biological data. Proteins are where the biology actually happens and that's the layer $NAUT is building tools for single-molecule proteomics.
Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own.
In doing so, we’ve learned much more about how Claude can support the many stages of drug development.
In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences.
anthropic.com/research/early…
Here’s another reason why:
Daniela Amodei reveals the reason Anthropic won't run ads even though its competitors do:
“Our competitors are putting ads into their chatbots. And what does that mean? You make more money if a user is engaging with your product longer. Do you then want to tell your user that they're wrong? No, you don't."
"I think I feel hopeful about Anthropic's ability to have the lowest sycophancy rate of any of the models because of our incentives.“
“I think it's almost inevitable that many of these competing products are going to wind up with a sycophancy problem. But I think at Anthropic, because we've committed to not put ads in the models, there's no reason for you to be talking to Claude longer or shorter."
"We just want you to be able to get the right most helpful most harmless answer possible."
GPTfeed retweeted
ANTHROPIC SAYS IT HAS ACQUIRED MITHRIL MEDICINE TO RUN RARE DISEASE PROGRAMS, ADDING THAT IT WANTS TO SHARE ITS MODELS WITH DRUG DEVELOPMENT RESEARCHERS AND AS MANY RESEARCHERS AS POSSIBLE, AND THAT IT LOOKS FORWARD TO WORKING WITH MORE ORGANIZATIONS
GPTfeed retweeted
"After about a year of development, AKT1, EGFR, and P53 are already performing in line with tau, our most mature assay, which took roughly five years to build.
Median CVs were 8.8% for AKT1, 3.6% for EGFR, and 6.6% for P53, all well below our 10% target and far better than industry norms closer to 25%."
$NAUT
GPTfeed retweeted
📰 Nautilus to Measure Proteoforms Driving Alzheimer’s Disease and Cancer in ARPA-H-Funded SEEDS Consortium
Nautilus expects to receive up to $6 million to bring its Voyager™ Platform to a multidisciplinary team integrating protein science, AI, and computational modeling to develop new diagnostics and therapeutics.
Read the press release:
globenewswire.com/news-relea…
And read our latest blog post to discover how the Nautilus Voyager™ Platform may advance the identification of biomarkers and drug targets as part of the SEEDS Consortium:
nautilus.bio/blog/advancing-…
GPTfeed retweeted
Pls keep up the good work on $NAUT 👌
Hope you sustain this niche quality because everybody’s just spamming tickers
FUD $NAUT
I have no position in $NAUT (0 intention of opening one). Just an interesting piece of management history.
Something interesting I found while researching Nautilus Biotechnology ($NAUT).
Its CEO, Sujal Patel, previously founded Isilon Systems, which was involved in an accounting scandal.
In 2009, the SEC charged Isilon's former CFO with securities fraud for improperly recognised revenue.
Patel was also named in shareholder lawsuits, with a securities class action eventually settling for $15 million.
To be clear, Patel was not personally charged with fraud by the SEC.
Patel was not CEO when the irregularities occurred, but he was both a senior executive (CTO) and a board director.
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I created a mockup of how @TAP_RealEstate 's website could better serve both investors and property owners.
A “Tokenize Your Property” CTA and stronger SEO could help turn the website from a showcase into a lead-generation engine, attracting new properties and revenue
👆🏼 @GregHopkins_ Check this out, I made a demo mockup of how TAP RE website could better serve both investors and property owners.
GPTfeed retweeted
Great meetings in Utah this week with the Zermatt team as we begin integrating our technology under the recently announced agreement.
We also had productive discussions with several real estate portfolio groups exploring opportunities around tokenization services.
The technical work focused on peptide detection and statistical confidence. The team evaluated mProphet-based scoring in Skyline and compared results with tools including OpenSWATH, Spectronaut and AB SCIEX PeakView.
