FDA declares Novo Nordisk $NVO (Catalent) plant, key to drug manufacturing for some biotechs, out of compliance. Impacting $SRRK and $REGN today.
https://t.co/LLlei1xM7X via @elaineywchen
We interviewed 50+ regulatory affairs professionals at pharmaceutical companies.
The #1 pain point mentioned by 82%:
"We spend weeks manually updating SOPs and batch records every time FDA publishes new guidance."
This work should be automated.
We're making it happen.
1/🚨WOW! CRISPR & Gene Editing have made it into today’s FT’s business section After AstraZeneca’s announced its recent $555M collaboration signed with Algen Bio - a Berkeley-based company which originated from the lab of CRISPR co-inventor and Nobel Prize winner Jennifer Doudna.
According to the collaboration agreement- $AZN will receive certain rights to develop and commercialise CRISPR Gene Editing therapies and Algen will receive in return $555M upon achieving specific commercial and regulatory milestones.
It’s always a positive sign when Big Pharma companies are returning and reinvesting in the CRISPR & Gene Editing space. $XBI
saying AI in biology is a scam is more about your lack of understanding of its strengths and limitations. It is quite like saying computers in biology are a scam.
The 2 simplest ways AI helps biology
- parsing multimodal data in parallel to choose the best data for a human to look at reducing inefficiency
- ability to embed large numbers of signals about cells and clusters of cells to create lower-dimensional representations that are more human interpretable in the 3D/4D.
Even people who think AI in biology is a grift (lol) cannot argue against these two.
If you think AI is a scam here, that is either a data issue or a skill issue.
How AI agents actually monitor regulatory changes:
1. Web scrapers check https://t.co/jNfE2wIcXj, EMA, PMDA every 6 hours
2. NLP models detect semantic changes in guidance
3. RAG retrieves affected sections from your documents
4. LLM drafts compliant revisions with citations
5. Human reviews and approves
Agentic AI in production. Check us out https://t.co/DlOd6okesT
Everything is accelerating
Researchers at Harvard Medical School developed a tool that uses AI to accelerate drug discovery and development.
"The new technology, called PDGrapher, applies machine learning to identify a list of genes that can reverse disease in cells when targeted by drugs."
"The study, published last month in Nature, claims the technology works up to 25 times faster than existing methods."
ChatGPT-Like AI Model Details 1,300 Regions/Subregions in Mouse Brain Map
Tissue-agnostic CellTransformer can be used on other organs and tissues, including cancerous tissue, for which large-scale #spatialtranscriptomics data is available
@UCSF#brain#AI
https://t.co/nlCaOt1lfY
@bindureddy Agreed, we’re actually getting rid of tedious activities and building a true foundation of intelligence for pharma companies. Check us out! https://t.co/p5cIj8PRNs
We interviewed 50+ regulatory affairs professionals at pharmaceutical companies.
The #1 pain point mentioned by 82%:
"We spend weeks manually updating SOPs and batch records every time FDA publishes new guidance."
This work should be automated.
We're making it happen.
@yaireinhorn Wow, this $NVO-$AKRO deal is a game-changer! $54/share + $6 CVR ($5.2B total) for efruxifermin’s MASH potential is bold under new CEO Mike Doustdar’s watch [Reuters, 10/09]. With 29% fibrosis improvement at 96 weeks in Phase IIb [Applied Clinical Trials, 10/05] and MASH cases set to double by 2030 [Frontiers, 2024], this could redefine Novo’s metabolic portfolio. Thoughts on the 9,000 job cuts’ impact? $XBI
@HealthcareAIGuy@JAMANetwork This administrative burden doesn’t only exist at the clinical level, but also within the pharmaceutical companies themselves! The “validation tax” is growing exponentially
If you're in Philly, come hang out in November!
Join @davidwest_irl, CEO/Founder of @Proscia, and others (TBA...) — we’ll have a panel of founders, investors, & a crowd of builders, execs, and enthusiasts.
If you are interested in sponsoring and/or speaking, let us know ⚡
How AI agents actually monitor regulatory changes:
1. Web scrapers check https://t.co/jNfE2wIcXj, EMA, PMDA every 6 hours
2. NLP models detect semantic changes in guidance
3. RAG retrieves affected sections from your documents
4. LLM drafts compliant revisions with citations
5. Human reviews and approves
Agentic AI in production.