Small personal update: very pleased to be in Singapore next week to present 2 spotlight papers at ICLR 2025 on AI for molecular design!! 🇸🇬

DM me if you want to meet up and chat about AI for bio, drug discovery, science policy or just chat about aviation!!!

12/ Another standout: the plan proposes an internal headhunting team within the UK Government to attract top global talent to AISI, the UK Sovereign AI Team, and UK-based companies.

Will they also have the power to fast-track visas? From experience, i hope so....

10/ The plan’s proposal to create a UK Sovereign AI Team is great. This unit will partner with private and academic sectors to back national champions and remove roadblocks in AI, with a strong focus on AI for science and robotics.

8/ Another standout is the creation of AIRR programme directors—mission-focused individuals with autonomy to strategically allocate compute to high-potential projects.

A kind of "Compute Czar" role, this could significantly accelerate progress on big bets in AI for science.

7/ However, there’s a risk of duplicating efforts where existing world-class institutions, like the EBI managing the PDBe, are already doing excellent work.

Not every problem needs to fit into a National Data Library-sized™ hole. Let’s build on what we already have!

5/ That’s why I’m thrilled to see the plan emphasise strategic data initiatives:
-Identifying high-impact datasets
-Improving data quality
-Incentivising researchers and companies to unlock and curate datasets

These efforts will make sparse, unstructured datasets better for AI

4/ If we want breakthroughs beyond protein folding, we need to address data gaps across science.

AlphaFold was made possible by sustained investment in protein structure data.

Similar long term commitments are essential for other fields like materials and climate science.

3/ AI breakthroughs like AlphaFold wouldn’t be possible without decades of work on datasets.

e.g., AlphaFold was trained on protein structures from the Protein Data Bank (PDB), which took 50+ years and ~$20 *billion* to create.

This is the kind of foundational effort AI needs.

2/ There’s a lot to like in this plan:
- Expanding UK AI compute capacity by 20x
- Establishing AI Growth Zones
- Building up AI talent pipelines

But as a scientist, what excites me most is the report’s focus on **data**—an area we really need to get right.

Just added Graph Therapeutics, a new startup in Vienna focusing on precision medicine for inflammation and immunology

Founded by former Allcyte team

🚨I have updated the TechBio Company Database with a bunch of new companies!

Find it here: tinyurl.com/techbiodatabase

New ones are:
- Enveda Biosciences (Natural Products)
- Cure_51 (Personalised Medicine)
- Antiverse (Antibodies)
- Tamarind Bio (SaaS)
- Biorelate (Target ID)

cont.

Was very fortunate to be invited to give a talk on AI for Drug Discovery at the (very nice) British Ambassador's Residence in Rome last week!

Thanks to the Foreign Office for the invitation!

You can also break down by geography - I'd had many people say this is really useful for when it comes to applying for jobs.

You can also break down all companies by nice.

For example here are all the ones pursuing 'small molecules'

Please share to make more people aware and reach out for any feedback/additions (I have added many suggestions even if I haven't got around to replying to your email!)

The database is in a Notion database to allow for easy visualisation and querying.

Now I can share external links without the posts being down regulated - I thought it would share this again!:)

I have compiled a list of now 100+ companies in the 'TechBio' space into a fully open database for the community.

Find here and please share if you like
open.substack.com/pub/harrisbi...