For most of its history, vaccine development has been a reactive business: a virus appears, scientists scramble, and an injection arrives just in time for the variant it targetted to have already moved on. DIOSynVax decided to skip the chase entirely. They fed an AI every Sarbeco coronavirus genome they could find, including the bat viruses still minding their own business in caves, and asked it to design a single "super-antigen" that captures what the whole family has in common rather than any one member.
The result, their vaccine has now passed its first human trial in 39 volunteers: safe, no significant side effects and immune responses against COVID, plus some bat viruses that haven't even bothered us yet. It is, the team notes, the first vaccine whose active ingredient was dreamed up entirely in a computer to reach human testing.
OpenAI + Ginkgo Bioworks collaboration: looking to do this at scale
🧐 What's in it for me? For all the talk of AI doing admin, here it has achieved something genuinely consequential: designed a vaccine that works in people. The promise is a vaccine you don't renew every autumn like a tax disc, one built to cover tomorrow's variants and possibly an entire viral family at once. It's early (Phase 2 is next), but the same trick is already being pointed at flu and Ebola.
💵 Out of the Lab: If antigens can be designed by software rather than discovered by trial and error, the bottleneck in vaccine-making shifts from the lab bench to the GPU cluster, which is a very different competitive landscape.
DIOSynVax, the Cambridge spinout founded by the project's scientific lead, is the purest bet on AI-first antigen design, with flu, bird flu and haemorrhagic-fever candidates already in its pipeline.
BioNTech saw this coming, paying a reported half-billion-plus for AI outfit InstaDeep in 2023 to fold machine learning into its own discovery engine.
Moderna has likewise staked its platform on computational design, and a future-proof antigen would slot neatly onto its mRNA rails.
Until next time.
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