Fold AI
Unfolding RNA with AI
At a glance
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Development stage
Prototype developed
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Investment stage
Seed
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UNSW affiliation
Spinout - staff led
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Technology readiness level
TRL 4
We're uniquely positioned to capture the US$8B RNA-targeting therapeutics market with our first-in-class multimodal AI system uniquely focused on RNA targeting therapeutics.
We're accelerating RNA therapeutics with AI that decodes molecular structures, designs novel drugs, and predicts clinical success—faster and smarter.
Founded by award-winning experts in AI and RNA, we achieved revenue in 12 months while in stealth. Our vertical AI system delivers 100x state-of-the-art efficacy in predicting therapeutics, optimising off-target effects, toxicity, and drug-like properties to accelerate life-changing treatments.
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Fold AI’s vertical AI system generates a ranked list of optimal RNA-targeting therapeutic candidates, minimizing toxicity while maximizing clinical potential. We collaborate with RNA-focused pharma and biotech partners, predicting and co-developing drug candidates for their RNA targets toward the clinic. Partnership revenue fuels Fold AI’s in-house drug discovery program enabled by our proprietary AI, which simultaneously identifies RNA targets and designs drug candidates against them in a unified framework.
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Only 0.05% of the human genome is currently druggable. By targeting RNA instead of proteins, Fold AI expands the druggable genome by 1000x enabling drugs against previously undruggable protein targets, as well as against non-coding RNAs, which comprise 69% of the druggable genome – the new era of precision therapeutics.
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- Pharma, biotech, and other types of companies and organizations working on RNA-targeting therapeutics
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- Recipients of the inaugural NSW Chief Scientist and Engineer’s BioSciences Fund investment
- Revenue within the first 12 months
- Multiple partnerships in the pipeline
- World leader advisors in each of the fields: RNA biology, drug discovery, RNA-targeting ASO and small molecule therapeutics
- 100x SoTA on RNA-targeting ASO prediction benchmarks
- Robust model for RNA-targeting small molecule prediction outperforming SoTA models in generalizability
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