# CisFalcon

- **Event:** [Built with Claude: Life Sciences](https://cerebralvalley.ai/e/built-with-claude-life-sciences)
- **When:** Jul 7 at 12:00 PM – Jul 14 at 12:00 AM (EDT)
- **Where:** Online
- **Team:** [Ubaidullah Shuaib](https://cerebralvalley.ai/u/corridor)
- **GitHub:** https://github.com/belumume/cisfalcon
- **Demo video:** https://youtu.be/L5xhnDS4weI
- **Gallery:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-claude-life-sciences/hackathon/gallery/212

AI now designs synthetic enhancers meant to switch a gene on in one cell type and stay silent everywhere else. When one fires in the wrong cell, the consequence can be clinical: in a real enhancer-AAV gene therapy for Dravet syndrome, driving the gene in all neurons instead of only interneurons raised mortality in mice, while the cell-type-specific version was safe and corrected seizures (Mich et al., Sci Transl Med 2025). 

CisFalcon catches that failure from sequence, before a lab spends six weeks and a synthesis run. Paste a designed enhancer into the live tool (https://cisfalcon-lifesci.fly.dev/) and it scores cell-type specificity against a frozen external measured-activity model, then applies the prescribed motif edit and re-scores from failing to passing (a proposed fix, not wet-lab validated). On 93,435 independent designs from a different lab it separates failures at AUROC 0.80; ranking a batch safest-first cuts wasted syntheses about 70%. 

We also tested the harder within-tissue question directly, on real in-vivo cortical enhancers with an independent model (AUROC 0.71). It flags risk; it does not design DNA.

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