Phylox designs novel herbicide modes of action for the resistant weeds breaking modern agriculture, discovering molecules superweeds have never seen.
Superweeds now shrug off entire classes of herbicides. Resistance is spreading across the world's biggest cash crops, and the incumbent discovery pipeline has run dry.
Protein language models can now model plant targets directly, opening biology that was previously a black box.
Molecular screening that once cost a fortune is now cheap enough to search billions of candidates in silico.
The incumbent pipeline has stalled. The opportunity to define the next mode of action is open right now.
Point AI at a fresh target, surface molecules that bind, and confirm the winners in the lab.
We point the AI at the GLR3.4 binding pocket, a new and unexploited herbicide target class.
The platform predicts and shortlists novel molecules that bind, ranking billions of candidates in silico.
We confirm the top hits in the lab, then license winning chemistry to major agriculture companies.
Independent science researcher (TRP pain-receptor channels). 1st place, IFT Nutmeg & PepsiCo Engineering Awards. 1st at HackPrinceton. Researcher at Brown.
3× Regeneron ISEF Grand Award winner. 1st at JSHS '25, National STEM Champion '26, 1st in Applied Technology. Researcher at Yale.
IEEE-published AI/ML researcher (youngest author). 3M Young Scientist & GENIUS Olympiad 1st-place gold, Science. 3rd at JSHS '25.
A pre-seed round to take Phylox from validated targets to confirmed, licensable hits. Capital goes straight into compound synthesis, wet-lab assays, and field validation.