Genome-directed antibiotic reinforcement

Don't develop new antibiotics.
Reinforce the existing ones with AI.

genome in matched reinforcement out minutes

New antibiotics can't win the economics. So we don't build them. Subsira reads a pathogen's genome and returns the reinforcement matched to each antibiotic it's resistant to — in minutes.

Two years of in-house pairing experiments Validated in vivo
subsira · match
Antibiotic failing
Input — bacteria genome + failing antibiotics
E. coli · ST131 ✕ Meropenem ✕ Ciprofloxacin ✕ Gentamicin
ATGCTAGCGGATCCTAGCTAGGCTAAGCTTGACCTAGCGTTAGCCGATCGGATCGTAGCTAGCGATCGATCGGCTAGCTAGCGGATCC
screening candidate reinforcers…
One reinforcer matched per antibiotic
  • 01Meropenem + vB_Eco-2170.94
  • 02Ciprofloxacin + vB_Eco-4020.88
  • 03Gentamicin + vB_Eco-1550.81
one strain-specific reinforcer per failing antibiotic — each selected on a trade-off in this genome
The reframe

Resistance shouldn't be a chemistry problem. It's a matching problem.

The reinforcement for a failing antibiotic already exists. The bacterial genome selects the right one — until now, this has been done empirically. We turned that into an inference problem: genome in, matched reinforcement out, in minutes.

Why the pairing holds: a resistant strain can defend itself against the antibiotic, or against the agent we pair with it — and those two defenses trade off against each other. Which trade-off applies to this strain is written in its genome.

Reinforcement — what we mean by it A second agent, selected by the pathogen's own genome, paired with the antibiotic that strain has defeated — chosen because escaping it costs the strain the defense it was using against the antibiotic. Today that agent is a matched phage. Next it's a matched β-lactamase inhibitor. It is never a generic potentiator handed to every patient — if the genome doesn't choose it, we don't ship it.

The economics

New antibiotics can't win. So the pipeline died.

~$1.5B
to develop one new antibiotic
~$46M
average revenue it earns per year
0
new classes in ~30 years
<1 yr
Achaogen — bankrupt after approval

You can't out-invent a market this broken. So we don't — we match the reinforcement the genome already points to.

The platform

One engine. Expanding modalities.

The engine is the durable asset; each modality is an instance of it at a different genomic resolution. We add a modality only where a feature in the genome names the agent.

01 · Live today

Strain-level matching

Matched down to the individual isolate, on the receptors and defenses carried in its genome. No two strains get the same answer.

Resolutionstrain
Agentmatched phage
Evidencestrong, published
Readinessnamed-patient today
02 · Validating next

Enzyme-level matching

The resistance genotype names the enzyme outright, and the enzyme names what restores the β-lactam.

Resolutionenzyme
Agentβ-lactamase inhibitor
Evidencewell-characterized
Readinesseasy to validate
03 · On roadmap

Locus-level matching

Capsule, surface and defense loci are legible in the same sequence, and each one names an agent of its own.

Resolutionlocus
Agentdepolymerases, anti-defense
Evidenceemerging
Readinessresearch → next

Same engine, finer resolution each time — strain, then enzyme, then locus. The genome selects the agent at whichever resolution the mechanism lives. We never add genome-independent potentiators.

Where this goes

Reinforce the antibiotics you already have.

From restoring one failing antibiotic to the decision layer for every resistant infection.

info@subsira.io Washington, DC · US