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TETmedical

Rapid blood test for ischemic stroke

Raised to date

$3.5M

of $9.8M offered across 1 Form D filing

Still open
$6.3M
Investors
45
Last filed
Jun 24, 2026

About

TETmedical, Inc. (Tethered Enzyme Technologies) is a clinical-stage nanomedicine diagnostics company spun out of Cornell University research, with labs at the Cornell Business & Technology Park in Ithaca, NY and an administrative office in Fair Haven, NJ. Its platform is a patented 'TET nanobot' — thousands of enzymes tethered to a nanoparticle — that performs chemical operations orders of magnitude faster than conventional antibody assays. Its lead product, NSE-FAST, is a rapid blood test to aid diagnosis of acute ischemic stroke, and received FDA Breakthrough Device Designation in June 2026. The platform is backed by more than $6M of NIH-funded research plus $2.8M in government grants, and the company was co-founded by serial medtech entrepreneur David Fischell with Cornell scientists Alex Travis and Roy Cohen.

Tethering thousands of enzymes to a single nanoparticle produces signal amplification far faster than antibody-based assays, which is what makes a rapid point-of-care blood test for acute stroke feasible where existing workflows miss roughly 17% of ischemic strokes (up to 42% of atypical presentations).

Funding

  • EquityFiled Jun 24, 2026Form D
    $3.5M/ $9.8M

Product

NSE-FAST

In vitro diagnostic test

A rapid blood test measuring neuron-specific enolase functional activity, designed to aid in the diagnosis of acute ischemic stroke, including the atypical presentations most often missed in emergency settings.

  • Built on the TET tethered-enzyme nanoparticle platform for rapid signal generation
  • Targets the ~17% of US acute ischemic strokes currently missed, and ~42% for atypical presentations such as dizziness
  • Granted FDA Breakthrough Device Designation in June 2026

Built for

Hospitals, emergency departments, and stroke centers needing faster and more reliable triage of suspected acute ischemic stroke

People on file