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Neurodegeneration
Targeting the aggregates behind Alzheimer’s, Parkinson’s, ALS and prion disease. The goal is to break them down rather than slow their spread.
AI & computational biology · Las Vegas
Drug discovery from first principles.
An AI and computational biology company finding new ways to stop disease, starting where conventional drug design doesn’t look.
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Intact
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U.S. patent applications pending
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Training data required: models are derived from physics
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Guesswork parameters to fit
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Engine serving every disease program
01 The problem
Most drugs are designed the same way: find a protein, build a key to fit its lock.
It’s slow, it’s expensive, and it breaks down when the target mutates, hides or has no lock at all.
Infection
Virusesevolve around their drugs.
Resistance
Bacteriabuild resistance.
Oncology
Cancersrewire themselves.
Neurology
Misfolded proteinsin Alzheimer’s and Parkinson’s have resisted decades of effort.
02 Our approach
We don’t start with the lock.
We start with the hidden architecture that disease molecules depend on to hold together, a layer of biology that standard drug design largely ignores. Our platform turns that architecture into a computable target.
Conventional design asks
What fits this protein?
Guideng asks
What makes this structure fall apart, and only this one?
Physics, not curve-fitting
No training data. No guesswork parameters.
Because the models are derived rather than fitted, they don’t depend on what’s been tried before.
A new target class
Structure becomes the target.
The architecture that holds a disease molecule together becomes something we can compute against, even when there’s no pocket to bind.
Hardware speed
Runs on hardware the size of a postage stamp.
Built on physics rather than curve-fitting, it’s fast enough to screen at hardware speed on very small devices.
03 Programs
Five programs. One platform.
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Broad-spectrum antivirals
A mechanism designed to act across virus families rather than one strain at a time. It isn’t tied to any single viral protein, so a mutation alone doesn’t route around it.
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Next-generation antibiotics
Aiming at a feature bacteria can’t give up without dying, closing the usual escape route to resistance.
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Precision oncology
Matching therapy to the individual tumor, with a method for predicting which patients will respond before treatment begins.
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Molecular targeting
Mapping exactly where a structure is weakest, so a drug can be placed where it does the most good with the least collateral.
04 Why it’s different
Built to reach targets no one has tried before.
One engine, every program.
The same platform serves neurology, infection and oncology. Switching disease areas is a setting, not a rebuild.
Derived, not fitted.
The models come from physics and mathematics, not from training on past drugs, so they can reach targets no one has tried before.
Built for speed and trust.
Screening runs at hardware speed, and every result carries a tamper-proof record built for regulatory review.
05 Status
In computational discovery, building toward the lab.
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U.S. patent applications pending.
Computational discoveryNow
Laboratory validationBuilding partnerships
Founded by Eric Guideng, inventor and independent researcher, Las Vegas.
Building partnerships for laboratory validation.
For investors, research labs and collaborators who want to test a different starting point for drug discovery.
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