Simulate life before you test on it.
CytoMind is the interface to the Digital Twin. In the laboratory it simulates biology before a single experiment. In your hand it becomes the surface through which you see, understand and govern your own twin.
CytoMind works at the scale of a cell — and the scale of a life.
The same intelligence runs in two places: inside the lab, simulating biology; and in your hand, as the surface onto a lifelong Digital Twin.
Virtual Cell Platform
Dynamic digital twins of human cells that behave like real cells inside the computer — moving biology from static data to simulated behaviour, from correlation to causation.
For researchers →Individual layer · PHCPersonal Health Cloud
The surface through which one person sees their Digital Twin — what it holds, what it predicts, what it is uncertain about, and who is permitted to use it.
For individuals →CytoMind operates the twin. The platform owns it.
There is one Digital Twin per person, held by the platform with one identity, one consent record and one contiguous audit trail. OmnigeniX writes molecular interpretation into it. TheraMind reads it at the point of care. CytoMind simulates against it and gives the individual a window onto it.
This matters more than it sounds. It is why a variant interpreted in a laboratory today is still readable by a clinician in ten years, and why a person can revoke consent once rather than product by product.
Biology is too complex, and too costly, to learn by trial and error.
Drug discovery still runs on experiments that take years and billions — with most candidates failing late, and data siloed across every omics layer.
Sources: Sun et al., Acta Pharmaceutica Sinica B (2022), on clinical development failure rates and their causes; consistent with the long-standing ~10% likelihood-of-approval figure reported across the literature.
Explore more, faster — safer, and for less.
Explore more, faster
Simulate years of biology in hours or days.
Safer and more ethical
Reduce reliance on animal models.
Lower cost, higher return
Fail in silico rather than in Phase II, where most attrition occurs.
Better predictions
More accurate outcomes across the pipeline.
A twin is not a data lake.
Every twin carries its own provenance, consent status, model versions, uncertainty and audit history — and the person it describes can see all of it.
Provenance
Where every observation came from, by what method, at what version.
Consent status
What is shared, with whom, for what purpose, for how long.
Uncertainty
Calibrated intervals, and an explicit statement of what is not known.
Audit history
Every access recorded immutably, and visible to the person.
Simulate biology. Or understand your own.
Partner with the Virtual Cell Platform, or join the waitlist for the Personal Health Cloud — tell us which fits.