Medicine is about to become continuous.LIFE OS is the model that makes it possible.
Your drug acts every hour. You see the patient every twelve weeks. LIFE OS keeps a live model of that patient's biology and of what your asset is doing inside it.
What it is
A live model of patient biological state, running around a drug in trials, expanded access and post-launch.
What you get
Response, tolerability, adherence and the mechanism behind them — weekly, per patient.
What it is not
Not a survey app, not a claims database, not a dashboard on old data.
Pharma · biotech · CRO · clinical research
01 — The gap
Drug design is only the beginning.The patient is the harder system.
The asset acts continuously. Biology reacts continuously. Trials and care still observe through visits, isolated biomarkers and endpoints — and between those checkpoints the system keeps moving.
You cannot control what you cannot observe.
02 — The model
Data is not the product.State is.
A lab value is a coordinate; a diagnosis is not a trajectory. LIFE OS reconstructs how the biological system moves — from what was measured, what happened, what was done and how the patient responded.
Four different objects, tracked separately.
I(t)
Immune state — what is activated
P(t)
Biological pressure — what the system is experiencing now
D(t)
Damage / dysfunction — what has accumulated
R(t)
Repair / resilience — capacity to recover
03 — Your asset, observed
Watch your asset work.Answers while they still matter.
| What you ask today | How you find out today | With LIFE OS |
|---|---|---|
| Is the drug working in this patient? | Endpoint at week 12 or 24 | Weekly change in the biology that drives the endpoint |
| Why did this patient not respond? | Post-hoc subgroup analysis | Their own baseline: genetics, microbiome, inflammation, metabolism |
| Is a side effect starting? | The patient reports it, or a lab flags it | Physiological drift days before it is reported |
| Is the patient still taking it? | Pill counts and self-report | Dose timing plus the biological signature of a taken dose |
| What should we combine it with? | A new study, a few more years | Which biological gap stays open in non-responders |
For non-responders, LIFE OS measures the distance between current state and the state associated with the desired outcome: what changed, what did not, and what is blocking full response.
04 — The loop
Medicine becomes a loop.Observe → Understand → Act → Measure → Learn.
Every measured response re-enters the model, so asset understanding improves with every treated patient.
05 — Scale
The largest biological model will not come from static datasets.It will come from trajectories.
One patient builds a Patient Biology Model. Many patients around one asset build an Asset Biology Model.
| Where does this asset work best? | And for which biological state |
| What predicts early response? | Baseline state + first-weeks drift |
| What predicts non-response or toxicity? | The bottleneck, not the subgroup label |
| Which combinations repeatedly emerge? | Across patients, indications and assets |
06 — Three surfaces, one runtime
Simple for the patient. Integrated in the clinic.Real-time for the asset builder.
For the patient
One action at a time.
What to eat, when to dose, what to monitor, when to call the clinician. No graphs to decode.
- App, account and activation code in ~2 minutes
- Sampling and data refresh handled automatically
For clinics & hospitals
Inside existing care.
The physician links the patient by QR, sets the objective, and sees the reasoning behind every action delivered between visits.
- Patient linked in one scan — no new workflow
- Structured exports, GDPR and MDR-aligned governance
For the asset builder
Real-time biology.
Consented, de-identified biological state around your asset as it evolves.
- Continuous cohort state, not quarterly extracts
- API and secure data room, audit trail and consent scope
| Drug-design platforms | Work before the patient |
| RWE players | Structure historical data |
| Sensors | Observe narrow streams |
| LIFE OS | Connects observation, biological state, action, response and learning |
06b — Clinical evidence
Clinically proven
Medical device · Clinical research
Clinically proven. CE-marked.
- 1,000+
- Patients in clinical studies
- 5
- Clinical studies conducted
- 4
- Published results
- >70%
- Patients much improved at three months
07 — Questions
LIFE OS, answered directly.
What is LIFE OS?+
A continuous biology runtime. It combines periodic measurements (blood, genomics, microbiome, imaging) with continuous signals (wearables, symptoms, dose timing, food, activity) to keep a live estimate of a patient's biological state Z(t) while a therapeutic asset is acting.
How is it different from real-world evidence platforms?+
RWE structures data that was already recorded. LIFE OS measures biology as it happens and reconstructs state between visits, so response, tolerability and adherence are visible while they can still be acted on.
What can a pharma team see?+
Per-patient and cohort response trajectory, immune shift, biological pressure, accumulated dysfunction, repair capacity, response gap and the bottlenecks limiting response — consented, de-identified, with full audit trail.
What does the patient see?+
One action at a time: what to eat, what to avoid, when to take the dose, what to monitor, when to call the clinician. The modeling stays behind the interface.
Which data does LIFE OS use?+
Shotgun metagenomic microbiome sequencing, human DNA and polygenic risk, blood panels, wearables and biosensors, medication and dose timing, nutrition, activity, sleep, symptoms and clinical events — on one patient timeline.
When is it available?+
The patient companion and clinic console are live today. The asset-facing interface enters early access with selected pharma, biotech and CRO partners, estimated November 2026.
08 — Request access
LIFE OS
Understand life while it is happening.
Send your name, company, role, work email, therapeutic area and asset stage, and what you want LIFE OS to understand around your asset.
Request early access