Core capability · digital twin
Get to spec before the first vial.
Every process change on a sterile line is a gamble paid in scrapped batches. The Sterira digital twin simulates fill dynamics, lyo cycles, and contamination flow against your validated envelope, so you converge on the right parameters in software, not on the floor.
The problem
Tuning a sterile process burns real product.
Scale-up, tech transfer, and change control all traditionally cost engineering batches: expensive, slow, and constrained by cleanroom time. Each iteration is days of setup for a single data point.
- Engineering runs consume high-value product.
- Cleanroom time caps how fast you can iterate.
- Tech transfer restarts the learning curve per site.
How it works
Calibrate, simulate, transfer.
- 01
Calibrate to your line
The twin is fit to your equipment, product, and historical data until it tracks reality.
- 02
Simulate the space
Thousands of parameter combinations explored against the validated envelope in software.
- 03
Recommend parameters
Converges on a robust set with confidence bounds, ready for a confirmation run.
- 04
Deploy to agents
Validated parameters flow straight to the fill, lyo, and contamination agents.
What it models
The physics that decide a batch.
Fill dynamics
Foaming, shear, and weight response across pump and product variation.
Lyo heat & mass transfer
Sublimation, shelf gradients, and collapse-margin behavior.
Airflow & ingress
Contamination pathways and recovery under real velocities.
Load heterogeneity
Edge-vs-center effects across the shelf or tray.
Design space
Maps the robust operating region for QbD filings.
What-if scenarios
Test excursions and failures without risking product.
Tech transfer
Move a process between sites in software first.
Re-calibrate the twin to the receiving site's equipment and the validated parameters transfer with it, collapsing weeks of on-floor requalification into a confirmation run.
See validation support →Under the hood
A twin you can trust to file with.
Fit to your reality
Validated against real runs before any recommendation is trusted.
Confidence, not certainty
Every recommendation carries explicit uncertainty bounds.
Feeds the agents
Approved parameters deploy directly to the operational agents.
Where it pays off
Every high-stakes change.
Scale-up
Move from pilot to commercial fill without a wall of engineering batches.
Tech transfer
Qualify a process at a new site from a re-calibrated model.
Change control
Assess the impact of a component or parameter change in software.
New product intro
Find the robust operating window for a new molecule fast.
"We used to budget engineering batches by the dozen for tech transfer. The twin got us to a confirmation run on the first attempt at the receiving site."
Global biopharma
Connected agents
The twin drives the suite.
FAQ
Common questions.
It is calibrated against your real runs until it tracks them within a defined tolerance, and every recommendation ships with quantified confidence bounds rather than a single point estimate.
No. It dramatically reduces the number needed. You still perform a confirmation run before any regulated change; the twin gets you there in one attempt instead of many.
Yes. It maps the robust design space and generates the supporting evidence. See validation.
Stop tuning with product.
Calibrate a twin to your line and converge on spec in software.