Bioreactor & facility twin
Culture, feed, perfusion, and purification modeled end to end.
Simulation & optimization · digital twin
Simulate the batch, then run it for real.
A bioreactor-and-facility twin that hits the titer and CQA spec before the run, and generates the rare failures no plant could survive collecting.
Runs on DGX/HGX and OVX with Omniverse
The problem
Facilities commit millions to a plan they cannot test first.
Recipe, feed, perfusion, gradient, and pooling choices are set from golden-batch spreadsheets and a scientist's judgment, then run live and hoped for. Tech transfer and scale-up from lab to manufacturing take years because every process change is validated on real, expensive runs.
The rare failures are the ones that matter most: a contamination, a VCD crash, a chromatography breakthrough, a CQA excursion. They cannot be collected safely or often enough to learn from, and there is no way to rehearse them before the batch or schedule campaigns against the real constraints of equipment, resin, media, and people.
What Twineon does
Where the batch is de-risked before anything touches the floor.
Twineon simulates the culture, feed, perfusion, and purification of a batch to hit the target titer and CQA spec before the run, and auto-optimizes feed and gradients against the twin. It generates thousands of synthetic scenarios that are impossible to collect on real batches, so the whole fleet learns from failures no plant could survive. And it schedules campaigns, feed and perfusion windows, resin cycles, and skid allocation under real constraints.
Hit spec before the batch
Simulate to the titer and CQA target with auto-optimized feed and gradients.
Synthetic rare failures
Contamination, drift, VCD crashes, and breakthrough generated at scale.
Campaign scheduling
Feed windows, resin cycles, and skid allocation optimized under real constraints.
Feeds the fleet
Validated recipes and surrogate models handed back to the live platform.
Author and explore
Process scientists build twins and run what-if scenarios on RTX workstations.
- Physics-based and ML hybrid simulation of bioreactor and purification dynamics
- Synthetic scenario generation for rare, high-value failures
- Auto-optimization of feed, gradient, and pooling policies against the twin
- Constraint optimization for scheduling and resource allocation
Under the hood
Simulation as a control asset, not a report.
Mechanistic simulation is usually run offline by MSAT consultants and handed over as a document. Twineon closes the loop. It optimizes the batch, generates the failures no plant can collect, and hands validated recipes straight to Bioseon's live agents. The optimization sharpens as the twin calibrates on partner processes.
Built on NVIDIA
The heaviest GPU workload in the ecosystem.
- ComputeDGX, HGX, and OVX run twin simulation, synthetic generation, and policy training at scale. RTX workstations handle twin authoring and what-if runs.
- Twin & dataOmniverse and Cosmos build the bioreactor and facility twin and synthesize rare scenarios. Modulus provides the physics-ML surrogate models. BioNeMo grounds the biological behavior.
- OptimizationcuOpt optimizes campaigns, feed and perfusion windows, resin cycles, and skid allocation.
- ServingOmniverse Cloud runs collaborative twin sessions across sites. Triton and NIM serve surrogate models to the live platform under NVIDIA AI Enterprise.
Commercials
The planning brain of the manufacturing network.
- PricingBundled into the Bioseon Site tier at $85,000 per month and central to Enterprise deals from $700k to $8M ACV, with a premium tier for custom cell-line and process twins.
- Who buysMSAT and process-development directors hold the budget, process scientists champion it, QA and validation approve.
- The moatA calibrated cross-site twin plus the only large library of synthetic and real rare biologics failures, the training ground that makes every downstream model better.
- First deploymentCalibrate a single-bioreactor twin on partner data, deliver hit-titer-before-batch simulation for one process, add synthetic contamination and VCD-crash scenarios, then cuOpt campaign scheduling.
Where it fits
Twineon rehearses what the others run.
Rehearse the batch before you run it.
Twineon lands on tech transfer and scale-up, where hitting spec faster saves years and millions. We start with a single-bioreactor twin on your data.