Constellab Digital Twin
Optimise your bioprocesses through simulation and prediction
The bioprocess development challenge
Bioprocess development still relies on lengthy, costly experimental cycles: every change in medium, temperature or operating parameter requires a new lab run. The accumulation of experiments generates large volumes of poorly exploited data, and teams lack tools to anticipate system behaviour before conducting experiments.
Constellab Digital Twin builds mathematical models calibrated on your fermentation data to simulate, predict and optimise your bioprocesses in silico. It integrates natively into your Constellab environment (directly connecting instruments, data files and dashboards) to reduce the number of experimental runs, maximise yields and accelerate scale-up.
Why adopt the digital twin?
Mathematical modelling
Build mechanistic models calibrated on your real fermentation data: growth kinetics, substrate consumption, metabolite production.
In silico simulation
Test new operating parameters, medium compositions and feeding strategies without conducting physical lab runs.
Medium optimisation
Automatically identify optimal culture conditions to maximise biomass and product of interest yields.
Yield prediction
Anticipate process performance before every run, reduce surprises and plan your production campaigns with confidence.
Fewer experimental cycles
Significantly reduce the number of lab runs needed to reach your targets: fewer reagents, less time, lower costs.
Native Constellab integration
Directly connect your instruments, data files and Constellab Bioprocess dashboards for an end-to-end pipeline with no manual re-entry.