Services
Bioprocess modelling
Mechanistic, statistical, ML and hybrid models of your bioprocess, taken from a feasibility study to a qualified, monitored model through our staged framework.
The challenge
Your process runs, but its behaviour lives in people’s heads and in spreadsheets. Scale-up, tech transfer and troubleshooting all depend on a model nobody has written down, and a model nobody can defend in front of QA is not one you can use for decisions.
Our approach
We work in four stages, each closed by a signed gate:
- Feasibility study (8–12 weeks). Is this a modelling problem, and is it worth a full cycle? A data audit and a feasibility model built from the simplest baseline, judged against criteria agreed before we see any results.
- Process design. Mechanistic understanding and DoE, an ALCOA+ data audit and a documented architecture choice: mechanistic, statistical, ML or hybrid. Acceptance thresholds are fixed with your SME and QA before training, in a frozen Model Design Specification (MDS).
- Qualification (DQ → IQ → OQ → PQ). Reproducible training, validation on batches never seen in training, uncertainty quantification and prospective runs in shadow or advisory mode.
- Continued verification. Deployment with a rollback path, monitoring, drift detection and planned retraining under your change control.
You can start at any stage. If you already have a model, we pick up where it is.
What you get
- Feasibility report and an updated User Requirements Specification (URS)
- Model Design Specification (MDS) with acceptance criteria set before training
- PQ protocol and report, and a Model Risk Assessment
- Monitoring panel, retraining plan and a Model Card