The problem space
Scale-up is rarely a clean linear extrapolation. Mass-transfer behaves differently in a larger vessel; mixing and oxygen profiles change; small differences in equipment geometry surface as unexpected deviations during a campaign. The institutional knowledge that lets a senior scientist guess the right adjustment is hard to write down, and harder still to transfer to a new team or a new site.
Tech transfer is the parallel problem in time rather than scale: moving a process from one place to another and keeping the parts that matter intact. The hard part isn't the documentation — it's knowing which details mattered, and being able to replay the reasoning when something looks wrong.
What we're exploring
Modica's adaptive digital twin is being built to make the implicit assumptions of a bioprocess explicit and reusable. The aim is to give scale-up and tech-transfer teams a single, evolving model of the process that can be queried, perturbed, and compared against new equipment — rather than a paper protocol that gets reinterpreted at every step.
We're at the R&D stage. Some of what we're working on is described in our FENG-funded project; we'll publish more as the tooling matures.