We use a broad range of Machine Learning methods, with particular expertise in kernel methods and Deep Learning, for a variety of biological and wider problems.
We have been working in all forms of biomodelling – from biophysics simulations of macromolecules through systems biology models of metabolism – for over 18 years.
We’ve been using 3D printing and laser cutting since before you’d even heard of it, but we still prefer the most rapid prototyping of all – a trip to the local hardware store.
With a combination of Arduino, Raspberry Pi and wifi plugs, all coordinated via Python-based Flask APIs, we can automate your laboratory. Our own labs have bioreactors, incubators and various process monitors that can be operated from anywhere via the web.
Bioprocess Design and Operation
We’ve run everything from plate readers up to large bioreactors. Our cost-effective cell flocculation and lysis protocols were developed in-house. We built a medium-scale protein production facility for our Rapid Synthetic Biology process.
We pride ourselves on understanding our sector’s economic as well as technical drivers. We use process engineering techniques, including whole process modelling, to identify where there is a need for our brand of cost-effective intervention and to optimise our processes.
Our agile R&D moves fast to prototype, implement, validate and optimise new technologies. We begin by deconstructing conventional wisdom to identify what works and what needs overhauling. We bring in technologies from other fields. We’re guided by what we call “good enough” design metrics that put the brakes on costly and slow over-engineering.