DrMaria Papathanasiou

I lead the Life Sciences and Process Systems Engineering Lab in the Sargent Centre for Process Systems Engineering. We develop computational methods (digital twins, optimisation, and hybrid and machine-learning-based control) that make the design, operation and supply of medicines and foods faster, more flexible and more sustainable.

Our research spans across:

• model-based design spaces and process flexibility under uncertainty
• advanced and reinforcement-learning-based control of continuous biomanufacturing
• machine-learning enhanced drug discovery
• supply chains for next generation vaccines and advanced therapies
• sustainability-by-design in biopharma
• alternative-protein systems, including food structure and digestion modelling

We work closely with industry partners including and we release our tools open source on our lab's GitHub. Our work has been recognised with IChemE’s Junior Sargent Medal (2023) and an IChemE Global Team Award (2021).

I welcome applications from excellent and enthusiastic students from all over the world. Get in touch to hear about current vacancies.

Not a scientist? Read the summary below

Welcome to our lab! We use expert knowledge and real-world data to build digital twins of the processes that make medicines and food.

What is a digital twin?

A digital twin is a computer model, built on mathematical equations, that mimics what happens inside a physical or biological system or a piece of equipment.

Why are digital twins useful?

They let us run many experiments on the computer instead of in the lab, which is faster and cheaper. We use them to find the conditions under which a process performs best. We then design smart controllers that keep the process at those conditions, and we test how processes and supply chains cope when things change or go wrong. We also use them to measure and reduce the environmental footprint of manufacturing.

How do we work with experimental researchers and industry? Experimental researchers and industrial partners give us expert knowledge and data, and real-world data is essential for checking that a digital twin is right. In return, our tools give them a continuous picture of what is happening in their process, even when measurements are not available. They can also guide the design of targeted experiments, saving time, cost and labour.

Research Themes

• Design spaces and process flexibility
• Hybrid and machine-learning-based process control
• Supply chains for vaccines and advanced therapies
• Sustainable biomanufacturing
• Food and alternative-protein systems

Please visit our website for more information: papathanlab.com

REPORTS & MEDIA

• Co-lead the Steering Committee of CEPI’s CMC Platform Best Practices initiative and co-led its Process Validation workstream, developing best practices to accelerate vaccine development and approval in outbreak emergencies. You can read the best practices here: https://tghncollections.pubpub.org/pub/ehrwu33m/release/2
• My lab contributed to the Royal Society DELVE report on SARS-CoV-2 vaccine development and implementation (2020) and to CEPI’s CMC Platform Best Practices initiative.
• We develop tools and strategies to ramp up manufacturing and supply chain distribution capacity for COVID-19 vaccines. You can read an overview here: https://www.imperial.ac.uk/news/197321/is-world-ready-produce-billion-doses/