The ever-increasing quest for rapidly designing and deploying efficient biopharmaceutical production lines worldwide is timely more than ever, as mankind faces global health and safety risks, from ageing to epidemics and from well-understood ailments to new pathogens. The World Health Organisation (WHO) recognises that numerous biotherapeutic products succeed in treating many life-threatening chronic diseases, but their manufacturing cost remains prohibitive, thus limiting their use and spread, particularly in developing countries. Unlike small molecules, our mechanistic understanding of the respective reaction landscapes is often remarkably limited, rendering biopharma production intensification very challenging.
This PhD research project at the University of Edinburgh (UoE) School of Engineering will employ advanced process modelling and optimisation methods in order to quantitatively understand and evaluate biomolecular reaction mechanisms, with a view to scaling them up towards design and operational optimisation of advanced biopharmaceutical manufacturing. Current research efforts to this end promise a significant worldwide impact if successful, since suppressing production costs paves the way for affordable access to critical healthcare.
This project will develop computational tools and systematic methodologies for biopharma process intensification by selecting biomolecules of high therapeutic value, reviewing current progress in mechanistic understanding of biomolecular synthesis pathways, and developing process modelling platforms for technoeconomic optimisation of biopharma manufacturing.
The Gerogiorgis Research Group at the School of Engineering (University of Edinburgh) employs high-fidelity first-principles modelling and advanced numerical methods for systematic synthesis, design and optimisation of complex chemical processes, with emphasis on continuous pharmaceutical manufacturing and comparative technoeconomic analyses for pharmaceuticals, bioproducts, food/drinks and energy. Their research is recognized with multiple IChemE Global Award distinctions, an Academy of Athens research publication prize, and a recent Royal Academy of Engineering (RAEng) Industrial Fellowship.
An advanced undergraduate degree (MEng or Dipl. Eng.) in Engineering (2:1 or higher), preferably with prior (Dipl./MEng thesis) research experience, is required. Strong numerical modelling (e.g. MATLAB) skills are essential; moreover, process simulation and optimisation (e.g. gPROMS/ASPEN/UNISIM) skills are desirable.
Further information on English language requirements for EU/Overseas applicants.
Applications are welcomed from self-funded students, or students who are applying for Scholarships from the University of Edinburgh or elsewhere