UK-based biotechnology firm Nuclera has been awarded two Innovate UK grants totalling £1.14 million to further develop its eProtein Discovery system. The funding comprises a £790,000 flexible, agile, scalable, and sustainable technologies (FASST) grant and a £350,000 Engineering Biology grant.

Collaborative efforts to enhance protein expression technology

The FASST grant, awarded in collaboration with DeepMirror, is part of the Innovate UK Transforming Medicines Manufacturing (TMM) programme. This initiative aims to bolster the UK’s capabilities in pharmaceutical manufacturing by developing novel technologies to expedite patient access to new therapies.

For the Engineering Biology grant, Nuclera will work with independent experts Dr Konstantinos Beis from Imperial College London and Dr Andrew Quigley from Diamond Light Source to evaluate and refine the platform.

Dr Michael Chen, CEO and co-founder of Nuclera

Addressing challenges in drug discovery and protein manufacturing

Nuclera’s eProtein Discovery platform aims to overcome the time and cost constraints associated with custom protein reagent production in drug discovery. The system purportedly accelerates drug discovery processes by up to 30-fold, providing rapid access to challenging proteins in less than 48 hours using a benchtop system.

Dr Michael Chen, CEO and co-founder of Nuclera, said: “Receiving both grants from Innovate UK is testament to the power of eProtein Discovery and demonstrates that Nuclera has the technical innovation to address global unmet challenges in the fields of manufacturing and engineering biology.”

Potential impact on membrane protein research

Dr Quigley, group leader of Diamond’s Membrane Protein Lab (MPL), commented on the collaboration: “Nuclera’s proposed platform aims to assess the most suitable conditions to obtain functional protein, and the MPL is well positioned to assist in this development with over 30 different membrane protein controls available.”

Nuclera’s eProtein Discovery platform not only produces proteins rapidly but also provides sequences and optimal conditions to inform protein manufacturing processes, potentially streamlining research and development in the pharmaceutical industry.