Skip to main content

Oxford University today joins a consortium led by the digital quantum computing company, SEEQC, to build and deliver a full-stack quantum computer for pharmaceutical drug development for Merck KGaA. The consortium has today been awarded a £6.85M grant by Innovate UK’s Industrial Strategy Challenge Fund (ISCF) to build a commercially scalable quantum computer designed to tackle prohibitively high costs within pharmaceutical drug development. The partnership will accelerate the use of quantum computing within pharmaceutical research to dramatically reduce the time required for drug development on a global scale.

Professor Charlotte Deane, who leads the Oxford Protein Informatics Group in the Department of Statistics and Professor Frank Von Delft, at the Centre for Medicines Discovery at the Nuffield Department of Medicine, will be leading from Oxford University. Find out more.

Related News

What does a statistician do for the England football team?

From squad selection to modelling how footballs behave at altitude, statistician Matt Penn explains how data is helping shape the modern game, and why coaches will always matter more than the numbers.

New evidence suggests vast hidden magma systems inside Mars

Researchers from the Departments of Earth Science and Statistics have found evidence that Mars once hosted enormous, Earth-like magmatic systems deep below its surface – even though the planet lacks the plate tectonics long considered essential for this kind of geological complexity. The findings open up new possibilities for how rocky planets become habitable.

Finding a needle in the genomic haystack: Targeting rare genes using statistical outliers

In statistical modelling, extreme outliers are often written off as 'noise'. But a new study by researchers from Oxford's Department of Statistics and Big Data Institute published this week in The American Journal of Human Genetics reverses that principle, using these outliers as the basis of a targeting system for locating rare, high-impact genetic mutations.