Calendar An icon of a desk calendar. Cancel An icon of a circle with a diagonal line across. Caret An icon of a block arrow pointing to the right. Email An icon of a paper envelope. Facebook An icon of the Facebook "f" mark. Google An icon of the Google "G" mark. Linked In An icon of the Linked In "in" mark. Logout An icon representing logout. Profile An icon that resembles human head and shoulders. Telephone An icon of a traditional telephone receiver. Tick An icon of a tick mark. Is Public An icon of a human eye and eyelashes. Is Not Public An icon of a human eye and eyelashes with a diagonal line through it. Pause Icon A two-lined pause icon for stopping interactions. Quote Mark A opening quote mark. Quote Mark A closing quote mark. Arrow An icon of an arrow. Folder An icon of a paper folder. Breaking An icon of an exclamation mark on a circular background. Camera An icon of a digital camera. Caret An icon of a caret arrow. Clock An icon of a clock face. Close An icon of the an X shape. Close Icon An icon used to represent where to interact to collapse or dismiss a component Comment An icon of a speech bubble. Comments An icon of a speech bubble, denoting user comments. Comments An icon of a speech bubble, denoting user comments. Ellipsis An icon of 3 horizontal dots. Envelope An icon of a paper envelope. Facebook An icon of a facebook f logo. Camera An icon of a digital camera. Home An icon of a house. Instagram An icon of the Instagram logo. LinkedIn An icon of the LinkedIn logo. Magnifying Glass An icon of a magnifying glass. Search Icon A magnifying glass icon that is used to represent the function of searching. Menu An icon of 3 horizontal lines. Hamburger Menu Icon An icon used to represent a collapsed menu. Next An icon of an arrow pointing to the right. Notice An explanation mark centred inside a circle. Previous An icon of an arrow pointing to the left. Rating An icon of a star. Tag An icon of a tag. Twitter An icon of the Twitter logo. Video Camera An icon of a video camera shape. Speech Bubble Icon A icon displaying a speech bubble WhatsApp An icon of the WhatsApp logo. Information An icon of an information logo. Plus A mathematical 'plus' symbol. Duration An icon indicating Time. Success Tick An icon of a green tick. Success Tick Timeout An icon of a greyed out success tick. Loading Spinner An icon of a loading spinner. Facebook Messenger An icon of the facebook messenger app logo. Facebook An icon of a facebook f logo. Facebook Messenger An icon of the Twitter app logo. LinkedIn An icon of the LinkedIn logo. WhatsApp Messenger An icon of the Whatsapp messenger app logo. Email An icon of an mail envelope. Copy link A decentered black square over a white square.

Aberdeen University will use innovative approach to tackle Covid-19

Mirela Delibegovic will lead the research at Aberdeen University.
Mirela Delibegovic will lead the research at Aberdeen University.

Aberdeen University will use artificial intelligence in an attempt to develop a fast-track test that could help in the mass screening process for Covid-19.

The Scottish Government has given the £140,000 project the green light, allowing researchers begin working to identify specific elements of the virus that trigger the body’s defence systems.

The team will work with Vertebrate Antibodies Ltd (Val) and their technology to develop a sensitive test that could then be used for mass screening of NHS staff and keyworkers.

It would help identify high-risk patients and carriers, provide data on the prevalance of Covid-19 and allow for targeted vaccinations in the future.

Lead investigator Professor Mirela Delibegovic said: “By working with Val’s team and using their established expertise in antibody design and production enhanced by harnessing artificial intelligence, we hope to create a diagnostic test that can quickly and effectively identify Covid-19 in individuals.

“By employing this innovative approach, we hope to achieve high-throughput capacity in a proven format that will enable mass testing which could benefit key workers and the most vulnerable members of society.”

The project has received £101,903 funding from the Scottish Government as well as a £38,000 contribution from Val – a bio-tech spin-out company from Aberdeen University – and is due to last six months.

Dr Ayham Alnabulsi, co-founder and chief executive of Val, added: “Vertebrate Antibodies is pleased that it is able to contribute its proprietary AI technology, EpitopePredikt, and the expertise of its technical team to help develop an assay  that could underpin a test that would help with the national effort to manage the COVID-19 pandemic.”

The project was pitched in response to the Scottish Government’s funding announcement for research aimed at tackling the challenges of the pandemic.

St Andrews University has also been awarded three research projects as part of the rapid research programme.

Professor Colin McCowan will lead research using a tracker app to explore differences between patients, identify community cases and link this with medical records.

The second project, led by Dr Nathan Bailey, will look at the evolution of the virus strain that causes Covid-19.

And Dr Ruth Bowness will use a mathematical model to stimulate the infection in the body and the spread from person to person to create predictions.