As we navigate the?COVID-19 pandemic, it is clear that having the right tools and technology to fight infectious diseases is at the forefront of healthcare innovation priorities. In times like these, we have seen that it is vital to act quickly to mitigate consequences to human populations, the economy, and the ecosystem.?

In addition, the emergence of new variants of the COVID-19 virus has shown that it is of critical relevance to keep track of them in the community as both natural and acquired immunity wanes.?With this consideration in mind, a group of scientists from the?, a United Nations Academic Impact (UNAI) member institution in the United Kingdom, recently joined forces with Vertebrate Antibodies Ltd and the National Health Service (NHS) Grampian to tackle the ongoing pandemic.?

Their partnership has resulted in the development of ground-breaking antibody tests combining innovative artificial intelligence (AI) and epitope display technologies. The collaborative team of scientists, clinicians, and AI experts, worked tirelessly to develop serology tests, known as antibody tests, that could help address these various challenges as they emerge. However, existing antibody technologies suffer from inherent limitations affecting their performance.?

In practice this means that existing available tests can be inaccurate with low sensitivity, especially in detecting mutations, which in many cases are far more transmissible. Funded by the Rapid Response in COVID-19 (RARC-19) research program of the Scottish Government, the team used AI technology, termed EpitopePredikt?, to identify specific elements of the virus. The objective was to see which one of such elements trigger the body’s immune defense.

So, the researchers developed a new way, coined EpitoGen? technology, to combine and display up to 100 of these viral elements as they would appear naturally as part of the virus using a biological platform.?This innovative technology resulting from this scientific endeavor effectively detects an antibody response to new variants without losing accuracy. Quality assurance assessments demonstrated that these tests detected antibody responses from patient samples with more than 99% accuracy.?

Furthermore, the new tests can assess the long-term immunity of the individuals and whether immunity is vaccine-induced or is just a natural result of previous exposure to the infection – information that is indeed invaluable in helping to prevent the spread of infection, and shape public health guidelines and regulations. Currently, available tests struggle to detect variants of the virus and give little or no information about the real impact of virus mutations on vaccine performance.??

The new tests can also provide information that can be used to estimate the duration of the vaccine's immunity and the effectiveness of the vaccine on emerging variants. This data is quite critical to obtaining an accurate picture of the outbreak and its evolution, providing information that could inform and influence public health measures.?“The virus mutates into more transmissible variants, which means that we need a novel approach to incorporate mutant strains into the tests,” said professor Mirela Delibegovic, project lead from the university.

“This is a game-changing technology with the tremendous potential to change the trajectory of global recovery from the COVID-19 pandemic,”?she emphasized. The innovation and advancement of sensitivity that this new technology provides ensure affordable, accurate testing for many auto-immune conditions. These new antibody tests may prove to be an enhancement mechanism for both diagnostics and the promotion of health, something fundamental particularly during these challenging circumstances.

These efforts by scientists of the University of Aberdeen align with?, within the 2030 Agenda for Sustainable Development It shows how scientific knowledge and expertise in institutions of higher education are making a significant contribution to addressing the ongoing pandemic while helping to boost global public health.