How Sharing Clinical Science Research During the Pandemic has better Prepared Us for The Future
“The scientific community working together can do some pretty amazing things.” That was the conclusion of John Cooke, M.D., a hospital director from Houston, when reflecting on the pandemic. Previously, vaccine development has taken up to 20 years, but researchers were able to accelerate the process to produce a coronavirus vaccine in only eleven months, changing the future of drug development. Here Charlie Rapple, co-founder of science showcase Kudos, explores other ways the pandemic has been a catalyst for research discoveries.
People want to believe that science deals in absolute truths – that scientific ‘facts’, once established, don’t change, but they do. Science is a process of constantly expanding knowledge, and new research can contradict what was previously understood to be true. The pandemic threw this reality into stark relief – both in terms of the public’s expectations of scientific infallibility and the pace that scientists’ own beliefs were challenged. In a 2022 Guardian interview, several scientists acknowledged they had changed their minds as the pandemic progressed, on topics ranging from vaccines to the use of masks. Professor Peter Openshaw of Imperial College London, for example, had not expected COVID vaccines to work, explaining “there had been no example of a vaccine for a human coronavirus, yet they were more effective than I’d hoped.”
Innovation
There was a lot of innovation during the pandemic, from increased telemedicine devices to experimental treatments. As the pandemic identified one area for improvement, scientists and healthcare practitioners strove to solve it. One of the biggest challenges faced during the pandemic was the ability to stay ahead of the virus. Hospitals and other care facilities became overwhelmed by the high infection rate before they could find a solution, needing to process high volumes of data to identify patterns in symptoms, infection rates, and virus longevity. However, this helped fast-track automated processes. For example, developments in artificial intelligence can identify patterns in symptoms and other ‘red flags’ to healthcare professionals. These can help provide early diagnosis of infections, quicken drug discovery, and identify warning signs for diseases so that healthcare workers can better manage cases early on. AI and machine learning can then build platforms for automatic monitoring and predicting the spread of the virus, including identifying virus ‘hot spots’ to make it easier to find those who had come into contact, like the NHS Track and Trace app. According to research by De Gruyter, the World Economic Forum used its ML expertise to help researchers and practitioners analyse large volumes of data to forecast the spread of COVID. The tools act as an early warning system for future pandemics while also identifying vulnerable populations and predicting what treatment will be the most effective.
While this study showed the benefits of using digital technologies in healthcare, it also explored its limitations. Currently, AI technologies are not as advanced as they need to be, hindering accuracy when making predictions. AI can also amplify inequalities and bias in training data. This research highlighted both AI’s advancements and limitations, giving scientists a deeper understanding of how reliable AI can be and the steps needed to improve this in the future. The improvements outlined in the research can help contain future virus outbreaks to avoid the challenges faced over the last few years.
Treatment
During the pandemic, scientists used research conducted during previous research into other illnesses to streamline treatment options. For example, there was already research conducted on the Coronavirus family – SARS and MERS by The University of Oxford. This research offered scientists a head start on COVID-19. As of early 2022, very few drugs have been approved by the World Health Organization to treat critical COVID cases. During the pandemic, Hoang Linh Nguyen et al found that remdesivir, which can block the activity of RNA-dependent RNA polymerase (RdRp) in old SARS-CoV and MERS-CoV viruses, had been used to treat symptoms of COVID in many countries.
