A new partnership has been launched with AI specialist Casualy and University College London to research COVID-19.
The teams will explore the identification of biomarkers and potential therapeutic agents using AI techniques to read and interpret vast sources of information. This could be from previous research into similar viruses.
The technology uses AI to quickly read, understand and interpret vast databases of biomedical knowledge. The company uses machine-reading to surface evidence from 30 million biomedical publications in seconds, enabling researchers to quickly map epidemiology data, biomarker genes, molecular targets and identify potential treatment options.
Working with the AI specialist, UCL will focus on projects that include the development of therapeutics and diagnostic approaches to epidemiological models, mental health-focused strategies and healthcare system logistics.
Professor Spiros Denaxas, from the UCL Institute of Health Informatics “As a medical researcher working at the interface between care and research, Causaly allows me to rapidly ingest, analyse and derive insights from huge amounts of biomedical literature. Importantly, it allows us to focus on the translation of our research by enabling us to triangulate evidence derived from research and clinical guidelines.”
Dr Vassilis Georgiadis, UCL Innovation & Enterprise, added “Our partnership with Causaly strengthens UCL’s research and innovation tools to battle the COVID-19 pandemic, giving our researchers superior access to existing biomedical knowledge. What’s impressive is that Causaly’s platform mimics how humans read cognitively. The company is looking to understand the context of data in text itself, extracting evidence and causality, which we hope will provide significant benefits to our research groups working on COVID-19 related projects.”
The company said “COVID-19 shares some molecular pathway similarities with other betacoronaviruses, such as the Severe Acute Respiratory Syndrome-CoV (SARS-CoV) and the Middle East Respiratory Syndrome-CoV (MERS-CoV). Causaly’s AI platform enables the rapid identification of all previously reported drugs for the betacoronavirus genus and also uncovers relationships that would not be obvious from a traditional literature review search.”
Yiannis Kiachopoulos, Co-founder and CEO at Causaly, said “By using Causaly, UCL researchers will be able to unlock hidden evidence in biomedical literature faster, exploring mechanisms of action, treatments, side effects and more, using our cause-and-effect database that maps over 170 million relationships.”
