Academics at University College London (UCL) are working with Causaly to help accelerate various aspects of research into the current coronavirus pandemic, including identification of biomarkers and potential therapeutic agents. Causaly is a technology company that uses artificial intelligence (AI) techniques to 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 map epidemiology data, biomarker genes, molecular targets and identify potential treatment options.
Earlier this year, UCL Innovation & Enterprise and Causaly began exploring the potential of collaborating on a data-based project. With the ongoing escalation of COVID-19, the two organisations saw a greater opportunity to bring their collective expertise to bear on the coronavirus pandemic.
The UCL researchers have been working on a number of COVID-19-related research projects, including the development and delivery of a low-cost breathing aid, trials of a potential antiviral and rapid genome sequencing to get b a better understanding of the spread of the disease. Ongoing research into various aspects of the pandemic at UCL could be enhanced by Causaly’s technology and expertise – for example, helping to identify potential molecular targets of the disease.
The SARS-CoV-2 coronavirus 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. Causaly's AI additionally allows users to find biomarker genes and potential molecular targets of a disease.
