UK headquartered AI precision medicine company PrecisionLife has identified 59 repurposing drug candidates that could be used to develop new therapeutic strategies to increase the survival rate of patients who develop sepsis while suffering from severe Covid-19.
Data scientists from PrecisionLife used the company’s proprietary AI enabled precision medicine platform to identify the repurposing drug candidates. The new study, released on open access preprint repository Biorxiv, sought to identify genetic risk factors for sepsis especially in the context of Covid-19, and to use these insights to identify existing drugs that might be used to treat life-threatening late-stage disease. “Ours is the first study looking at host genomics and opportunities to treat later stage severe disease where host immune processes take over”, said Dr Steve Gardner, CEO, PrecisionLife.
“Like the initial genomic studies on Covid-19 patients, previous analyses of sepsis patients have failed to identify more than a handful of genetic variants that predispose individuals to developing the disease. By providing deeper insights, this study identifies novel approaches and hope for new therapies”, said PrecisionLife, which analysed patient datasets compiled by UK Biobank to identify genes associated with sepsis, which are also found in severe COVID-19 patients. Sepsis is reported to be observed in 60% of severe Covid-19 patients and is a life-threatening condition with a mortality rate of approximately 20%.
PrecisionLife said it identified mutations in 70 sepsis risk genes, 61% of which were also present specifically in severe Covid-19 patients. Several of the disease associated genetic signatures found in both sepsis and severe Covid-19 patients are said to have been previously linked to cancer, immune response, endothelial and vascular inflammation and neuronal signalling. Of the sepsis risk genes, which the study shows are also Covid risk genes, 13 are known to be druggable, that is, targeted by active chemical compounds used to treat these other diseases and therefore represent potential drug repurposing opportunities. The study went on to identify 59 compounds and drugs that are known to be active against these 13 targets, which could form the basis for future drug trials and repurposing projects, as well as offer potential as Covid-19 high risk biomarkers.
As more COVID-19 patient data becomes available in UK Biobank and other patient data sources, PrecisionLife said it will be able to analyse the clinical impact of these disease signatures in a larger group of patients.
Image: Disease architecture of the sepsis cohort generated by the PrecisionLife platform. Each circle represents a disease associated SNP genotype, edges represent co-association in patients, and colors represent distinct patient sub-populations or ‘communities’.