Poolbeg Pharma plc (LON:POLB), a clinical stage infectious disease pharmaceutical company with a capital light clinical model, has partnered with leading global biopharma services company, Eurofins Genomics (‘Eurofins’), to complete RNA sequencing for Poolbeg of Respiratory Syncytial Virus (RSV) disease progression samples from human viral challenge studies.
This deep sequencing work is a key step leading to Poolbeg commencing Artificial Intelligence (AI) analysis of its RSV data and will mean that it then has full immunological datasets for RSV, as well as influenza, which are ready to use with AI platforms to identify drug targets and products for influenza and RSV indications. The Company already has RNA sequencing data for influenza. This data is unique as it covers the full disease cycle and presents significant opportunities to unlock insights into these diseases which will magnify the power of the AI analysis.
The project with Eurofins is expected to be completed by the end of 2021 and will involve next generation RNA sequencing of RSV transcriptomics, or disease progression data, which enables the tracking of the biology of immune responses in molecular detail during infection.
Sequencing of the samples will be tailored for incorporation into AI algorithms which will be the first time that human challenge trial immune data has been analysed using AI, unlocking unique insights from the rich dataset that Poolbeg will translate into additional pipeline products which will be progressed using its capital light clinical structure.
RSV is a contagious virus that affects the respiratory tract of children and at-risk older adults; in severe cases, it can cause pneumonia and other life-threatening breathing difficulties. RSV is a significant public health threat and is one of the leading causes of hospitalisation to at-risk older adults. There is currently no vaccine on the market for RSV.
Jeremy Skillington, PhD, CEO of Poolbeg Pharma, said:
“This is an exciting step in our AI data analysis programme. The deep genetic analysis of RSV progression will be key information to feed into AI drug and target discovery tools. We already have similar data for influenza so we will now have complete discovery datasets for both influenza and RSV.
Our AI analysis will be breaking new ground in data-driven drug discovery as it will be the first time that human challenge trial immune data is used in this way. Having the sequencing specially tailored to work with AI platforms will enable us to discover potential new drug candidates for both diseases in a quicker and more cost-effective way.”
