First time that AI analysis of human challenge trial data is used to identify novel drug targets for influenza
Use of AI will help identify more targets, quicker and more cost effectively than previously possible
24 March 2022 – Poolbeg Pharma (AIM: POLB, ‘Poolbeg’ or the ‘Company’), a clinical stage infectious disease pharmaceutical company with a unique capital light clinical model, has signed a deal with CytoReason , a leading artificial intelligence (AI) company developing computational disease models for efficient drug discovery and development, to provide AI analysis of Poolbeg’s influenza disease progression data derived from human challenge study samples.
The partnership will harness the insights of Poolbeg’s unique repository of influenza human challenge trial* data and is another significant milestone in its strategy to leverage its proprietary databank to identify new pharmaceutical assets using artificial intelligence. CytoReason has built world-class validated AI models which can extrapolate immune cell behaviour based on bulk transcriptomics, making it an ideal partner to maximise the insights of Poolbeg’s influenza data. To date, five of the world’s top ten pharma companies use CytoReason’s technology including Pfizer, Sanofi, Merck KGaA and Roche. Poolbeg’s ability to execute a deal of this nature with a company of CytoReason’s stature is a testament to the quality of Poolbeg’s proprietary databank which will significantly improve the outputs of the collaboration.
The partnership will bring Poolbeg’s unique repository of clinical samples and associated data from influenza human challenge trials together with CytoReason’s leading and validated AI technology. This will enable a deep understanding of the mechanism of influenza infection and recovery and, as a result, help identify novel drug targets for the disease. Poolbeg’s datasets for influenza are already tailored for incorporation into CytoReason’s platform algorithms. Both CytoReason and the Company are excited about the unique and novel disease-relevant insights, which have the potential to transform how influenza is currently treated. T he project is due to commence immediately with a full work programme already agreed, and first results expected in H1 2023.
CytoReason’s machine learning algorithm works by combing through enormous repositories of clinical data to build models of human disease, which can then be used by biotech and pharmaceutical partners to identify novel targets, prioritise mono/combination therapies, find biomarkers, and understand which patients will benefit most from those new treatments. CytoReason will build a tailored AI model using its existing clinical data in conjunction with Poolbeg’s human challenge data to maximise the insights generated. As a result, CytoReason will be able to prioritise new drug targets quickly and cost effectively, in a manner consistent with Poolbeg’s business model. Based on the target identification insights generated from the analysis, the Company plans to source drugs with existing Phase I safety data that can immediately continue clinical development to rapidly generate early human proof of concept data for influenza, with the ultimate aim of monetising the asset through partnerships and licensing deals with pharma and biotech .
This is the first time that AI analysis has been undertaken on influenza human challenge disease progression data and samples. Data from human challenge studies are unique in that they track a healthy subject through disease to recovery in carefully controlled and monitored isolation units, collecting samples throughout the course of disease, and vitally collecting matched baseline and follow-up samples before and after infection. CytoReason will be analysing blood transcriptomics, proteomics, DNA sequences and viral loads and disease signs and symptoms from the human challenge studies .
This deal comes at a time when the threat of influenza is significant. Cases are at their highest globally since the COVID-19 pandemic began where pre-pandemic one in eight people were affected, resulting in five to ten million hospitalisations and 500,000 deaths each year. Poolbeg’s asset, POLB 001, which is progressing towards its first human challenge trial in June 2022, was identified using the unique disease progression data available from human challenge trials. By utilising AI, the Company will identify more targets, quicker and more cost effectively than previously possible without this technology.
This is Poolbeg’s latest AI deal following the partnership with OneThree Biotech, Inc. announced in February 2021 to identify new drug targets and treatments for Respiratory Syncytial Virus (‘RSV’).
Jeremy Skillington, PhD, CEO of Poolbeg Pharma, said:
“This exciting deal is all about creating opportunities. Opportunities to unlock the potential of our unique bank of human challenge data. Opportunities to develop drugs for infectious disease more quickly and cost effectively. And opportunities to tackle the growing global threat of influenza.
“This is the first time AI analysis will be undertaken on influenza human challenge trial data and we look forward to the results early next year. We are delighted to be working with such an industry leading partner as CytoReason and using cutting-edge AI technology as we continue to develop and progress our innovative infectious disease drug pipeline.”
David Harel, CytoReason’s CEO , said:
“We are excited about the potential of Poolbeg’s data and are delighted to be the first AI company to analyse Influenza human challenge data. Our top-tier scientists, along with our platform of computational disease models, will enable Poolbeg to significantly shorten the drug discovery time for Influenza treatments, dramatically reduce the costs involved, and ultimately help more patients.”
*A human challenge study is a controlled clinical infection trial whereby individuals are intentionally exposed to a virus, or a condition caused by a virus is simulated, to assess the impact of treatments.
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Poolbeg Pharma Plc
Jeremy Skillington, CEO
Ian O’Connell, CFO
+44 (0) 207 183 1499
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