OneThree Biotech completes build and optimization of AI model for RSV data

RSV infections in children

Poolbeg Pharma, a clinical stage infectious disease pharmaceutical company, says its artificial intelligence (AI) partner, OneThree Biotech, Inc., has completed the build and optimization of a tailored AI model of Poolbeg’s respiratory syncytial virus (RSV) human challenge data and can now commence its analysis.

Results are expected in Q4 2022.

The tailored AI model is the platform from which OneThree Biotech and Poolbeg will mine insights from human challenge trial derived disease progression data, with the aim of identifying novel drug targets and therapies to treat RSV, a disease which is a significant public health threat.

OneThree’s clinically validated model has been optimized to harness the clinical, molecular (e.g. gene and protein expression) and virological data collected during human challenge trials, and includes next-generation sequencing data captured daily at all timepoints before, during and after a healthy volunteer has been infected with RSV. 

The company said the controlled environment of the human challenge trial creates a clean and complete dataset suited for AI disease modeling such as this. The research team has integrated OneThree Biotech’s AI with Poolbeg’s dataset and publicly available datasets to optimize the power of the model and validate its results. 

The team will use the model to discover and identify the disease signatures that define RSV infection and then identify drugs that can effectively reverse those signatures with therapeutically meaningful benefits with a view to then adding such identified drugs to Poolbeg’s pipeline.

Producing candidates quickly

The research program will prioritize identifying drug candidates with existing phase I safety and tolerability data generated during prior development for other disease indications. This approach reduces spend and risk, with the resultant clinical development program progressing to a capital light clinical proof of concept trial. The approach is expected to generate multiple clinical stage candidates quickly and cost-effectively, in a manner consistent with Poolbeg’s model.

Jeremy Skillington, CEO of Poolbeg Pharma, said: “OneThree Biotech’s AI model optimization has been completed on time and is on-track to deliver results later this year. This is the first time that AI has been used to model RSV with the complete longitudinal disease data which can only be produced from human challenge trials. 

“We are excited to see the insights into RSV that can be generated from this analysis which will help us to identify the best potential drug candidates to develop as part of our rapid, capital-light portfolio. RSV is a disease with a significant unmet medical need which causes an estimated 100,000 deaths per year in children under the age of five, we hope that the results from this programme can help us to identify an effective treatment to address this significant public health threat.”

Poolbeg also has an AI partnership with CytoReason, which is focused on drug target identification for influenza infections. This is currently in the modeling stage.

About respiratory syncytial virus

RSV is a common contagious virus affecting the lungs and breathing passages. It is one of the major remaining infectious diseases for which there is currently no vaccine or specific treatment.

Older adults are at high risk for severe disease due to age-related decline in immunity and underlying conditions. RSV can exacerbate conditions including chronic obstructive pulmonary disease, asthma and chronic heart failure and can lead to severe outcomes, such as pneumonia, hospitalization, and death.

RSV is also the most common cause of bronchiolitis (inflammation of the small airways in the lung) and pneumonia in children younger than 1 year of age in the U.S.

Each year, RSV causes more than 360,000 hospitalizations and 24,000 deaths globally in adults. Adults with underlying conditions are more likely to seek medical advice and have higher hospitalization rates than adults without these conditions.

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