February 8, 2022

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Brainomix Announces the Development of a Proprietary AI-Trained Predictive Biomarker for Idiopathic Pulmonary Fibrosis (IPF)

The imaging biomarker has demonstrated superior prognostic value compared with traditional measures, and may provide a more reliable measurement of the effects of novel therapies in clinical trials

 

Oxford, UK, 8th February, 2022

 

Brainomix has announced that the latest version of its e-ILD software has been refined and validated using data from the Open Source Imaging Consortium (OSIC) Member Challenge. OSIC is a global, 501(c)(3), not-for-profit cooperative effort between academia, industry and patient advocacy groups created to enable rapid, open source advances in the fight against idiopathic pulmonary fibrosis (IPF), fibrosing interstitial lung diseases (ILDs), and other respiratory diseases, including emphysematous conditions.

Using a large set of anonymized HRCT scans and accompanying clinical data from the OSIC Data Repository, Brainomix applied an artificial intelligence, machine learning approach to the analysis of CT scans from patients with a diagnosis of IPF. The analysis demonstrated the value of several AI-powered imaging biomarkers including a proprietary biomarker which quantifies the extent of the lung affected by reticulo-vascular abnormalities.

The results of the Brainomix analyses have shown that this novel automated imaging biomarker quantified by the e-ILD software can predict both lung function decline and survival in IPF patients from a baseline CT scan. Furthermore, Brainomix has demonstrated that this quantification through e-ILD can enable a twofold increase in the ability to predict transplant-free survival versus the currently used Forced Vital Capacity (FVC) endpoint.

In the setting of a clinical trial, combining automated e-ILD imaging biomarkers with respiratory physiology would improve selection of patients most at risk of disease progression, and serial measurements would provide a more robust assessment of disease response to treatment. Composite endpoints including automated e-ILD image analysis offer a better surrogate of transplant-free survival than traditional clinico-physiological markers alone which are conventionally used in this setting.

Elizabeth Estes, Executive Director for the Open Source Imaging Consortium (OSIC) commented: “We are pleased to see these encouraging data and developments from Brainomix as they highlight the important value of our consortium in enabling the development of novel solutions to combat Pulmonary Fibrosis.”

Today’s announcement comes shortly after the Oxford-based company announced a Series B investment of £16M, along with plans to expand its AI-enabled portfolio into lung fibrosis and cancer, creating opportunities to form value-generating pharmaceutical partnerships that could improve clinical trial success, foster broader adoption of existing therapies in new indications, and improve patient outcomes.

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