Brainomix Reports Positive AI Imaging Data in IPF Trial

Oxford, United Kingdom, September 8, 2026

AI Imaging Detects Changes in Lung Fibrosis

The analysis was conducted using data from Endeavor BioMedicines’ EXCITE Phase 2a clinical trial, which evaluated ebzirfan, an investigational monoclonal antibody targeting integrin αvβ6, in patients with IPF. Brainomix applied its e-Lung quantitative imaging platform to HRCT scans collected during the clinical study, enabling researchers to objectively measure changes in lung abnormalities associated with fibrosis. According to the companies, the quantitative analysis identified differences in lung fibrosis progression between treatment groups. The technology generated quantitative measurements from CT images that could provide a more detailed assessment of disease changes than visual evaluation alone. Such approaches are increasingly being investigated in respiratory medicine because IPF is characterized by progressive scarring of lung tissue that can be difficult to measure accurately using conventional methods. The findings are particularly relevant to clinical drug development, where sensitive and reproducible biomarkers can help researchers determine whether an investigational therapy is affecting disease biology. Quantitative imaging may also help reduce variability associated with subjective radiological assessments and potentially identify treatment effects earlier.

Ebzirfan Targets Fibrotic Disease Pathway

Ebzirfan is an investigational therapy designed to inhibit integrin αvβ6, a molecular pathway involved in the activation of transforming growth factor beta (TGF-β), an important driver of fibrosis. By targeting αvβ6, the therapy is intended to reduce pathological signaling associated with the development and progression of fibrotic tissue. The EXCITE Phase 2a study evaluated the safety and efficacy of ebzirfan in patients with IPF. IPF is a chronic and progressive interstitial lung disease in which scar tissue gradually accumulates in the lungs, impairing respiratory function and limiting the ability to exchange oxygen. The use of quantitative CT analysis provides another layer of evidence for evaluating potential treatment effects. Brainomix said its analysis showed that quantitative imaging biomarkers were sensitive to changes in fibrotic lung disease, supporting their potential application as clinical trial endpoints or exploratory biomarkers. However, the imaging findings should be interpreted alongside established clinical measures such as forced vital capacity (FVC), exercise capacity and patient outcomes. Quantitative imaging remains an investigational approach in this context and does not by itself establish the clinical effectiveness of ebzirfan.

Imaging Biomarkers Could Strengthen IPF Trials

The presentation at ERS Congress 2026 highlights the growing role of artificial intelligence and quantitative imaging in respiratory clinical research. Traditional clinical-trial assessments can require relatively large patient populations and extended follow-up periods to detect meaningful changes in slowly progressing diseases such as IPF. AI-supported image analysis could potentially address some of these challenges by extracting standardized quantitative measurements from routine medical images. Brainomix’s e-Lung platform is designed to analyze lung CT scans and characterize features associated with interstitial lung disease and pulmonary fibrosis.

For pharmaceutical developers, the ability to generate reproducible imaging biomarkers could have implications for patient stratification, treatment monitoring, endpoint development and clinical-trial design. More objective measurements could also help researchers understand how investigational therapies affect structural changes in the lungs. The companies said the new findings strengthen the evidence supporting quantitative imaging as a tool for evaluating fibrotic lung disease. Further clinical validation will be necessary to determine how these biomarkers can be incorporated into regulatory-grade clinical development programs. Overall, the Phase 2a analysis represents an intersection of AI-enabled medical imaging and pharmaceutical drug development, demonstrating how advanced image quantification could improve the evaluation of investigational treatments for idiopathic pulmonary fibrosis and other progressive fibrotic diseases.

Source: Brainomix press release