Brainomix e-Lung AI chosen as co-primary endpoint in Boehringer Ingelheim Phase 3 trial

Brainomix, a global leader and pioneer of AI-powered imaging tools in lung fibrosis and stroke, today announced it was selected by Boehringer Ingelheim, the leading biopharmaceutical company providing therapeutic options for interstitial lung disease (ILD), to provide objective, quantitative HRCT imaging biomarkers as a co-primary endpoint in the DROP-FPF Phase 3 study.

DROP-FPF is a Phase 3b double blind, randomized, placebo-controlled study investigating the safety and effectiveness of nerandomilast (Jascayd®) in individuals with interstitial lung abnormalities (ILA’s) and a family history of pulmonary fibrosis. Jascayd® received FDA approval for both idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF) in late 2025, ushering in a new therapeutic option to help manage these devastating forms of ILD.

The study, set to initiate patient enrollment in January and include a two-year follow-up period, will investigate whether early intervention with nerandomilast slows the progression of early signs of pulmonary fibrosis in people with a family history of the condition. Pulmonary fibrosis causes irreversible lung damage and impacts 3-4 million people worldwide1. Yet individuals at elevated risk due to family history currently have no approved treatment options until symptoms emerge, often after substantial lung damage has already occurred.

This trial marks the first time that automated, quantitative high-resolution CT (HRCT) imaging biomarkers will serve as a co-primary endpoint in a Phase 3 ILD study. Brainomix’s AI-powered e-Lung software will provide objective measurements of fibrosis extent and disease severity by analyzing HRCT scans at baseline and at follow-up timepoints.

Martin Beck, Senior VP and Head of Therapeutic Area Inflammation at Boehringer Ingelheim, commented:

IPF and PPF are serious, progressive lung diseases that can be more life-threatening than some forms of cancer. They progress silently, with early symptoms often dismissed as ageing or misdiagnosed. But in a progressive disease, there is no going back. Once fibrosis advances, the damage is irreversible. That’s why this study is so important. Our goal is simple but profound: learn whether acting earlier can change outcomes for families facing these devastating diseases. Using Brainomix’s advanced HRCT algorithms to define meaningful progression, we aim to generate insights that could transform how and when to intervene.

Professor Peter George, Consultant Pulmonologist at the Royal Brompton Hospital, UK and Brainomix Senior Medical Director, added:

Accurate and reliable quantification of subtle but clinically meaningful features of disease progression is essential to achieving the objectives of this study. Brainomix e-Lung enables this through validated, proprietary, AI-driven CT biomarkers that accurately quantify physiologically meaningful features of interstitial lung disease. This information can reveal whether disease biology is changing, even when patients still appear clinically well and have normal lung function, allowing researchers to detect treatment effects far earlier than previously possible. This has the potential to significantly improve clinical trial design.

The AI-powered and FDA-cleared e-Lung software has been trained on large, diverse datasets of patients with various forms of ILD and has been validated in the Phase 3 INBUILD study that originally led to the approval of nintedanib (Ofev®) in patients with progressive pulmonary fibrosis.

The DROP-FPF study will be delivered in partnership with Voiant – the industry leading AI-based clinical trial imaging solution provider – leveraging Brainomix’s advanced imaging biomarkers alongside Voiant’s centralized image management and analytics framework.

Jessica Ataharul, Vice President of Clinical Operations at Voiant, said:

AI-driven quantitative imaging analysis enables more confident detection of treatment effects while improving efficiency through smarter patient selection and optimized trial design. By combining Brainomix’s advanced imaging biomarkers with Voiant’s independent imaging and analytics framework, the study will deliver higher-precision respiratory endpoints with greater speed and reliability.