AI is quietly reshaping clinical trials—and not just by speeding up drug discovery. In a notable milestone for medical imaging and respiratory research, Brainomix has been selected by Boehringer Ingelheim to provide AI-powered imaging biomarkers as a co-primary endpoint in a Phase 3 pulmonary fibrosis study.
The decision marks the first time automated, quantitative high-resolution CT (HRCT) imaging biomarkers are being used as a co-primary endpoint in a Phase 3 interstitial lung disease (ILD) trial. It’s a move that could change how disease progression is measured—and how early treatments are evaluated—in conditions where damage is often irreversible by the time symptoms appear.
A New Standard for Measuring Lung Disease
The study, known as DROP-FPF, is a Phase 3b, double-blind, randomized, placebo-controlled trial investigating nerandomilast (Jascayd®) in individuals with interstitial lung abnormalities (ILAs) who also have a family history of pulmonary fibrosis.
That population is critical—and underserved. Pulmonary fibrosis affects an estimated 3–4 million people worldwide, yet individuals at high genetic risk currently have no approved treatment options until symptoms emerge, often after substantial and permanent lung damage has already occurred.
DROP-FPF aims to answer a simple but consequential question: Can early intervention slow disease progression before fibrosis becomes clinically obvious?
To do that, the trial needs measurement tools sensitive enough to detect subtle changes long before lung function declines. That’s where Brainomix comes in.
Why Brainomix Matters Here
Brainomix’s AI-powered e-Lung software will analyze HRCT scans at baseline and follow-up timepoints, providing objective, quantitative measurements of fibrosis extent and disease severity.
Unlike traditional endpoints—such as lung function tests or symptom progression—AI-derived imaging biomarkers can detect structural changes in lung tissue even when patients appear clinically stable.
This capability is what elevates Brainomix’s role from “supporting technology” to co-primary endpoint provider, putting AI-derived imaging on equal footing with conventional clinical measures.
For clinical trials, that’s a big deal.
From FDA Approval to Earlier Intervention
The timing is significant. Nerandomilast (Jascayd®) received FDA approval in late 2025 for both idiopathic pulmonary fibrosis (IPF) and progressive pulmonary fibrosis (PPF), adding a new option for managing advanced disease.
DROP-FPF extends that momentum upstream—testing whether treatment can make a difference before fibrosis becomes clinically entrenched.
According to Martin Beck, Senior VP and Head of Therapeutic Area Inflammation at Boehringer Ingelheim, early detection is essential in diseases that progress silently.
“Once fibrosis advances, the damage is irreversible,” Beck said. “Using Brainomix’s advanced HRCT algorithms to define meaningful progression, we aim to generate insights that could transform how and when to intervene.”
That framing underscores why AI-based imaging is so attractive here: it offers a way to see progression earlier, more precisely, and more consistently than human interpretation alone.
AI Imaging Moves From Validation to Center Stage
Brainomix’s technology isn’t new to late-stage trials. Its FDA-cleared e-Lung software has been trained on large, diverse ILD datasets and previously validated in the Phase 3 INBUILD study, which supported the approval of nintedanib (Ofev®) for progressive pulmonary fibrosis.
What’s different now is the role the technology is playing.
Rather than serving as an exploratory or secondary measure, Brainomix’s biomarkers will directly influence how efficacy is judged in a pivotal trial. That shift reflects growing confidence in AI-driven quantitative imaging as a regulatory-grade endpoint.
Professor Peter George, Consultant Pulmonologist at the Royal Brompton Hospital and Brainomix Senior Medical Director, emphasized the importance of that precision.
“Brainomix e-Lung enables accurate quantification of physiologically meaningful features of disease progression,” he said. “This allows researchers to detect treatment effects far earlier than previously possible—even when patients still appear clinically well.”
For trial designers, earlier detection can mean shorter studies, clearer signals, and more efficient development pathways.
Delivered With Voiant’s Imaging Infrastructure
The DROP-FPF study will be delivered in partnership with Voiant, an AI-based clinical trial imaging solutions provider. Voiant will supply centralized image management and analytics, while Brainomix contributes its advanced imaging biomarkers.
Together, the platforms aim to deliver high-precision respiratory endpoints with greater speed and reliability, according to Jessica Ataharul, Voiant’s Vice President of Clinical Operations.
The collaboration reflects another industry trend: AI tools are increasingly being deployed in combination, rather than as isolated point solutions, to modernize trial execution end to end.
Broader Implications for Clinical Trials
Beyond pulmonary fibrosis, the implications are broader. Regulators, sponsors, and CROs have long sought more objective and sensitive endpoints—especially in diseases where progression is slow, heterogeneous, or difficult to measure.
AI-powered imaging biomarkers offer a potential answer, but only if they can demonstrate reliability, clinical relevance, and scalability. By elevating Brainomix’s technology to a co-primary endpoint in a Phase 3 study, DROP-FPF represents a meaningful step toward that future.
If successful, it could encourage wider adoption of AI-derived endpoints across oncology, neurology, cardiology, and other imaging-intensive fields.
For Brainomix, the selection reinforces its position not just as an imaging AI vendor, but as a strategic enabler of next-generation clinical trials.
And for patients at high risk of pulmonary fibrosis, it opens the door—finally—to answering whether acting earlier can change the course of a devastating disease.
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