All four projects (RABIOPRED, ADDIA, COVIRNA, HELICAL) involve biomarker identification, validation, or diagnostic tool development.
FIRALIS
French biotech SME developing and validating diagnostic biomarker assays, specializing in RNA-based IVD kits and AI-driven disease prediction.
Their core work
Firalis is a French biotech SME specializing in diagnostic biomarker development and validation, based in Huningue near the Basel biotech cluster. They develop in-vitro diagnostic (IVD) assays and biomarker kits for disease prediction and patient stratification, with applications spanning rheumatoid arthritis, Alzheimer's disease, cardiovascular conditions, and COVID-19 prognosis. Their work bridges molecular biology (including long non-coding RNA) with AI-driven prediction models to translate research biomarkers into clinically usable diagnostic tools.
What they specialise in
COVIRNA focuses on long non-coding RNA as the basis for a COVID-19 prognostic test, suggesting deep molecular expertise.
COVIRNA combines AI with biomarkers for patient stratification and prediction modeling, indicating a move toward computational diagnostics.
RABIOPRED, ADDIA, and COVIRNA all center on validating biomarker assays for clinical use in specific disease contexts.
HELICAL project (MSCA-ITN) involved health record linkage, broadening their data capabilities beyond wet-lab diagnostics.
How they've shifted over time
In their early H2020 period (2015-2018), Firalis served as a third-party contributor providing biomarker assay expertise for specific diseases — rheumatoid arthritis (RABIOPRED) and Alzheimer's (ADDIA) — without leading or formally partnering. From 2019 onward, they stepped up to full participant roles, expanded into health data linkage (HELICAL), and took on their largest funded project (COVIRNA) combining RNA biomarkers with AI prediction models. This shift signals a company moving from specialized subcontractor to an active R&D partner with growing computational and data capabilities.
Firalis is evolving from a pure wet-lab biomarker company toward integrating AI and health data analytics into their diagnostic pipeline, making them increasingly relevant for digital health and precision medicine consortia.
How they like to work
Firalis has never coordinated an H2020 project, starting as a third-party contributor and graduating to participant status — a trajectory typical of growing SMEs building credibility in EU research. Despite their small size, they have connected with 40 unique partners across 17 countries, indicating they are sought after for their specialized biomarker expertise rather than building a closed network. They fit best as a technical SME partner bringing diagnostic development capabilities to larger health-focused consortia.
With 40 consortium partners across 17 countries, Firalis has a surprisingly broad European network for an SME of its size. Their base in Huningue (French-Swiss-German border triangle near Basel) positions them at the heart of Europe's pharmaceutical and biotech corridor.
What sets them apart
Firalis occupies a specific niche: translating research-stage biomarkers into validated IVD products, which is the exact gap where most diagnostic innovations fail. Their combination of wet-lab assay development, RNA biology expertise, and emerging AI capabilities makes them a rare SME that can bridge molecular discovery and clinical deployment. For consortium builders, they bring a ready pathway from biomarker candidate to commercial diagnostic kit — a concrete exploitation route that strengthens any health project proposal.
Highlights from their portfolio
- COVIRNALargest funded project (EUR 1.1M) combining long non-coding RNA biomarkers with AI for COVID-19 prognosis — shows rapid pivot capability to urgent health challenges.
- ADDIAAddressed Alzheimer's blood-based diagnostics, one of the most commercially significant unmet needs in neurology, positioning Firalis in a high-value market.
- HELICALMSCA training network on health data linkage — unusual for a diagnostics SME, signals strategic expansion into data-driven health research.