For drug discovery researchers, the protein is the target. But understanding its exact chemical makeup, the subtle modifications that dictate function, remains a stubbornly expensive and indirect process. A Zurich-based deep tech team is betting that a silicon chip, a nanopore, and a machine learning model can change that calculus, turning protein analysis from a batch-processed inference into a direct, single-molecule readout.
UNOMR, a 2022 spinout from ETH Zürich’s Laboratory for Biosensors and Bioelectronics, is building a hardware and software platform to analyze proteins. Its core is a patented interface nanopore sensor fabricated using standard semiconductor processes. The system measures tiny changes in ionic current as individual protein molecules pass through, aiming to detect modifications like glycosylation with high resolution [ETH Zürich, April 2026]. The long-term vision is audacious: making proteins as readable as DNA sequences have become [ETH Zürich, April 2026]. For now, the wedge is giving biopharma and food science labs a more direct window into protein structures that current mass spectrometry methods can only estimate.
The hardware-first wedge into proteomics
Most proteomics today relies on mass spectrometry, a powerful but indirect technology. Proteins are digested into fragments, analyzed, and then computationally reassembled to infer the original structure and its modifications. It’s a bulk measurement, not a single-molecule observation. UNOMR’s approach is a departure. Its sensor is designed to analyze intact proteins one by one, requiring only small sample volumes and basic purification [Venture Kick, April 2025].
The technical bet rests on scalability. By building its sensor using silicon and standard lithography, the company argues it can follow a manufacturing path more akin to semiconductors than bespoke lab equipment [Innovationspark Ost, February 2024]. This is not just an AI software layer on top of commoditized hardware; it’s a integrated stack where the proprietary sensor generates the unique data that the proprietary AI models are trained to interpret.
A founding team built for the long haul
The company is led by three PhDs from the same ETH lab, a structure that suggests deep technical alignment but also a need to build commercial muscle externally. Dr. Til Schlotter, the CEO, handles application development, customer interaction, and fundraising. Dr. Julian Hengsteler, the CTO, leads the engineering of the sensor hardware, software, and microfluidics. Dr. Julia Wagner, a co-founder acting in an advisory COO capacity, brings a background in mathematics, venture capital, and operational strategy [ETH Zürich, April 2026].
Their early backing has come entirely from Swiss non-dilutive grant programs, a common path for deep tech in the region but one that precedes the scrutiny of institutional venture capital. The table below outlines their publicly disclosed funding to date.
| Date | Amount (CHF) | Program | Purpose / Note |
|---|---|---|---|
| 2023-2024 | 130,000 | BRIDGE | R&D grant awarded to Til Schlotter [BioIncubate]. |
| Nov 2024 | 40,000 | Venture Kick | For business model validation and prototype work [Venture Kick, November 2024]. |
| Apr 2025 | 150,000 | Venture Kick | For hiring, business development, and preparing on-site customer tests [StartupTicker, April 2025]. |
This funding runway is typical for validating a deep tech thesis but is a fraction of what will be required to scale hardware manufacturing and build a commercial sales operation. A subsequent, undisclosed financing round was noted by May 2026, though its size and lead investor were not made public [Venture Leaders, May 2026].
Traction and the path to a first customer
Commercial momentum is in its earliest phases. The company has identified Nestlé as a partner exploring the technology’s potential for analyzing protein glycosylation in food science [Gebert Rüf Stiftung]. More broadly, UNOMR is seeking early adopters across pharmaceutical, biotechnology, medical, and academic research markets to test and refine the platform [ETH Zürich, April 2026].
The stated plan, following the April 2025 grant, was to begin on-site customer testing within two years [StartupTicker, April 2025]. A mid-2026 LinkedIn post from an industry contact noted the company was "getting closer to putting its early access device into customers' hands for on-site testing" [David Sommer - BarrelWise Technologies | LinkedIn, 2026]. This suggests the critical transition from lab prototype to field-testable instrument is underway.
The formidable road to market
The ambition is vast, but the risks are layered and capital-intensive. Success depends on executing across multiple frontiers simultaneously where others have stumbled.
- Technical performance. The sensor must deliver consistent, high-resolution data in real-world lab conditions, not just in a controlled research setting. Protein analysis is notoriously noisy, and single-molecule detection adds another layer of complexity.
- Manufacturing scale. While the silicon path offers scalability in theory, moving from lab-scale fabrication to reliable, high-yield production is a classic deep tech valley of death. Support from the German Chips Competence Centre to find European fabrication pathways is a relevant, but early, step [German Chips Competence Centre, August 2026].
- Commercial displacement. The platform must convince labs to adopt a novel, hardware-based workflow alongside or in place of entrenched mass spectrometry systems. The value proposition hinges on delivering insights that are impossible or prohibitively expensive with current tools, not just incrementally better.
- The funding ladder. The ~$320,000 (estimated) in disclosed grants is seed capital for R&D. The next round will need to be orders of magnitude larger to fund instrument production, commercial hires, and sustained application development. Attracting that capital requires demonstrable technical milestones and, ideally, paid pilot agreements.
The next twelve months
The coming year is a make-or-break validation window for UNOMR. The key milestones are not about vague platform development but specific, customer-facing outcomes. Securing the first paid evaluation agreements with biopharma or diagnostics clients would be a powerful signal. So would publishing peer-reviewed data demonstrating the sensor’s performance against gold-standard methods for a specific application, like characterizing therapeutic antibody glycosylation.
Internally, growing the team beyond its founding PhD core is already a priority, as indicated by a posting for a "curious, hands-on intern" in mid-2026 [LinkedIn, May 2026]. Strategic hires with experience in instrument sales or biopharma applications will be necessary to bridge the gap from lab to customer site.
The ideal customer profile here is clear: a translational research group or biotech process development team focused on protein-based therapeutics, where understanding glycosylation patterns is critical for drug efficacy and safety. They have a budget for advanced analytical equipment but are frustrated by the limitations and indirect nature of current tools.
The realistic competitive set isn’t a direct sensor clone,none are named in the public record,but the entrenched alternative. It’s the multi-million dollar mass spectrometer from Agilent or Thermo Fisher, and the service labs that operate them. UNOMR isn’t trying to replace that entire ecosystem overnight. Its near-term goal is to carve out a high-value niche where single-molecule, modification-specific analysis commands a premium, proving its hardware wedge before expanding its scope.
Sources
- [ETH Zürich, April 2026] We are addressing a ‘blind spot’ in biology and medicine: how UNOMR makes proteins readable | https://ee.ethz.ch/news-and-events/d-itet-news-channel/2026/04/we-are-addressing-a-blind-spot-in-biology-and-medicine-how-unomr-makes-proteins-readable.html
- [StartupTicker, April 2025] UNOMR obtains CHF 150,000 to bring a new dimension to proteomics analysis | https://www.startupticker.ch/index.php/en/news/unomr-obtains-chf-150-000-to-bring-a-new-dimension-to-proteomics-analysis
- [Venture Kick, November 2024] AI to improve the healthcare system | https://www.venturekick.ch/CHF-40000-for-AI-to-improve-the-healthcare-system-streamlined-literature-review-a-platform-to-coordinate-space-traffic-and-singleprotein-sensors
- [Innovationspark Ost, February 2024] 2023: We present our funded startups | https://innovationspark-ost.ch/en/2023-we-present-our-funded-startups-2/
- [BioIncubate] UNOMR | Startup Team | https://www.bioincubate.ch/unomr
- [Gebert Rüf Stiftung] UNOMR - Revolutionizing Proteomics with Nanopores | https://www.grstiftung.ch/en/funding/portfolio~grs-095-24~.html
- [Venture Leaders, May 2026] UNOMR: The Venture Leader Biotech enabling single-molecule protein analysis | https://www.venture-leaders.ch/UNOMR-The-Venture-Leader-Biotech-enabling-singlemolecule-protein-analysis
- [German Chips Competence Centre, August 2026] G3C supports UNOMR in identifying suitable European fabrication pathways | Source integrated from research snippets.
- [David Sommer - BarrelWise Technologies | LinkedIn, 2026] LinkedIn post noting progress toward customer testing | Source integrated from research snippets.
- [LinkedIn, May 2026] UNOMR career posting for an intern | https://www.linkedin.com/company/unomr