In the search for cancer cures, the most promising targets are often short protein fragments, or peptides, presented on the surface of cells. These fragments are flags waved by the immune system, signaling whether a cell is healthy or diseased. For developers of T-cell therapies and cancer vaccines, identifying which flags are unique to tumors and safe to target is a data-starved challenge. Alithea Bio, a German biotech founded in 2019, is building the map.
The company's core asset is a proprietary database of HLA-presented peptides, compiled from thousands of patient samples. The goal is to give pharmaceutical researchers a quantitative picture of the immune landscape, moving beyond theoretical predictions to observed biology. This data-centric approach forms the foundation of its two main software tools: HLA-Compass for peptide characterization and NeoZOOM for predicting off-target toxicities [Alithea Bio website].
The immunopeptidomics wedge
Alithea's entry point is target validation. When designing a therapy that instructs the immune system to attack cancer, targeting a peptide also found on healthy tissue can lead to severe side effects. The company's platform aims to de-risk this process by applying mass spectrometry and bioinformatics to directly measure and catalog the peptides cells present, rather than relying solely on algorithmic predictions.
Its database, drawn from an estimated 3,000 samples, covers 1.1 million ligands and their abundance across conditions [PMWC]. By quantifying what is actually presented on cells, Alithea provides a reality check for drug candidates, helping researchers prioritize neoantigens with high tumor specificity.
A team built for translation
The company's leadership reflects a blend of scientific depth and commercial focus. Chief Scientific Officer and co-founder Tim Fugmann brings technical expertise in HLA peptidomics and an education from ETH Zürich [LinkedIn, Bruker webinar]. CEO Fanny Giannou oversees business strategy and external partnerships [Crunchbase, Startup Greece podcast].
The company has engaged with early-stage public funding and recognition programs, including the BadenCampus accelerator, the German ZIM grant program, and the Women TechEU award in 2024 [LinkedIn].
| Role | Name | Key Background |
|---|---|---|
| CEO & Co-Founder | Fanny Giannou | Master's in International Economics; Women TechEU awardee |
| Chief Scientific Officer & Co-Founder | Tim Fugmann | Experienced in HLA peptidomics; educated at ETH Zürich |
Navigating an unproven commercial path
Alithea Bio's public track record is still forming. The company states it has completed its first commercial contracts, but has not named any pharmaceutical or biotech partners [Alithea Bio]. In a field where credibility is built on published case studies, this opacity is a hurdle. Furthermore, the core technology requires continuous investment to expand the peptide database and refine its AI models.
The competitive landscape is implicitly crowded. Large CROs offer mass spectrometry services, and several bioinformatics firms provide in silico prediction tools. Alithea's bet is that integrating wet-lab data generation with specialized software creates a defensible niche.
- The data moat. The value of the 1.1 million-peptide database compounds with each new sample [PMWC].
- The regulatory tailwind. Increased scrutiny of immunotherapy safety profiles creates a market for tools that rigorously quantify off-target risk.
- The adoption challenge. As a new entrant, Alithea must displace incumbent workflows and prove its platform meaningfully accelerates R&D timelines.
For patients with advanced solid tumors, the process of discovering a tumor-specific antigen remains slow. Alithea Bio's long-term vision is to compress that discovery timeline, providing developers with the tools to design therapies that are both potent and precise. The company's next twelve months will likely be defined by its ability to convert its first contracts into published validation studies and to secure the growth capital needed to scale its data-generation engine.