15.01.2026 / Start-up company Absea Biotechnology GmbH is developing new proteomics technologies. An interview with Dr. Philip Lössl, Senior VP Science and Business Development

What makes the Absea Biotechnology Group special?

Absea Biotechnology develops protein science technologies to advance proteomics. One of our main areas of focus is developing monoclonal antibodies for the entire human proteome. These antibodies can detect highly specific molecular biomarkers or diseased cells, such as those associated with cancer or autoimmune diseases. In collaboration with our sister companies in China and the U.S., we have amassed the world’s largest library of recombinant human proteins, which we are continually expanding through our high-throughput protein production platform. Alongside this, we are establishing mass spectrometry pipelines in Berlin to better understand protein–drug interactions (PDIs).

We see ourselves as partners and service providers in proteomics, in vitro diagnostics, and pharmaceutical and life sciences research.

How did the Absea Biotechnology Group come about?

Immunology professor Wei Zhang laid the groundwork. While earning her Ph.D. at Cambridge, she collaborated with Nobel Prize winners César Milstein and Gregory Winter, who studied the fundamentals of monoclonal antibodies. After founding her first antibody company, Zhang worked closely with the Human Protein Atlas project. Absea later developed an even larger partnership with Olink, a Swedish company that is now part of ThermoFisher. Since then, Absea has developed thousands of protein antigens and monoclonal antibodies for Olink. In 2020, the Absea Group was reorganized around bioinformatician Tao Chen to better support this proteome-wide approach. In 2023, we established our Berlin-based start-up, focusing on mass spectrometry research and development.

What is the secret behind Absea’s extensive protein library?

Tao Chen developed a machine learning-based algorithm for designing protein constructs. These constructs correspond to natural sequences found in our bodies, though they are sometimes slightly shorter. Thanks to the algorithm, we know exactly how to shorten the proteins in order to produce them efficiently and cost-effectively with a high success rate.

What innovations are you pursuing?

Our antibody and protein libraries map the proteome and support affinity-based methods. This treasure trove of molecules can also help us develop more unique mass spectrometry technologies and complement “making molecules” with “mapping molecules.” Our scientific advisors, Mikhail Savitski from the European Molecular Biology Laboratory (EMBL) in Heidelberg and Fan Liu from the Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP), both leading experts in mass spectrometry proteomics, encouraged us in this endeavor. Together with Matthias Mann– Germany’s most cited researcher, one of the founding fathers of proteomics, and a researcher at the Max Planck Institute of Biochemistry (MPIB) in Martinsried – we published an approach to using our proteins for clinical testing mass spectrometry.

What does this approach entail?

Proteomics typically only allows for the relative quantification of protein biomarkers: a physician could tell you that you have more of a certain protein in your blood than last time, but they could not tell you the exact amount. Therefore, absolute quantification of biomarkers is important for clinical diagnostics. Until now, peptides labeled with heavy isotopes have been used for this purpose. However, this method only allows the part of the protein biomarker covered by the peptide to be seen and quantified. For this reason, we started producing whole proteins labeled with isotopes. Until now, this was not possible on a large scale. Thanks to our many years of experience in protein production, however, we have figured out how to do this.

When these labeled proteins are added to the sample, they are much more similar to the biomarker because both are proteins. Unlike peptides, proteins can be included in sample preparation. This enables researchers to monitor where deviations occur. During sample preparation, the biomarker and the labeled protein are broken down into peptides. The isotope-labeled counterpart is also found in the peptides. This provides a large number of data points for quantifying the biomarker. If the correlation with the labeled counterpart is incorrect, further mass spectrometry measurements can determine what happened in this region.

This allows parallel and highly sensitive testing of entire protein panels for a specific disease to detect abnormal quantities. At this level, the results could be relevant to clinical practice.

A path to clinical application would therefore be possible.

That is our hope. The plasma proteomics community is proposing the same approach. We are already working with a European university hospital, but we are still in the research and development phase.

However, we have even more plans: we are developing a methodology platform to better map protein–protein and protein–drug interactions at the molecular level. Our goal is to analyze these interactions directly in intact cells, tissue lysates, and cell lysates to gain a better understanding of diseases and the effects of drugs. Ultimately, we want to help our partners develop more effective drugs.

How would you go about doing that?

The first step is to determine if a drug binds to the intended protein and if there are any other unexpected – or even undesirable – binding partners. We use mass spectrometry technology to accomplish this. This technology can show us which protein areas are blocked by a drug across the entire proteome. We also discover the precise location where the drug binds. This information tells us, for example, whether the drug can inactivate the protein or prevent it from interacting with other proteins.

The second step involves protein-protein interactions (PPIs). Which PPIs occur in treated or untreated cells? Which ones occur in healthy or diseased cells? Crosslinking mass spectrometry provides an overview of the entire cellular network. Using our antibody libraries, we can then go into greater depth: we can use crosslinking to fix all protein–protein contacts in the cell. Then, the protein of interest can be enriched using one of our numerous antibodies and extracted from the cell with all its interaction partners for analysis.

Which customers are you targeting with this approach?

For pharmaceutical customers, we can identify disease-relevant protein targets for drugs in the early stages of development. By showing exactly how drugs work, we can determine which candidates are worth further development.

Another customer group consists of protein biotechnology companies that specialize in AI. Our comprehensive, high-quality datasets contain thousands of PPIs and PDIs, providing these companies with valuable information for developing their AI models.

Starting in January, your start-up will be located in the BerlinBioCube incubator

We look forward to being in the same building as the other start-ups, exchanging ideas and supporting each other. I believe this is an ideal ecosystem for us to grow in. We already have academic collaborations on campus with the FMP and the Max Delbrück Center. We also have strong relationships with biotech companies. We see a lot of potential for joint projects at this location.

The interview first appeared in Standortjournal buchinside 1/2026.