Matthias holds a Masters degree in Computer Science with a major in software engineering and a minor in Bioinformatics from Berlin University (Freie Universität). While working at Charité University Hospital in Berlin, he developed a database for kidney transplantation data and worked on various laboratory information systems and research databases. His research at Charité focused on epitope matching models and machine learning. He was instrumental in the implementation methods to increase data quality. Since fall 2014 he focuses at PIRCHE on further improving the PIRCHE algorithm and investigating the technology's power in new domains.

Nils Lachmann’s Poster about PIRCHE® at DTG 2016 Receives Poster Award

At the 25th DTG (Deutsche Transplantationsgesellschaft) annual meeting in Essen, Germany, the poster titled “De novo donor-specific HLA antibodies after kidney transplantation are correlated with the number of predicted indirectly recognizable epitopes” was awarded with a poster prize. Nils Lachmann and his team of co-authors proved previous findings of Eric Spierings’ working group, that increased numbers of PIRCHE correlate with the development […]

The PIRCHE® technology: Predicting HLA epitopes being indirectly recognized improves donor selection in various transplantation settings

University Medical Center (UMC) Utrecht has developed a new method to select permissible mismatches. This technology applies to hematopoietic stem cell transplantation, solid organ transplantation, and other domains improving graft acceptance and therapy effectiveness. The new technology named PIRCHE® forecasts T-cell related immune responses against HLA derived peptides after transplantation(3). In contrast to existing technologies, […]