Bioprocess Engineer Lars Pelz honored with ACTIP Fellowship Award 2023

Producing highly efficacious and safe antiviral agents with a high-yield manufacturing process.

October 20, 2023

Lars Pelz, scientist in the Bioprocess Engineering group at the Max Planck Institute Magdeburg, has been awarded as one of the seven winners with the ACTIP Fellowship Award 2023 (The Advanced Cell Technology Industrial Platform). His application with his Ph.D. project on In-depth characterization and cell culture-based production of influenza A virus defective interfering particles “received an excellent score from the evaluators, based on its novelty, scientific impact, and relevance for the industrial use of advanced cell technologies”, said the ACTIP Executive Secretary.

The SARS-CoV-2 pandemic has highlighted the need to rapidly develop innovative process options for manufacturing of vaccines and novel therapeutic antivirals against pandemic diseases. In this project, it could be shown that viruses can be used not only for manufacturing of vaccines and viral vectors in gene therapy, but also for production of highly efficacious and safe antiviral agents. These antivirals are special viruses, namely defective interfering virus particles (DIPs) that occur naturally in each virus infection. Due to their properties, DIPs of influenza A virus (IAV) are able to interfere with the replication of IAV, SARS-CoV-2, respiratory syncytial virus, yellow fever virus and Zika virus infections and by that could act as antiviral. In his Ph.D. project, Lars Pelz together with many partners has focused on the establishment of a scalable high-yield manufacturing process of these DIPs with animal cell culture.

About Lars Pelz

Lars Pelz obtained his Master’s degree in Bioprocess Engineering from the Technical University of Munich in 2019. His Master´s thesis was on the production of yellow fever virus in BHK-21 cells at the Max Planck Institute for Dynamics of Complex Technical Systems in Magdeburg in the research group Bioprocess Engineering. In this group, he is now also pursuing his Ph.D.. His main interest lies in process intensification for virus production to increase virus yields and to develop more sustainable processes for biopharmaceuticals. During a visit as guest researcher at the McGill University in Montreal, Canada, in the lab of Prof. Amine Kamen, he again used process intensification, but now with another virus-host cell system.

About ACTIP - The Advanced Cell Technology Industrial Platform

ACTIP is an independent non-profit association of European companies and institutions engaged in the industrial use of advanced cell technology for research, development and/or production of biopharmaceuticals, vaccines and other preventative or therapeutic approaches. Its main objectives are to bring advanced cell technology experts together for networking, keeping up to date on cutting-edge developments and focus on technological and applied-oriented challenges for the industrial use of advanced cell technology.

Lars Pelz presented his award-winning research project at the ACTIP meeting in Dublin, Ireland, on 17th October 2023.

The ACTIP fellowship award includes a fully paid invitation to attend and present the research project at one the ACTIP meetings and a 1.000 Euro prize.

Original Publications

Pelz, L.; Piagnani, E.; Marsall, P.; Wynserski, N.; Hein, M. D.; Marichal-Gallardo, P.; Kupke, S. Y.; Reichl, U.: Broad-Spectrum Antiviral Activity of Influenza A Defective Interfering Particles against Respiratory Syncytial, Yellow Fever, and Zika Virus Replication In Vitro. Viruses 15 (9), 1872 (2023)
Pelz, L.; Rüdiger, D.; Alnaji, F. G.; Genzel, Y.; Brooke, C. B.; Kupke, S. Y.; Reichl, U.: Semi-continuous propagation of influenza A virus and its defective interfering particles: analyzing the dynamic competition to select candidates for antiviral therapy. (2021)
Rüdiger, D.; Pelz, L.; Hein, M. D.; Kupke, S. Y.; Reichl, U.: Multiscale model of defective interfering particle replication for influenza A virus infection in animal cell culture. PLoS Computational Biology 17, e1009357 (2021)
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