Bastian Nießing ^1* Yannik Breitkreuz ^2,3 Andreas Elanzew ^3* Marcelo S. De Toledo ^4,5,6,7 Peter Vajs ¹ Marina Nolden ¹ Frederik Erkens ¹ Paul Wanek ^4,5 Si Wah C. Au Yeung ^3* Simone Haupt ² Niels König ¹ Michael Peitz ^2,3,8* Robert Schmitt ^1,9 Martin Zenke ^4,5,6,7 Oliver Brüstle ^2,3*

• ¹ Fraunhofer Institute for Production Technology (FHG), Aachen, Germany
• ² LIFE & BRAIN GmbH, Bonn, North Rhine-Westphalia, Germany
• ³ Institute of Reconstructive Neurobiology, University of Bonn, Bonn, North Rhine-Westphalia, Germany
• ⁴ Institute for Biomedical Engineering, Faculty of Medicine, RWTH Aachen University, Aachen, Germany
• ⁵ Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, North Rhine-Westphalia, Germany
• ⁶ Department of Hematology, Oncology, Hemostaseology and Stem Cell Transplantation, University Hospital RWTH Aachen, Aachen, Germany
• ⁷ Center for Integrated Oncology Aachen Bonn Cologne Düsseldorf (CIO ABCD), Aachen, Germany
• ⁸ Faculty of Medicine, University of Bonn, Bonn, Germany
• ⁹ Laboratory for Machine Tools and Production Engineering, RWTH Aachen University, Aachen, Germany

CRISPR-Cas9 genome editing is a rapidly advancing technology that has the potential to accelerate research and development in a variety of fields. However, manual genome editing processes suffer from limitations in scalability, efficiency, and standardization. The implementation of automated systems for genome editing addresses these challenges, allowing researchers to cover the increasing need and perform large-scale studies for disease modeling, drug development, and personalized medicine. In this study, we developed an automated CRISPR/Cas9-based genome editing process on the StemCellFactory platform. We implemented a 4D-Nucleofector with a 96-well shuttle device into the StemCellFactory, optimized several parameters for single cell culturing and established an automated workflow for CRISPR/Cas9-based genome editing. When validated with a variety of genetic backgrounds and target genes, the automated workflow showed genome editing efficiencies similar to manual methods, with indel rates of up to 98%. Monoclonal colony growth was achieved and monitored using the StemCellFactory-integrated CellCelector, which allowed the exclusion of colonies derived from multiple cells or growing too close to neighbouring colonies. In summary, we demonstrate the successful establishment of an automated CRISPR/Cas9-based genome editing process on the StemCellFactory platform. The development of such a standardized and scalable automated CRISPR-Cas9 system represents an exciting new tool in genome editing, enhancing our ability to address a wide range of scientific questions in disease modeling, drug development and personalized medicine.