The specific detection of viruses plays an important role in various areas of pharmaceutical research, including the development of virus-based gene therapies and vaccines. Adeno-associated viruses (AAV) are frequently used as gene therapy vectors or as carrier viruses for new vaccines. AAVs are now the most attractive vector for gene therapy treatment of various diseases with several approved therapies. With the increasing importance of AAV in gene therapy, the need for reliable measurement methods to determine the titer and the ratio of empty to full capsids is also increasing. Established methods such as ELISA and qPCR have a number of disadvantages, such as time-consuming sample preparation or washing steps, which considerably increase the time required to detect the viruses. The aim of this project is to develop a new analytical method that enables the quantitative detection of AAV and the differentiation of empty and full capsids in complex samples within a few minutes. The method is based on marker-free electrical biosensors with a specially developed multifunctional coating on the surface. This enables sensitive and selective measurement of virus binding to the capsid-specific capture antibody. In addition, the readout electronics including algorithms for data evaluation are being developed. The biosensor signals are used to train and validate a machine learning algorithm (ML). This is expected to significantly optimise the performance of the biosensor system.  The method can open up new analysis parameters, offers a high temporal resolution and a compact readout unit without optical components. The successful development of detection methods for AAV is an important step towards fast, reliable and cost-effective in-process controls in the production of new gene therapies and vaccines.