Development of nanotechnology tools for real-time health care diagnostics

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We aim to develop nanotechnology tools for real-time health care diagnostics to improve diagnostics of osteoarthritis and cancer. Based on the indentation type atomic force microscopy (IT-AFM) technology that my team and I developed over the last 20 years, we are now taking the next steps by targeting different health applications with connection to digitization and the Internet of Things (IoT). A first application of the IT-AFM technology is the development of osteoarthritis (OA) drugs to drastically reduce the need of knee and hip joint implants. There are no OA drugs, because there are no sensitive tools to detect the structure-modifying effects of substances in articular cartilage in animal testing and in patients. A drug that could delay the time to surgery by only one year would be a huge market. As a second application the IT-AFM technology may be employed to quickly decide if a tumor is malignant or benign. In such scenario, a tumor biopsy is taken in the operation theatre and placed into the desktop analysis tool. Digital data is exchanged real-time with a reference laboratory that can quickly evaluate if a biopsy is malignant or benign. The IT-AFM technology may improve cancer diagnostics and prognosis and contribute to the development of personalized therapies. Such progress in medicine would save money and time and provide the surgeon with information for instant informed clinical decision making. The IT-AFM technology is scalable and can be expanded to a variety of biomedical and technical applications including the development of custom-made commercial products for specialized applications. We have developed the IT-AFM technology and published it in three landmark papers including an article in Nature Nanotechnology. We are currently evaluating different possible collaborations with our local partners and partners worldwide to find the best match for this work. Depending on the collaboration and in agreement with our partners and the students abilities, we will then how the Ph.D. student best fit our team.