Record #735258 - RWTH Publications

ElectroPros

Training research pioneers by utilizing and validating the promise of electroporation for minimal invasive oncological treatments.

Coordinator	PHILIPS ELECTRONICS NEDERLAND BV ; Universitätsklinikum Aachen
Grant period	2019-01-01 - 2022-12-31
Funding body	European Union
Call number	H2020-MSCA-ITN-2018
Grant number	813192
Identifier	G:(EU-Grant)813192

Note: The ElectroPros action aims to optimally prepare young researchers for the evolving technology in the healthcare space, especially related to minimal invasive oncology therapies, by offering a unique set of targeted interdisciplinary training and research assignments in the areas of biophysics modelling and simulation, device physics, optimization algorithms, software integration and experimental validation. Four European Industrial Doctorate positions are offered to Early Stage Researchers (ESRs) for a period of three years. In the training program a combination of industrial, academic and clinical research environments are provided by Philips, the University Clinic Aachen and RWTH Aachen, to explore the field of electroporation, as a new and promising technique for minimal invasive oncology treatment. Based on sound career development plans, and coached by experienced supervisors, the four ESRs involved will develop a competence profile which will springboard their future career in the wide European medical community in the industrial, clinical and academic domain. These researchers have the potential to become pioneers for new minimally-invasive therapies for the oncology domain. During their training, the ESRs will work on electroporation based treatment of cancer. The ESRs address shortcomings of the currently available equipment to enable for the first time ever a reliable patient-specific electroporation based treatment for cancer. With a focus on liver cancer, the ESRs will collectively establish novel insights on the biophysical effects on various tissues, important to understand the treatment effect, and integrate this knowledge in optimal device (needle) design and multi-physics models for treatment outcome prediction and inverse planning algorithms. Furthermore, the developed assets will be integrated in clinical prototype software to support and optimize the clinical workflow.