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In Silico Oncology and In Silico Medicine Group, ICCS, SECE, NTUA is a partner of the recently EC funded project entitled: “PersoRad: Implementation of mobile health tools and artificial intelligence for personalised radiation treatment planning and monitoring in prostate cancer”. Reference Number: ERAPERMED2019-299

AcronymPersoRad (Reference Number: ERAPERMED2019-299)

Duration 01/04/2020 - 31/03/2023

Project Topic Prostate cancer (PCa) is the most frequent diagnosed malignancy in male patients and radiation therapy (RT) is a main treatment option. However, RT concepts for PCa have an imminent need to be rectified in order to personalise the RT strategy by considering (i) the individual PCa biology and (ii) the individual disease process of each patient. The consortium concatenates a prospective, non-randomized phase II trial for personalised RT of PCa patients (HypoFocal) with novel tools for patient involvement, advanced “omic” and bioinformatical analyses. In detail: (i) data comprising clinical course and individual PCa radio resistance (measured by yH2AX foci in tissue specimen) will be interpolated by state of the art imaging techniques (PSMA PET/CT and mpMRI) as a radiomics approach and with genomic profiling of the respective tumor tissue samples to identify biomarkers predictive of radio resistance. Additionally, (ii) mobile health tools will be offered to eligible patients of the HypoFocal trial in addition to established health services research approaches, such as interviews and focus groups, in order to increase patient involvement and to obtain patient reported outcomes. Artificial neural network approaches will be employed to support the results which will be implemented in (radio)biological model systems in order to calculate the tumor control probability and normal tissue complication probability of each patient in the future. New online tools with controlled access will address data exchange between project partners ensuring the highest level of data protection. Hereby, the implementation of novel computational components enables (i) unbiased characterization of tumor biology for personalised treatment planning processes (ii) direct integration of patients’ preferences for a personalised follow-up process after RT and (iii) characterization of environmental and personal context factors that are the basis for these preferences.NetworkERA PerMedCall2nd Joint Transnational Call for Proposals (2019)

Project partners

EC Project Website:

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Jan 01, 2021

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