Knowledge commons in precision medicine built on Responsible Research and Innovation
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In the subproject ‘Crossover Research 2.0 – Well constructed Knowledge Commons’ (www.ntnu.edu/crossover-research) the domain of precision medicine is explored as a key visionary driver for developing the Knowledge Commons and the enabling of Systems Biology approaches to innovate health care. In particular, we seek to engage stakeholder concerns in investigating and establishing strategies for DrugLogics to contribute to the Knowledge Commons in an RRI mode.
The subproject ‘Rational development of anti-cancer combinations’ focuses on precision medicine for cancer by pursuing novel insight into cancer disease mechanisms, combinatorial drug treatment in order to enable selection of the best treatment for the individual patient. The aim is to develop and integrate computational, experimental and analytical approaches to predict and validate anti-cancer drug combinations and produce an integrated pipeline for rational screening of synergistic drugs and for clinical decision support in precision medicine.
In the subproject ‘Using computer models to predict drug resistance in colon cancer’ (www.colosys.org) we will develop a deeper understanding of colon cancer networks and convert them into computer models with which we will be better capable to predict response to treatment. The combination of computational, experimental and clinical testing will be explored to understand drug resistance mechanisms, further paving the way towards personalised treatment of colon cancer.
These three different subprojects require a multidisciplinary skill base, and we build on collaboration that has been ongoing for over 10 years during which we developed skills and personal relationships that significantly capacitate us in pursuing this kind of research.
In the DrugLogics initiative we will use recent discoveries made in our research at NTNU, integrate different technologies and analyse them as a practical test for treatment of patients with very specific types of cancer.
The work draws from three projects, each with its own website:
Crossover Research 2: Well constructed Knowledge Commons
COLOSYS: Using computer models to predict drug resistance in colon cancer
DrugLogics: Rational development of anti-cancer combinations