OraMod starts from the need of clinician to predict the progression of diseases based on large sets of data collected during the usual clinical workflow. While research relies on “black-box” models relying only on objective data, clinical practice is founded on the decision of clinicians, based on their expertise and on the interpretation of patients’ individual data and health conditions.
Our vision is to build-up from both research and clinicians’ experience and produce a breakthrough in personalized clinical practice, and give to clinicians the possibility to model and predict risk of disease reoccurrence. Therefore OraMod predictive modeling environment will be:
– Built on current knowledge as an INCREMENTAL tool
– «Transparent» in terms factors and their relative weight
– Includes «sensitivity» testing by the operator
In so doing OraMod contributes to translate research into the ward and paves the way to large scale clinical trials and adoption into routine clinical practice and to bring in silico oncology from research to the clinic.
To this aim OraMod will develop a data warehouse comprising heterogeneous pseudonymized/anonymized data from different origins, combined with data from hospital information systems and clinical trials.
Tools and services to allow interoperability with hospital information systems, diagnostic imaging systems and datasets and bio-banks will be developed conforming to international standards and to the requirements for future use in clinical research networks.