Overall strategy & general description

In connection with the scientific/technical dimensions of the work p-medicine will develop a data warehouse and a workbench with a tools repository. Heterogeneous pseudonymized/anonymized data from different origins will be stored in a data warehouse for further use by the scientific community. Clinical data will be exploited coming from hospital information systems and clinical trials. The legal framework of the project, which is based on the results of ACGT (Advancing Clinico-genomic trials), will be further developed and will guarantee data privacy and security. Most important for p-medicine are validated tools and services that provide interfaces to allow interoperability with biobanks, genetic databases, and medical imaging systems and data warehouses. These tools have to meet requirements to be used in large, international multicentre clinical GCP conform trials and need to be able to be integrated into existing systems used by ECRIN (European Clinical Research Infrastructures Network) and other communities. This includes aspects like data security by adopting the legal and ethical framework based on international requirements and approved concepts for anonymization and pseudonymization including validation. Previous R&D work done in European funded projects like ACGT, ContraCancrum and ECRIN (fits perfectly into this approach and will be heavily drawn on.

All scheduled activities are structured in a way to produce a coherent and integrated work plan. p-medicine consists of different innovative and interrelated components that will be integrated to form the p-medicine environment. The R&D work will be continuously influenced by the interaction between the research and verification components of the project. P-medicine will actively seek to re-adjust its research activities and objectives based on evidence as a result of a quality assurance process within the work plan. It is the final goal of this project to develop the p-medicine environment to a self-sustaining legal body that will further develop the vision of this project fostering personalized medicine.  

p-medicine will collaboratively develop advanced re-usable clinical trial driven multiscale cancer models. As p-medicine will explicitly integrate an impressively larger number of biocomplexity levels, spanning from the quantum chemical level up to the physiological system level, will study different cancer types and will also address pathogenesis it might be viewed as the precursor of the “second generation” of Oncosimulators. On top of that, the direct and orchestrated involvement of Cancer Hospitals throughout Europe will provide a large number of cases per year for the optimization and validation of the p-medicine Oncosimulator, which is expected to bring in silico oncology a big step further. Such an anticipated outcome would be another European first. As p-medicine is driven by clinicians, validated by clinical relevant use cases and focusing its research and development on several pressing needs in healthcare their successful resolution will have significant and far-reaching implications.

Personalized medicine

A user will be able to get access to p-medicine via a secure portal to use tools and workflows from the p-medicine workbench to execute his models by mining data from the data warehouse. The data warehouse is feed by data from Hospital Information Systems (HIS) or the integrated Clinical Trial Management Systems (CTMS) via a push service. The CTMS can synchronize with the HIS using a sync service. Data entering the p-medicine environment will be pseudonymized/ anonymized and semantically annotated. Access to external biobanks will be established and freely available data from the web can be stored in the data warehouse. Depending on the scenario users are able to execute models with the p-medicine Oncosimulator or they can use the Decision Support System (DSS). In both cases results will lead to personalized medicine via decision support. Patients as users of p-medicine can interact with the p-medicine environment via the Interactive Empowerment Service (IEmS) that will be developed in the project’s lifetime.

Patient empowerment

Patients are typically seen as the recipients of care. An important ideal of personalized medicine is to better enable patients themselves to be participants and guides in their own health care. The role of patients will be strengthened in p-medicine by allowing them to decide at any time what kind of research is allowed to be done with their data and their own biomaterial. Patient empowerment is based on information coming from research. Only by using this information to educate patients shared decision support is possible. This will enhance transparency for patients in the healthcare system and will convince patients to use their data for research purposes as shown in the figure below.

Use cases for patient empowerment that will be supported and tested within p-medicine are the following:

  • Allowance to decide about the usage of their own data and biomaterial
  • Under certain circumstances update of their own data
  • Usage of data mining and knowledge discovery tools that are able to summarize the history of their specific disease with all relevant information in a language understandable by them

These three use cases will increase the compliance of patients to their treatment and will improve the quantity and the quality of data for research purposes. Transparency in data handling, augmentation of the patient’s knowledge about his/her disease and participation as  an active partner in a shared  decision    
process in the management of his/her disease increases trust in the Health Care System including data handling and demands for more research by patients allowing the use of his/her individual data to solve his/her personal medical problem thus fostering also VPH models.

Figure: Circuit of patient empowerment

The circuit of patient empowerment from research to decision support and back to research. The green arrow indicates the necessity of tools for patients to provide feedback to enhance clinical research. Adapted from: “The Patients and Consumers Perspective”; eHealth Conference, Barcelona, 15th March 2010.