The predictive value of personalised models will depend on the successful integration of medical data (e.g histological analyses, genetic analyses of cancer biopsies, questionnaires on personal characteristics and lifestyle of the patient, medications and outcomes) into the model. These data are collected in different places and various time points but need to be gathered in a single dataset for each patient to allow integration of the data in a personalized model.
The Medical Platform will provide continuous input of users’ needs into the ICT R&D pipeline of ITFoM, evaluate solutions emerging from ITFoM for usability, and will prepare the implementation of the novel ICT solutions in healthcare and public health. The Medical Platform will address, in particular, the provision of data and materials required to establish the reference models as a common data basis for all ITFom platforms, will develop data management solutions for medical, life style and environmental data, define specific needs of user interfaces especially to display heterogeneous, very large and complex data sets of numerous and different origins – “a medical avatar”. In addition, the Medical Platform will develop tailored concepts to address data protection, privacy and ethical issues, and will perform research tasks to develop an evidence‑based strategy to achieve societal acceptance of innovative ICT solutions and paradigm shifts resulting from ITFoM.
Preparing the ethical and legal frameworks for societal acceptance
The aim of ITFoM is to contribute to a process of ‘revolutionizing our healthcare system’ by creating a paradigm shift in medicine and public health. Such fundamental changes mean that both the material conditions and the social norms that govern the conduct of a domain are altered in ways that will constitute profound challenges for existing ways of understanding and operating medical research and healthcare with extensive implications for researchers, scientists, medical personnel, patients, regulators and policymakers, pharmaceutical industry and society in general.
Data Protection and Privacy
The Medical Platform will address all data privacy issues of ITFoM from the patient and medical expert’s views and will match them with ethical and legal requirements. This will be performed at three levels. i) by assessment of user and societal requirements leading to the design of specification of ICT solutions as well as governance frameworks; ii) by testing of solutions developed in the context of use cases and preparing the implementation in health care and public health; iii) by establishing a monitoring board to advise and monitor of ITFoM for compliance with applicable data protection regulation.
Reference data set
The reliability of any computational modelling approach will critically rely on the quality of data used for modelling and the spectrum of biological aspects represented by the data set. Several international projects, such as the International Cancer Genome Consortium or the 1000 Genomes Project have produced large high quality data sets. However these data are restricted to certain organs or health/disease conditions and would not be suitable for integrated modelling of biological systems across different organs and disease conditions on an individual basis. The ITFoM reference data set will consist of unique biological samples representing most tissues/cell types of man as source of molecular data as generated by the Analytical Platform together with detailed related medical, lifestyle and environmental exposure data.
Medical Data Management
Computational modelling within ITFoM considers two major categories of data with different ethical, legal, and societal implications. Type 1 data are related to an individual and comprise a huge variety of medical data (including physiological, imaging, treatment and disease outcome data) as well as data on lifestyle and environmental exposure. Type 2 data (also related to the individual) are molecular data that are generated by analysis of human biological samples using a broad spectrum of ‑omics technologies (external data and data generated within ITFoM). Issues related to the management of type 1 data are addressed in the Medical Platform since these data are typically collected and stored in the health care systems and have to consider special data protection and privacy requirements. Furthermore standardisation of data quality including standardisation of biosample quality (as data source), phenotype description, multi‑language interoperability, and heterogeneous national ethical and legal frameworks for medical data are specific challenges to be addressed.
Bridge to the e‑Health community
Building on the conclusions of the EU Task Force on e‑Health (“Redesigning health in Europe for 2020”), it is the aim of ITFoM to ensure that data and models resulting from its work programme can be efficiently accessed, understood, appraised and applied within the healthcare systems by all actors including scientists, clinicians, patients and citizens, private sector, regulators and policymakers in the wide field of e‑Health Literacy. As more health information becomes available through e‑Health systems, this will help to improve the models, provide input into assessment tools such as health technology assessment enabling evidence‑based and timely policy making, and offer efficient community platforms including mobile health solutions (mHealth), social media, social networks and (digital) health thereby helping to introduce new ICT into the healthcare systems.
User needs and interfaces
Human computer interaction (HCI) challenges will be addressed for different user communities (scientists, doctors, patients, healthy individuals) including topics from information visualisation and augmented reality by developing for example “a medical avatar”. New interfaces are necessary to augment medical data and to integrate the outcome of ITFoM models with (personal) health records. Clinicians and patients will be involved to influence the design of the interfaces and ITFoM’s new visual. Application scenarios will include (medical) decision support systems, visual analytics, personal health records, search interfaces and awareness, with large potential for the associated industries. For instance, where interfaces are developed for mobile devices including medical sensors we will develop new HCI paradigms. Sensors can capture simple responses like pace and pulse up to very general data such as logging of the daily food intake, physical activity or specific measurements, e.g. data about insulin injections or concrete metabolites.
Epidemiology in clinical medicine and public health
The modelling of the ‘virtual patient’ will pose essential challenges to epidemiology clinical research, public health and comparative effectiveness: i) the integration of role of prognostic factors, health management and screening activities that would impact the predictive modelling of treatments developed within the virtual patient; ii) the evaluation of efficacy of diagnostic screening or treatments based on individualised medicine.
Our aim is to provide an epidemiological support for the validation of predictive modelling as compared to known prognostic factors. The identification of prognostic factors will be an important component as they will enable to validate whether the computational modelling and prediction of survival exceed what could be predicted through the classical prognostic markers.
ITFoM considers health and disease from the biological systems perspective, which describes the functioning of the human body depending on biological networks. This networking occurs at the molecular, cellular, tissue, whole body and population levels, whereas diseases can be considered as network malfunction. Most human diseases are thereby multifactorial by nature, i.e. co‑determined by multiple genetic and environmental factors. Because the networks of life are all connected, different diseases are often affected by the same sub‑networks, although to different extents. Detailed modelling of the integral network inside the human, as condensed in the form of an ICT model for each individual, should ultimately deliver a completely new level of understanding health and disease. To bring ITFoM to much earlier fruition whilst working towards the ultimate aim of a “virtual patient”, ITFoM will put in place a number of ‘use cases’ addressing specific sub‑requirements of the future “virtual patient”. The activities and results of the use cases will be integrated into human ICT models of ever increasing connectivity, resolution and quality.
ITFoM will focus in it’s ramp‑up phase on two use cases:
Diabetes and metabolic diseases
Relevant European activities in cooperation with ITFoM:
BBMRI: Biobanking and Biomolecular Resources Research Infrastructure
P²G: Public Population Project in Genomics
BioShare: Development of Harmonized Measures and Standardized Computing Infrastructures
Gen2Phen: Genotype to Phenotype Database
ECRIN: European Clinical Infrastructure Network
ELIXIR: European Life Sciences Infrastructure for Biological Information
PHGEN: Public Health Genomics European Network