Data-rich, individualised medicine poses unprecedented challenges for IT, in hardware, storage and communication. ITFoM proposes a data-driven, individualised medicine of the future, based on the molecular/physiological/anatomical data from individual patients. ITFoM shall make general models of human pathways, tissues, diseases and ultimately of the human as a whole. Patient individualised versions of the models will then be used to identify personalised prevention/therapy schedules and side effects of drugs. This is the first time that huge IT implications of worldwide individualized patient care will be addressed in combination with genomics and medical requirements. The project outcomes will enable calculation of health, disease, therapy and its effects for individual patients. These may revolutionize our health care with enormous (i) benefits for health (prevention, diagnosis and therapy), (ii) reduction in cost by individualising combinations of a limited number of drugs, and (iii) new commercial opportunities in IT, analytics and health care. This entails nothing less than the transformation of biomedical science from empirical and stochastic to fact based and knowledge driven i.e. based on an ICT paradigm.
Prof. Hans Lehrach
Max Planck Institute for Molecular Genetics, DE
The ultimate goals of ITFoM are twofold. The first goal is to give each patient’s doctor the power to analyse a person‘s human genome at every stage of disease management – through diagnosis, treatment and follow-up. This will require a revolution in ICT technologies so that relevant computing, storage, networking and modeling technologies are developed. The second goal is to enable the connection of high throughput biomolecular characterization and clinical imaging technologies. Beneficiaries of this linkage will include: the patient and their doctor; drug researchers in both the discovery and development phases; epidemiologists attempting to analyse health trends; and policy- and decision-makers developing effective national and EU-wide health policy options and legislation. Enabling this connection will require a revolution in integrated information management and decision making. This constitutes a fundamental transformation of biomedical science – from probability-based and empirical to evidence-based and knowledge-driven.
The project outcomes will enable the prediction of health, disease, therapy and its effects for individual patients and and through application in the clinic will change the future of medicine.
18 page presentation ITFoM fet11 Analytical platform
22 pages on the importance of getting more prevention and accurate diagnosis as the burden of cancer and other disease is predicted to increase. If cancer levels increase by 3 times by 2030 (because of older population) and we do not have a better handle on the medicine and costs it will be an even bigger problem.
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