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The ‘Virtual Patient’ in healthcare: IT Future of Medicine

To be able to mobilise our healthcare system to treat patients as individuals rather than as members of larger, divergent groups, the IT Future of Medicine (ITFoM) initiative proposes to develop a new, data rich computation-based individualised medicine of the future, based on integrated molecular, physiological and anatomical models of every person (‘Virtual Patient’) in the healthcare system. The establishment of such ‘Virtual Patient’ models is now possible due to the enormous progress in analytical techniques, particularly in the ‘omics’ technology areas and in imaging, as well as sensor technologies. Complemented by continuing developments in ICT, these technological developments could, over the coming years, make the ‘Virtual Patient’ a key component in healthcare and disease therapy and prevention. ITFoM is an European consortium combining unparalleled expertise in medicine, analytics and ICT to develop the ‘Virtual patient’.

by the ITFoM consortium

Today´s medicine
Currently medicine assesses patients as parts of large, often inhomogeneous groups. Rather than as individuals, patients are treated as members of a group for which a specific therapy has been statistically shown to be more effective than other therapies. This is even regardless of the fact that this therapy might very well make the majority of patients more ill than they would be without treatment.

Today’s medicine does not take into account the tremendous diversity between human individuals. Moreover, diseases are not homogenous either in regard to clinical manifestation or underlying causative effects. In cancer this is taken to an extreme with each tumour being different, because each of these tumours is the product of a specific and unique accumulation of mutational events.

Symptoms and signs of disease often appear only late in disease progression when a large portion of the involved organ has already failed. The symptoms might be non-specific, making a diagnosis difficult. Today´s routine clinical workup of sick patients can be extensive, expensive and can have side effects. For these reasons, many advocate preventive measures that mandate predefined checkups to be carried out by primary care physicians. Only a few preventive measures are currently useful including blood pressure control, blood sugar and lipid measurements, colonoscopy in older people, gynaecological tests in women and last but not least weight control. Both in the presence or absence of symptoms and signs of diseases, the knowledge of the full genome, the metabolome, the proteome, the microbiome and the total exposure to toxins from the environment, would have a tremendous impact on both disease workup and preventive measures.

Tomorrow´s medicine
The medicine of the future will use a ‘Virtual Patient’ system that can integrate all molecular, physiological and anatomical data into personalised models of individual people, enabling prediction of the result of lifestyle choices and medical interventions on a tailored case-by-case basis. This innovative approach will revolutionise healthcare systems, with enormous benefits for prevention, diagnosis and therapy of patients. The possibility to personalise the models allows tailor-made therapy and treatment strategies for each individual. With the model-based decision of which drug or which doses of drugs will have the optimal effect in an individual patient, the model approach will help to optimise treatment and reduce side-effects dramatically. A model-based approach will also serve as a research tool to discover and validate new compounds for drug development, potential drug treatments and applications, but also new commercial opportunities in ICT, analytics and healthcare.

ITFoM: IT Future of Medicine
ITFoM – one of the six pilot initiatives within the European Future and Emerging Technologies Flagship scheme competing for a total of 1 billion EUR over a time span of 10 years – will lay the groundwork for a project that will integrate medicine, analytical techniques and IT hardware and software development for the IT driven, data-rich, individualised medicine of the future.
By now, it has become quite conceivable to develop sequencing strategies allowing the determination of the genome, epigenome and transcriptome of a tumour, for instance, in parallel to its surgical removal, allowing the surgeon to scale the extent of the operation based on the real time computational modelling of its detailed genomic, epigenomic and transcriptomic characterisation. Dramatic improvements are also expected in the capabilities of other molecular analysis techniques, such as proteomics and metabolomics.

Why ITFoM makes the difference in ‘personalised medicine’: next generation of molecular analytics
The generation of the first draft of the human genome was a worldwide concerted action that had a strong impact on the development of new technologies for molecular biology. During the last ten years high throughput technologies have been emerging not only for DNA sequencing, but also for protein and metabolite analysis. These high throughput technologies are called ‘omics’ technologies, highly parallelised approaches aiming at the generation of information on complete sets of molecules in organelles, cells, whole pathways or even organs in order to get a comprehensive view of a biological system. A variety of ‘omics’ subdisciplines have emerged, each developing its own instruments, techniques and processes. With the increasing amount of data generated by the ‘omics’ technologies, development of tools for intelligent mathematical analysis and data mining are needed. This demand has developed into a completely new area in biology, namely bioinformatics.

For the first driver of the ‘omics’ technologies, DNA sequencing, currently the so-called ‘third generation’ sequencing technology is already appearing on the market. This innovation will allow the sequencing of a whole genome within one day, the costs for sequencing are in almost free fall, it can be anticipated that very soon the goal of sequencing a whole genome for less than 1.000 $ will be reached. These innovations open the door to allowing the sequencing of the genome of each single patient and using this information for truly personalised medicine. DNA sequencing is also used to study transcriptional expression, microRNA, DNA methylation, hydroxymethylation, transcription factor
occupancy, histone modification at specific sites in the genome and overall organisation of genomes in cells.

The personal genome information will be a very important basis for future medicine, but more ‘omics’ information will be integrated: information about proteins and metabolites will allow a much more precise picture of the physiological status of a person. The aim for protein and metabolite analysis now is to apply a method that allows the detection of all proteins and all metabolites in a given sample or tissue. The same holds true for the information about protein modifications and interactions.

Other lab technologies for molecular analysis including imaging and sensor technology are also starting to increase in speed, precision, application range and information output.

Another level of complexity takes into account life style and environmental factors, and more specifically the microorganisms interacting with the human body.

All these technologies allow the generation of highly detailed information about an individual’s genetic make-up and physiological status to give an unprecedented insight into the functioning of a person’s cells, tissues, organs and even the individual as a whole.

Systems biology is a solution that provides the methodologies and tools for mathematical analysis, integration and interpretation of biological data, employing mathematical models of biological processes. Mathematical models support the understanding of data sets on a large scale and integrate existing knowledge for interpretation. Model approaches in the ITFoM will drive the development further into models that are able to generate computational simulations to predict what cannot be measured directly. The translation of these novel approaches into clinical application will allow identification of the optimal therapy or medical treatment for each person based on the individual data available.

To generate the models and implement the ‘Virtual Patient’ model into clinical practice, substantial advances must be made in underpinning hardware and software infrastructures, computational paradigms, human computer interfaces and visualisation, as well as in the instrumentation and automation of techniques required to gather and process all relevant information. Examples of the major challenges in the information and communication technologies are interoperability, data storage and processing, efficient use of computing power, statistics and medical informatics. Integration of the individual datasets is realised via the ITFoM ‘Virtual Patient’ models enabling the provision of concrete health advice on a personal basis.

The authors
IT Future of Medicine Consortium (ITFoM)
Max Planck Institute for Molecular Genetics
Ihnestrasse 63-73
14195 Berlin