The completion of the Human Genome Project sparked the development of many new tools to be used in finding the mechanism behind disease. While the goal is clear, the path to such discoveries has been fraught with roadblocks in terms of technical, scientific, and sociological challenges. Historically, there have been few interactions between the research communities of medical informatics, medical imaging and bioinformatics. However, recent landmark achievements in genomics and the increased importance of genetics in healthcare are already changing the clinical landscape and are necessitating a highly interdisciplinary approach.
In recent years:
A large number of genomes are fully sequenced and public. The size of genomic databases increases exponentially containing tens higher organisms, hundreds of model and economically important species, thousands of microbial pathogens and almost all important viral genomes. Comparative genomics allow the identification of conserved structural and regulatory elements within the genomes.
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All kinds of proteins are deduced from the various genome projects. Within them conserved or variant regions, functional and structural elements, features and domains are identified. The continuum of life forms becomes clearer and the differences measurable. Novel biocatalysts and the parameters relating structure to function are identified from the diversity of living organisms. The network of molecular interactions and complex biological processes become available for modelling and in silico experimentation.
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Gene expression profiles allow clear identification, monitoring and classification of various organisms (i.e. pathogen strains), different tissues and tumours, health and disease states. Profiling highlights specific macromolecules and metabolic pathways (i.e. surface antigens) that could allow targeting of drugs or therapies.
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High-throughput screenings of hundreds of targets are generating new functional coordinates within the chemical space. Classification of chemical compounds and targets into functional groups, identification of relations between distant targets and drug effects and knowledge visualization for chemical structures and properties become the main tools for knowledge based drug discovery. Advanced protein engineering via computer aided design becomes a sophisticated tool for the development of new biocatalysts, therapeutics and diagnostic tools.
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Advanced methods (high-throughput crystallography, NMR) accelerate the resolution of new protein structures. New groups of 3D protein structures improve modelling of macromolecules. Information integrating environments allowing computer aided drug design and virtual screening for compound are developed by bioinformatics companies.
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A variety of biosensors that allow simultaneous monitoring of several metabolites and biological signals become widely available, portable and distributed. Additionally molecular imaging techniques and other functional imaging methods, such us PET and functional-MRI, are assuming new, important roles in molecular-genetic imaging cell metabolic states, for the in vivo monitoring of protein interactions and gene-expression.
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Functional genomics and genetic studies elucidate the function of unknown genes, mostly by the use of holist post-genomic approaches. The genetic determinants of multigenic diseases are analysed and evaluated. Pharmacogenetics identify the genetic basis of drug efficiency and adverse effects. Pharmacogenomic information from clinical trials are generating the basis of the future "targeted precise pharmacotherapy": the right drugs in the right doses to the right patient.
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Correlations between genotypes, gene regulatory networks and biochemical pathways allow the intervention and metabolic readjustments for combating complex diseases such as obesity, hypertension, hypercholesteraemia etc.
These recent and forthcoming developments in genomics and the increased importance of genetics in healthcare are already changing clinical care. Electronic genetic consulting becomes a trend. Sequencing and genotyping is being established as a laboratory routine in many healthcare systems and enterprises begin to enrich their service offering, such as providing analysis for health related genomic information (i.e. subscription sequencing).
But what is more important is the expectation that the new knowledge coming out of life science projects will change the world as much as or more than the Internet, will transform the pharmaceutical and health care industries and will profoundly improve the practice of medicine.
The vision is that since most individuals maintain unique genotype information they, or authorised health professionals, should in the future consult this information for their dietary choices, for lifestyle and job placement decisions, prenatal diagnosis of suspected disorders, evaluation of possible disease symptoms and risks. Classical epidemiological and clinical research on one hand and genomic research on the other, separately considered, are no longer capable for advancing the so-called genomic medicine.
Genomic medicine integrates molecular medicine, which aims to explain life and disease in terms of the presence and regulation of molecular entities, and individualised medicine, which applies genotypic knowledge to identify predisposition to disease and develops therapies adapted to the genotype of a patient. The former is driven towards gaining knowledge about the disease, while the latter tries to identify and clinically utilise individual genetic information. Needless to stress that individual genotypic information, essential to such approaches, must be the subject of extremely stringent security.
The integration and exploitation of the data and information generated at all levels by the disciplines of bioinformatics, medical informatics, medical imaging and clinical epidemiology requires a new synergetic approach that enables a bi-directional dialogue between these scientific disciplines and integration in terms of data, methods, technologies, tools and applications. Biomedical Informatics (BMI) is the emerging discipline that aims to put these worlds together so that the discovery and creation of novel diagnostic and therapeutic methods is fostered. This will eventually herald a new era of what has become known as 'individualised medicine', whereby the drugs people are prescribed will depend on their personal genetic makeup, especially where there are significant cost or risk implications.
The mission of BMI is to provide the technical and scientific infrastructure and knowledge to allow evidence-based, individualised healthcare using all relevant sources of information. These sources include the "classical" information as currently maintained in the health record, as well as new genomic, proteomic and other molecular-level information. BMI bears the potential to improve the health and quality of life of the individual, as well as to reduce the overall costs of healthcare systems, by enabling a paradigm shift from late stage diagnosis towards early detection or even prediction of disease.
In achieving this vision a new breed of techniques, systems and software tools are necessary in order to convert the enormous amount of data that geneticists and molecular biologists can obtain at their labs into information that physicians and other health care providers can use for the delivery of care and the converse - to codify and anonymize clinical phenotypic data for analysis by researchers.