Biomedical Informatics in Support of Individualized Medicine

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 health care are already changing the clinical landscape and are necessitating a highly interdisciplinary approach.

Recent and current developments include the following:

• A large number of genomes are now fully sequenced and public. The size of genomic databases has increased exponentially, now containing tens of higher organisms, hundreds of model and economically important species, thousands of microbial pathogens and almost all the important viral genomes. Comparative genomics allows the identification of conserved structural and regulatory elements within the genomes. Light has also been shed on the vast portion of the non-coding regions and 'gene deserts'.
• A large variety of proteins have been deduced from the various genome projects, and within them have been identified conserved or variant regions, functional and structural elements, features and domains. The continuum of life forms has become clearer and the differences between species measurable. Novel biocatalysts and the parameters relating structure to function have been identified from the diversity of living organisms, and the network of molecular interactions and complex biological processes has become available for modelling and 'in silico' experimentation.
• Gene expression profiles now allow clear identification, monitoring and classification of various organisms (eg pathogen strains), tissues and tumours, and states of health and disease. Profiling can highlight specific macromolecules and metabolic pathways (eg surface antigens) that could allow targeting of drugs or therapies.
• High-throughput screening of hundreds of targets is generating new functional coordinates within the chemical space. The primary tools for drug discovery are now the 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. Advanced protein engineering via computer-aided design has proven a sophisticated aid in the development of new biocatalysts, therapeutics and diagnostic tools.
• Advanced methods (eg high-throughput crystallography, nuclear magnetic resonance (NMR)) have accelerated the resolution of new protein structures, and the modelling of macromolecules has been improved by new groups of 3D protein structures. Bioinformatics companies have developed information-integrating environments that allow computer-aided drug design and virtual screening for compounds.
• A variety of portable and distributed biosensors allowing simultaneous monitoring of several metabolites and biological signals have become widely available. In addition, molecular imaging techniques and other functional imaging methods such as positron emission tomography (PET) and functional magnetic resonance imaging (MRI) are assuming new and important roles in molecular-genetic imaging of cell metabolic states. This is used for the in vivo monitoring of protein interactions and gene expression.
• Functional genomics and genetic studies are elucidating the function of unknown genes, mostly by the use of holistic post-genomic approaches. The genetic determinants of multigenic diseases are being analysed and evaluated, and pharmacogenetics is identifying the genetic basis of drug efficiency and adverse effects. Pharmacogenomic information from clinical trials is generating the basis of the future 'targeted precise pharmacotherapy'; that is, the right drugs in the right doses to the right patient.
• Correlations between genotypes, gene regulatory networks and biochemical pathways now allow intervention and metabolic re-adjustments in combating complex diseases such as obesity, hypertension, hypercholesteraemia etc.

These developments and the increased importance of genetics in health care are already changing clinical care. Electronic genetic consulting is becoming common, and sequencing and genotyping are being established as laboratory routines in many health-care systems. Enterprises are also beginning to enrich the services they offer, providing, for example, analyses of health-related genomic information (ie subscription sequencing).

More importantly however, there are expectations that the new knowledge coming out of life science projects will change the world as much as or more than the Internet has, transforming the pharmaceutical and health-care industries and profoundly improving the practice of medicine. Since most individuals maintain unique genotype information, it is envisaged that they, or authorised health professionals, will in the future consult this information for their dietary choices, lifestyle and job placement decisions, prenatal diagnosis of suspected disorders and evaluation of possible disease symptoms and risks. Taken individually, classical epidemiological and clinical research and genomic research are no longer capable of advancing this so-called genomic medicine.

Genomic medicine integrates molecular medicine with individualized medicine; the former aims to explain life and disease in terms of the presence and regulation of molecular entities, and the latter applies genotypic knowledge to identify predisposition to disease and develop therapies adapted to the genotype of a patient. Needless to say, individual genotypic information, essential as it is to such approaches, must yet be the subject of extremely stringent security.

The exploitation of data from bioinformatics, medical informatics, medical imaging and clinical epidemiology requires a new and synergetic approach that enables a bi-directional dialogue between these scientific disciplines, and integration in terms of data, methods, technology, tools and applications. Biomedical Informatics (BMI) is an 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 'individualized medicine', whereby the drugs people are prescribed will depend on their personal genetic makeup, especially where there are significant costs or risk implications.

The mission of BMI is to provide the technical and scientific infrastructure and knowledge to allow evidence-based, individualized 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 has the potential to improve the health and quality of life of the individual, as well as to reduce the overall costs of health-care systems, by enabling a shift from late-stage diagnosis to early detection or even prediction of disease.

To achieve this, a new breed of techniques, systems and software tools are required for two main reasons: to convert the enormous amount of data collected by geneticists and molecular biologists into information that physicians and other health-care providers can use for the delivery of care and the converse, and to codify and anonymize clinical phenotypic data for analysis by researchers.
Significant progress is also necessary in a number of domains, including:

• ontology-based integration of heterogeneous biological and clinical databases and the creation of a life-long active electronic health record for every citizen
• methods and tools for knowledge discovery, representation and visualization
• advanced computational methods in support of drug discovery, rational drug design, clinical trials and pharmacogenomics
• molecular and metabolic imaging methodologies in medicine
• simulations and modelling of molecular interactions, metabolic pathways, cells, tissues, and organs
• Grid-based approaches for demanding molecular-biomedical computational applications
• novel security-related methods and technology.

The goals of the current issue of ERCIM news, the first issue dedicated to biomedical informatics due to the relatively new nature of the field, are to show selected approaches and results from the research community of ERCIM, and to present the goals and objectives of some recently funded national and EU projects in this area.

Of the many articles submitted to this special theme, the 32 selected were most relevant to the domain of biomedical informatics. While some of the articles are still rooted in individual fields (eg medical informatics and bioinformatics), we believe they are relevant for the future multidisciplinary domain of BMI. Work reported in these articles can be divided into the following main areas:

• European R&D and national projects: articles in this category present the main objectives of selected European and national projects.
• Integration and analysis of biomedical data: a central issue in BMI is the integration of genetic information with the medical information contained in electronic health records or population databases in order to develop advanced prognostic or therapeutic tools for health professionals.
• A number of articles address this area, with several focusing on Grid-based approaches to these demanding molecular-biomedical applications.
• Data mining and visualization of biomedical data: the integration and exploitation of data from the disciplines of bioinformatics, medical informatics, medical imaging and clinical epidemiology require new methods and tools; several articles look at state-of-the-art technology in this area.
• Simulation and modelling of biomedical processes: several articles deal with computationally demanding tasks of modelling and simulation, including modelling a living cell and developing 'in silico' virtual experiments.
• Biomedical image and signal analysis: several articles describe research in biomedical imaging, with an emphasis on molecular-genetic imaging. Some also relate to traditional medical image analysis, but provide a treasure chest of tools and methodologies that can easily be applied in the biological domain.
• A couple of articles are also included which are related to chemoinformatics, and to the linking and integration of risk and environmental data. They are both relevant to future 'holistic' approaches to biomedical data and information management.

Finally, the newly formed ERCIM Working Group on Biomedical Informatics is introduced. The article describes the group's objectives, activities to date, and short-term plans in its attempt to create a highly interdisciplinary and distributed BMI research community from ERCIM organisations and other relevant stakeholders in Europe.

Please contact:
Manolis Tsiknakis or Dimitris Kafetzopoulos, FORTH
E-mail: tsiknakiics.forth.gr, kafetzoimbb.forth.gr