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Translational Research

Bridging the divide between genomics and clinical domains

The promise of the Human Genome Project was to enable the understanding of the genetic basis for disease and hence develop better therapies. However full realization of this promise requires that the associated phenotype be linked to this genomic information and that has not occurred on the scale needed to fully drive discovery of new medicines. While there have been huge advances in the generation of data (e.g. next generation sequencing, imaging, proteomics etc), as well as the digitization and exchange of healthcare records, a huge divide still exists in linking this data together to enable discovery. This divide can be largely overcome through an informatics infrastructure that enables frictionless information exchange to support translational research and achieve the vision of personalized medicine.

The challenges to frictionless information exchange

The amount, depth, breadth and complexity of genomic, biological, clinical and patient data poses huge challenges to frictionless information exchange needed to support translational research. These challenges can be summarized into four key areas;

Multiple, disparate data sources – in order to link genotype with phenotype a variety of heterogeneous data sources must be brought together in a semantically correct fashion. These data sources are often massive, may require curation and may contain less than perfect data

Ensure compliance and security  – on the clinical side of the divide is data that is sensitive patient health information (PHI) that must be managed in accordance with regulatory guidelines.

Support collaboration – translational research is multidisciplinary and collaborative studies are the norm. Informatics systems must be able to support this collaborative model while maintaining regulatory compliance and ensuring that scientific discovery proceeds unimpeded.

Drive the science  – the expectation is that new knowledge can be obtained from this huge body of biological and clinical information that will lead to new diagnostics, prognostics or  therapies that will improve patient outcomes. Such a goal will require tools to explore the data, formulate hypotheses and allow domain experts to work together to enable the bench-to-bedside-bench loop.

Enabling frictionless information exchange through translational informatics

Bridging the gap between the biological (bench) and clinical (bedside) domains and overcoming the barriers to frictionless information exchange can be achieved with the adoption of translational informatics platforms. Labmatrix, which was designed from the ground up to manage translational research data provides the critical informatics infrastructure to facilitate;

Why choose Labmatrix as your translational informatics platform?

Simply put because Labmatrix was designed to drive frictionless information exchange for translational research as it was initially developed to support translational research activities at Johns Hopkins. Labmatrix offers a range of benefits to bridge the bench-to-bedside divide;

Collection and harmonization of biological and clinical data – support for data integration and harmonization with specialized informatics systems (such as ELN, EMR, and LIMS)  provides a holistic, unified view of information across the bench-to-bedside divide.

Support for collaboration– Providing the critical infrastructure to maximize the value of massive integrated data sets, while ensuring appropriate access controls.

Generation of scientific insights – puts powerful tools for data exploration, reporting and ad hoc query in the hands of researchers so that they can mine the richly annotated information to drive translational research studies.

Enhanced security and compliance – Fine-grained access controls and security that extend across the biological-clinical divide and ensure that all collaborators, have the access they need, while maintaining compliance.