TRANSLATIONAL RESEARCH

The InforSense Translational Research Solution (TRS) provides a powerful and flexible framework to integrate and analyze clinical, patient specimen and experimental data for translational research. The solution enables different user groups to integrate data and construct analysis workflows that can then be deployed to a wider scientific audience. With these capabilities in place, users can use the Clinical Population Explorer to select a cohort of case and control patients to compare. These can form the basis of gene expression or Genome Wide Association Studies to identify biomarkers for diseases or targets, better understand disease progression or select appropriate drug dosage.

• Integrate data from HL7 healthcare databases, LIMS databases and experimental data sources using advanced data integration and ETL capabilities. Data can either be loaded into a new data warehouse or federated within the InforSense solution. This allows systems to be quickly put in place and usage understood and optimized, with the final processes being used to implement a full warehouse.
• Advanced data representation for temporal and spatial data is provided in the InforSense solution. These types are essential to model disease progression and events in a patient’s treatment and to understand images.
• Build Analysis Workflows that exploit powerful analytical tools and are able to automatically populate Excel spreadsheets.
• Deploy workflows via a web interface using interactive charts and expert constructed workflows that allow users to ask powerful questions.

The Translational Research Solution builds on InforSense’s expertise developing translational research analytics applications for the world’s leading research institutes. It incorporates the power of the InforSense 5.0 platform with expertise in micro-array analysis from BioSense, cohort identification and clinical decision support from ClinicalSense and automated QC and analysis of Genome Wide Association Studies from GenSense. This enables translational analysis to be quickly implemented out of the box with minimum configuration, but enables best practice analytical workflows to be developed and modified by internal teams, providing the flexibility to manage this evolving research field.