Paediatric hospital studies advanced with translational research solution
The Children's Hospital of Philadelphia (CHOP), a leading paediatric hospital and research facility, has implemented the InforSense-based translational research solution from IDBS to advance the understanding of complex genetic disease. Using the solution, CHOP can more easily define and run studies to identify relevant gene variants or link a diseased gene with a complex trait that causes or triggers certain childhood diseases and conditions including cancer, diabetes, asthma, and autism.
Using the translational research solution, researchers at CHOP can interactively build a custom phenotype (or patient group) based on multiple dimensions of patient data from nearly 90,000 patient records and get immediate, transparent results. Once the comparative groups are identified, researchers use the solution to integrate with existing PLINK programs to analyse genetic data from Illumina and Affymetrix genotyping platforms. Results are displayed in interactive web-based views, which can automatically link to additional annotation from metabolic pathway databases, public databases, and scientific literature. Because the process is smooth and intuitive, principal investigators (PI) or researchers can perform all activities without requiring support from IT, thus accelerating the pace of research.
'Using this software helps make our research much more manageable and transparent, and we are better able to mine the deep and rich data at our disposal,' said Hakon Hakonarson, MD, PhD, director of the Center for Applied Genomics at CHOP. 'Having both clinical and genomics components, it easily integrates with our existing infrastructure and gives us the technical functionality and the transparency we need to further our research.'
'We are delighted to be working with The Children's Hospital of Philadelphia in such an important research area,' said Neil Kipling, founder and CEO of IDBS. 'The capability of the InforSense solutions means that PIs can seamlessly combine clinical and genomic data and discover subtleties in patient populations that support the improved understanding of complex multigenic diseases.'