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While the challenges of integrating small animal/co-clinical data with data on humans are steep, given the lack of common data standards, the potential rewards are great. This goal depends on a common data standard and tool supportsupport by tool vendors for the standard. For example, consider the imperative scenario of wanting to generate effective therapy for a cancer patient. Researchers With an integrated query system, researchers could search in vivo imaging, radiology, and digital pathology data from the patient, run a gene panel, and identify abnormal genes in the patient. They could then compare these results to a genetic panel on a mouse, made possible with data described by With small animal/co-clinical data meeting the DICOM standard, to find a matching tumor. Small animal researchers could then experiment therapies on that mouse that could also researchers could find a mouse with the same kind of tumor and compare its response to various therapies that could eventually benefit the human patient. Finally, the researchers could run an integrative query to develop a sophisticated diagnosis and treatment plan.

Directly comparing data from co-clinical animal models to real-time clinical data is the goal of

The goal of the Small Animal/Co-clinical Improved DICOM Compliance and Data Integration sub-project is to The impact on integrative research projects such as co-clinical trials would be to give researchers the ability to directly compare data from preco-clinical animal models with to real-time clinical data.

Developing DICOM standards for small animal imaging and identify co-clinical datasets to test the integration of TCIA and TCGA for this data.

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