An Architecture for Integrating Genetic and Clinical Data

Personalized medicine is the new horizon of the medical science. Its main goal is to improve the quality of patient care, both in prevention and in therapeutic stage, and to improve the precision of therapy through the integrated analysis of clinical, biological and molecular data. Data integration represents a powerful instrument for clinicians to have an overall vision of diseases. Even if clinical data integration has been treated in many recent papers, few results have been presented with respect to integrating proteomics and genomics data. We present the architecture for the integration of genetic and phenotype data extracted from medical records. The focus is information extraction and data prefiling for early detection of chronic diseases. Focus is about cancer diseases where omics data, environmental, ontologies and clinical data can be integrated to improve knowledge about the risk assessment and genetic susceptibility.