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IBM Haifa Research Lab SPA a Platform for Hereditary Disease Management and Pedigree Analytics Rizzoli FOAK Alex Melament, [email protected] July 2010 IBM Haifa Research Lab: Let’s Build a Smarter Planet IOR - Rizzoli Orthopaedic Institute • IOR- is the main Italian institute of orthopedics and has a status of a 'Scientific research hospital’ - About 150,000 patients examined every year - Over 18,000 orthopedic operations every year - Nine laboratories at the institute employing a staff of 250 including doctors, biologists and technicians. • Medical Genetic Unit specializes in Rare Skeletal Hereditary diseases such as: - Multiple Osteochondromas (MO) - • Osteochondroma is a cartilage capped bony projection arising on the external surface of bone containing a marrow cavity that is continuous with that of the underlying bone Osteogenesis Imperfecta (OI) • It is frequently caused by defect in the gene that produces type 1 collagen, an important building block of bone. There are many different defects that can affect this gene. 1 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet Project Goals • Understanding the relationships between hereditary diseases and their genetic background - Analysis of inherited diseases and their associated phenotypes is of great importance to gain knowledge of underlying genetic interactions Discovering and defining a correlation between Phenotype and Genotype data will enable • Fit adequate treatment protocol • Ensure appropriate clinical follow-up • Improve patient’s quality of life • Build Healthcare Platform that will enable efficient treatment and productive research in Hereditary Diseases 2 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet IT for understanding of Hereditary Diseases • Collects and Integrates medical images, clinical and genomic data of each patient and his family - Leverages standards such as DICOM and HL7 - Maintains content and context aware associations to support clinical and research usage • Enables secure cross Hospital data and knowledge sharing - Leverages Industry’s Best Practices, Standards and IHE Profiles - Enables cross Hospital Patient ID correlation through PIX&PDQ interfaces • Enables data insights discovery - Supports federated queries - Provides on demand pedigree visualization - Provides a platform for data analytics & knowledge extraction • Enables to host third party analytics 3 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet Pedigree Analysis • The pedigree documents biological relationships in families and the presence of diseases. - Pedigree includes number, gender and closeness of affected relatives, their ages at disease onset, and associated health conditions • Pedigree is needed to - Assess disease risk - • BRCARPO risk model can indicate a chance of having BRCA1 or BRCA2 mutations Investigate correlation between Phenotype and Genotype data 4 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet Solution Architecture Hospitals (PACS, Clinical and Genetic Labs) EHR, Knowledge Systems DICOM HL7 v3, v2.x Physicians and Researchers WS WS Pedigree Analytics Cross River/Rimon (Phenotype,Genotype) WAS 7, DB2 Data Warehouse WAS 7, IBM CM Data Federation + WAS 7, DB2 Data Warehouse WAS 7 Excel BO Cube Services & IBM BI Infrastructure CMO Cognos Healthcare BUS (WAS7/WPS 6.1, HL7 v2&3, WS, IHE profiles) PIX/PDQ Server WAS 7 Partners (Disease risk assessment models, Pedigree clustering, classification and visualization tools) 5 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet Pedigree Visualization • Dynamic pedigree visualization • Presentation of all available information for the persons in the pedigree - Clinical, genomic data and medical images • Standard pedigree representation - HL7 v3 Family History - Enables standard based pedigree interoperability • Enables disease risk assessment 6 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet On Demand Analytics Platform – Currently Available Algorithms • Decision Trees – Explanation of one dimension by others; Clustering - Random ID3 - C4.5 (entropy based) • Bayesian Networks – Data Cleansing - Naive Bayes - Chu-Liu Trees • K-Means – Clustering - Hamming distance for category dimensions only - Continuous dimensions only - Discretization of Continuous dimensions by Entropy and application of • Hamming distance on all the dimensions. Statistical Analysis - Chi-Square – Association between two category dimensions - Spearman – Association between two category dimensions 7 © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet CMO – SOA based Medical Imaging Repository Image Processing • Supports DICOM, WADO, HL7, XDS-I, PIX and PDQ • Provides secure cross-enterprise Imaging Archive Image Consumers sharing • Complies with regulations for storing and managing data • Enables extensibility and reuse of existing legacy assets through an open and flexible architecture • Leverages IBM's market-proven middleware to ensure scalability, high availability and disaster recovery Data Sources (CT, MRI, US…, PACS) 8 Fine-Grained Authorization Data Analytics © 2009 IBM Corporation IBM Haifa Research Lab: Let’s Build a Smarter Planet 99 © 2009 IBM Corporation