Clinical Genomics Data Standards for Pharmacogenetics and Pharmacogenomics

Abstract

This special report concerns a talk on data standards given at a workshop entitled 'An International Perspective on Pharmacogenetics: The Intersections between Innovation, Regulation and Health Delivery', which was held by the Organization for Economic Co-operation and Development (OECD) on October 17-19, 2005, in Rome, Italy. The worlds of healthcare and life sciences (HCLS) are extremely fragmented in terms of their underlying information technology, making it difficult to semantically exchange information between disparate entities. While we have reached the point where functional interoperability is ubiquitous, we are still far from achieving true semantic interoperability where a receiving system can use incoming data as though it was created internally. The critical enablers of semantic interoperability are information standards dedicated to HCLS data, spanning all the way from biological research data to clinical research and clinical trials, and finally to healthcare clinical data. The challenge lies in integrating various data standards based on predetermined goals, thereby improving the quality of care provided to patients.

Pharmacogenetics in Europe: Barriers and Opportunities

“…In the context of data availability it has been suggested that the clinical implementation of pharmacogenetics may to a large extent depend upon successful integration of EHR into healthcare systems [24]. …”

A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine

“…Third, with respect to the need for standardized representation of patient data, standard information models and terminologies are available for representing both genomic and non-genomic patient data [49,60]. These available standards include HL7 data standards for traditional medical data such as problem lists, medication lists, and clinical encounter history [49]; HL7 data standards for family history information and genetic testing data developed by the HL7 Clinical Genomics Special Interest Group [60]; and data standards developed by the National Cancer Institute as a part of its cancer Biomedical Informatics Grid (caBIG ® ) initiative [61].…”

“…These available standards include HL7 data standards for traditional medical data such as problem lists, medication lists, and clinical encounter history [49]; HL7 data standards for family history information and genetic testing data developed by the HL7 Clinical Genomics Special Interest Group [60]; and data standards developed by the National Cancer Institute as a part of its cancer Biomedical Informatics Grid (caBIG ® ) initiative [61]. Also, there is an effort within the HL7 Clinical Decision Support Technical Committee to standardize a "virtual medical record" that defines the superset of patient data relevant for CDS [62].…”

“…The HL7 data standard for genetic testing incorporates clinically relevant subsets of bioinformatics data standards, including the bioinformatic sequence markup language (BSML) for sequence data [60] and the microarray and gene expression markup language (MAGE-ML) for gene expression data [63]. Of note, MAGE-ML complies with Minimum Information About a Microarray Experiment (MIAME) guidelines [64], which specify the minimal set of data on gene expression assays that should be included within an assay report to allow for proper interpretation.…”

Pharmacogenomics: Role in Medicines Approval and Clinical Use

“…It has been estimated that for many drugs the efficacy is less than 50% [1]. Treated with the same drug, some individuals may have excellent responses, some of them may not respond at all or respond partially, and some others may also experience adverse drug reactions to standard doses [1,2,3,4]. As mentioned previously, this individual variability can be due to genetic, physiological, pathophysiological, or environmental factors.…”