Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine

Development of a Large-Scale De-Identified DNA Biobank to Enable Personalized Medicine

2008 September ; 84(3): 362–369 | DM Roden, JM Pulley, MA Basford, GR Bernard, EW Clayton, JR Balser, and DR Masys
The article describes the development of a large-scale de-identified DNA biobank linked to phenotypic data from an electronic medical record (EMR) system at Vanderbilt University Medical Center. The "opt-out" model was implemented after extensive review and community input, with only a minority of patients ( (~5%) ) opposing the concept. Surveys indicated that 90% of respondents were comfortable with the idea of anonymized genetic information being used for research. The standard "consent to treatment" form was modified to include a statement about the DNA databank and an opt-out option. The de-identification process was validated to ensure acceptable error rates (<0.3% for complete HIPAA identifiers and <0.1% for aggregate error). The biobank has a weekly accrual rate of 700-900 samples, with a diverse range of phenotypes based on EMRs. The resource is designed to facilitate the study of genotype-phenotype relationships and personalized medicine, addressing challenges such as sample handling, de-identification, and community engagement. The article also discusses the advantages and limitations of the opt-out approach, emphasizing the need for continuous institutional investment in clinical genomics and biomedical informatics.The article describes the development of a large-scale de-identified DNA biobank linked to phenotypic data from an electronic medical record (EMR) system at Vanderbilt University Medical Center. The "opt-out" model was implemented after extensive review and community input, with only a minority of patients ( (~5%) ) opposing the concept. Surveys indicated that 90% of respondents were comfortable with the idea of anonymized genetic information being used for research. The standard "consent to treatment" form was modified to include a statement about the DNA databank and an opt-out option. The de-identification process was validated to ensure acceptable error rates (<0.3% for complete HIPAA identifiers and <0.1% for aggregate error). The biobank has a weekly accrual rate of 700-900 samples, with a diverse range of phenotypes based on EMRs. The resource is designed to facilitate the study of genotype-phenotype relationships and personalized medicine, addressing challenges such as sample handling, de-identification, and community engagement. The article also discusses the advantages and limitations of the opt-out approach, emphasizing the need for continuous institutional investment in clinical genomics and biomedical informatics.
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