Development of an Integrated Biospecimen Database among the Regional Biobanks in Korea

Abstract

ObjectivesThis study developed an integrated database for 15 regional biobanks that provides large quantities of high-quality bio-data to researchers to be used for the prevention of disease, for the development of personalized medicines, and in genetics studies.MethodsWe collected raw data, managed independently by 15 regional biobanks, for database modeling and analyzed and defined the metadata of the items. We also built a three-step (high, middle, and low) classification system for classifying the item concepts based on the metadata. To generate clear meanings of the items, clinical items were defined using the Systematized Nomenclature of Medicine Clinical Terms, and specimen items were defined using the Logical Observation Identifiers Names and Codes. To optimize database performance, we set up a multi-column index based on the classification system and the international standard code.ResultsAs a result of subdividing 7,197,252 raw data items collected, we refined the metadata into 1,796 clinical items and 1,792 specimen items. The classification system consists of 15 high, 163 middle, and 3,588 low class items. International standard codes were linked to 69.9% of the clinical items and 71.7% of the specimen items. The database consists of 18 tables based on a table from MySQL Server 5.6. As a result of the performance evaluation, the multi-column index shortened query time by as much as nine times.ConclusionsThe database developed was based on an international standard terminology system, providing an infrastructure that can integrate the 7,197,252 raw data items managed by the 15 regional biobanks. In particular, it resolved the inevitable interoperability issues in the exchange of information among the biobanks, and provided a solution to the synonym problem, which arises when the same concept is expressed in a variety of ways.

Specifics of creating clinical abstract of biospecimens

“…FSN представляет собой комбинацию основных частей и символа двоеточия ":", который действует как разделитель, например: <Аналит/компонент>:<вид свой ства наблюдения или измерения>:<временнóй аспект>:<система (образец)>:<масштаб>:<метод> 6 . Системы SNOMED-CT и LOINC были успешно применены для объединения данных 15 региональных биобанков Кореи, а также широко используются в рамках исследований сети eMERGE и других проектов [23,40].…”

Consent and Privacy in the Era of Precision Medicine and Biobanking Genomic Data

“…165 Furthermore, regardless of how well-crafted international regulations and guidelines are, the possibility of bad actors or a hacking incidents looms. 166 V.…”