• Proceedings of the KAIS Fall Conference
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• 2010.11b
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• pp.673-676
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• 2010

본 연구에서는 임상시험 데이터를 수집하는 CRF를 웹의 표준인 XML 기반으로 설계하고, 임상시험데이터 표준인 SDTM으로 변환된 eCRF를 생성하는 XML 기반 프로세스을 개발했다. 데이터구조와 폼이 분리되는 XML 기반 개발 프로세스는 XML Schema로 eCRF를 개발하고, SDTM을 적용한 XML 문서를 생성한다. 생성된 XML 문서에서 SDTM 규약에 맞는 도메인별로 변환방법을 제시한다. 이에 eCRF 분석과 데이터베이스 설계 및 구현이 동시에 이루어진다.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.8
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• pp.566-575
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• 2009

Clinical Data Interchange Standards Consortium (CDISC) developed global and platform-independent data standards to improve ineffective processes of clinical trial studies. Regardless of its objective toward global cooperation, the current version of the CDISC standard cannot describe clinical trial data in various languages for multi-national investigators or reviewers. This problem applies not only to tabulated datasets in Study Data Tabulation Model (SDTM) but also to extensible markup language representation of the datasets in Operational Data Model (ODM) instances. In order to address this issue, we propose to extend the current version of SDTM and ODM to collect clinical data for multi-national clinical trials. SDTM needs to have new special-purpose domain for multi-language representation purpose. Additionally, ODM is recommended to extend its XML schema using subtyping or type inheritance mechanism respectively. Our extension of SDTM and ODM enable to represent any granule of study data tabulation model or XML data entities to describe in efficient languages. This result will contribute to collect multi-language data easily for multi-national clinical trials.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1830-1840
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• 2011

CDISC (Clinical Data Interchanging Standards Consortium) standards are to support the acquisition, exchange, submission and archival of clinical trial and research data. SDTM (Study Data Tabulation Model) for Case Report Forms (CRFs) was recommended for U.S. Food and Drug Administration (FDA) regulatory submissions since 2004. Although the SDTM Implementation Guide gives a standardized and predefined collection of submission metadata 'domains' containing extensive variable collections, transforming CRFs to SDTM files for FDA submission is still a very hard and time-consuming task. For addressing this issue, we developed metadata based SDTM mapping rules. Using these mapping rules, we also developed a semi-automatic tool, named CDISC Transformer, for transforming clinical trial data to CDISC standard compliant data. The performance of CDISC Transformer with or without MDR support was evaluated using CDISC blank CRF as the 'gold standard'. Both MDR and user inquiry-supported transformation substantially improved the accuracy of our transformation rules. CDISC Transformer will greatly reduce the workloads and enhance standardized data entry and integration for clinical trial and research in various healthcare domains.

• Proceeding of EDISON Challenge
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• 2017.03a
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• pp.672-676
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• 2017

데이터 처리 및 도표화는 임상 연구 보고서에 부록을 작성할 때 시간 소모적인 작업이다. 저자는 SAS (버전 9.3) 및 R (버전 3.3.1: PK 플롯 생성 용)을 사용하여 CDISC/SDTM 표준에 부합하는 자동 부록 생성 시스템 (ARGUS)을 개발했다. 이 시스템은 하나의 주 프로그램과 세 개의 서브 프로그램으로 구성되어 있다. 일반적인 데스크탑 환경에서 제출 버튼을 누른 후 약 1 분 만에 데이터베이스 파일을 MS Word 형식의 부록 문서로 변환한다. ARGUS 시스템을 사용하여 약 8일간 팀을 구성한 부록을 작성하던 작업이 6~7 시간 내에 완료되었다.