Practical Metadata Strategy for Clinical Research
Implementing a cohesive metadata strategy using existing standards like CDISC SDTM and tools to improve control and efficiency in managing clinical study data and metadata. The strategy involves creating a Study Metadata Modeler, standardizing metadata, and utilizing tools for better management and setup of studies.
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Presentation Transcript
A Coherent and Practical End-to-End Metadata Strategy using Existing Standards and Tools for Clinical Research Stephane AUGER Danone Research, FRANCE
CONTEXT Clinical studies performed in 4 divisions Dairy, Waters, Baby and Medical Nutrition Historically Mostly paper-based studies until very recently DM Outsourced to CROs Few internal data / metadata standards Result Few controls on data / metadata received from CROs Lack of homogeneity between studies Resource intensive to pool for meta analysis or format for a DR/DW
CONTEXT 2010 Upper management request for a Data Warehouse First, we need to get more control over our clinical study metadata Thought process to address the end goal: Use existing tools/software as much as possible Standardize up front CDISC SDTM, CDASH, ODM A bonus if we could make metadata management and study set-up more efficient
Key Decision #1: Metadata Standards Management (1) Implementation of a Study Metadata Modeler (SMM) with a duel use 1. Manage Study Metadata Standards CRF Forms, Item Groups, Items, Codelists Item Characteristics (type, formats, range values etc.) CRF completion guidelines / help text Database structure Based on SDTM/CDASH
Key Decision #1: Metadata Standards Management (2) Implementation of a Study Metadata Modeler (SMM) with a duel use 2. Create Study-Specific Metadata Use Metadata Library to create a study-specific CRF Export study-specific CRF in ODM format to an EDC system Requires ODM-compatible EDC system
SMM Functionality Workflow Config. CRF ODM DB Complex Edit Checks Structure Simple Edit Checks Database Admin. SMM EDC ODM IWRS Coding TSDV Visit Layout Custom Attributes Custom Configuration
Key Decision #1: Metadata Standards Management (3) SMM - Implementation Experience Define company standard CRF forms and variables Workgroups representing Clin Ops, QA, Statistics, Data Management 1 year 80 man/days Resulted in a Data Standards Committee and change management process Define standard DB structure in the SMM Each EDC has different production database specificities One library for multiple EDC systems SMM provider an essential resource 3 months 60 man/days
Key Decision #2: ODM-Compliant EDC (1) Implementation of ODM-compliant EDC tool(s) 1.ODM-in Import Study-Specific CRF metadata - ODM file 2.ODM-out Export study metadata & study data in ODM
Study Set-up: What s left to do? Workflow Config. CRF ODM Complex Edit Checks Visit Layout SMM Database Admin. Simple Edit Checks EDC ODM Medical Coding DB Structure Custom Attributes TSDV
Key Decision #2: ODM-Compliant EDC (2) Implementation Experience Many challenges to overcome and details to solve SMM & EDC implementation at the same time Requires tech-savy personnel 60-80% of the EDC study build is done automatically in this process Main differences between our two EDC tools Two-step ODM import process Visit configuration Complex edit checks need to be re-configured
Key Decision #2: ODM-Compliant EDC (3) Implementation Experience (2) Database & EDC Set-up Impact on EDC budget? 75% decrease in professional service costs 62% decrease in overall EDC budget CRF = EDC Set-up Reduced Programing Reduced Validation Metadata Control Standardization Efficiency Warehouse-ready data Impact on Data Management Resources? No Change in Study Build FTEs (but more tasks performed internally) 50 decrease in study set-up time (Protocol to EDC Go-Live) 20% increase in overall DM study budget (vs. Paper-based)
Roles and Responsibilities Complex Edit Checks EDC Vendor Hosting & Support CRF & Study Build C R O Validation Custom Config. / Reports Workflow Config. Danone (Data Manager) In-Study DM SMM Database Admin. ODM In Database Lock EDC
Key Decision #3: ODM-Compliant Mapping Tool Study Metadata Standards SMM EDC ?? ODM ODM Study Build ODM
Key Decision #3: ODM-Compliant Mapping Tool Implementation of ODM-compliant Mapping (ETL) tool 1.Maps ODM (from the EDC) to produce: SAS transport datasets (SDTM format) Define.xml Standardized ODM 2.Standard Mapping Metadata Re-Usable mapping scripts Validation = only once
Key Decision #3: ODM-Compliant Mapping Tool Data Repository? EDC a ODM ETL SAS Datasets Mapping Define.xml Tool ODM EDC b ODM
Clinical Study Data & Metadata Flow: Tools Conduct Exploit Build METADATA Metadata Standards & Study Set-up (Formedix) Data Collection (EDC) (Medidata RAVE OpenClinica) METADATA + STUDY DATA Mapping (XML4Pharma) Data Repository
Clinical Study Data & Metadata Flow: Management Conduct Exploit Build METADATA Metadata Standards & Study Set-up (Formedix) Data Collection (EDC) (Medidata RAVE OpenClinica) METADATA + STUDY DATA Mapping (XML4Pharma) Metadata Standards & Management Data Repository
Clinical Study Data & Metadata Flow: Standards Conduct Exploit Build METADATA Metadata Standards & Study Set-up (Formedix) Data Collection (EDC) (Medidata RAVE OpenClinica) METADATA + STUDY DATA SDTM/CDASH Mapping (XML4Pharma) SDTM Data Define.xml Repository ODM
Conclusion End-to-End metadata standardization and control is possible There are significant cost and time savings to be had! The tools and standards are ready and available NOW
