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Managing and Analyzing Clinical Data

Managing and Analyzing Clinical Data

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Managing and Analyzing Clinical Data

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  1. Managing and Analyzing Clinical Data Mark Lambrecht, Principal Industry Consultant, SAS BIAS Meeting, March 14th 2014, Milan, Italy.

  2. Table of Contents SAS and CDISC • Clinical trial challenges • The promise for CDISC • SAS response • PROC CDISC, SAS Clinical Standards Toolkit, SAS Clinical Data Integration Roadmap and SAS destination Capabilities and processes supported by SAS Examples • Roundtrip in define.xml • Reading a define.xml • ADaM support • Bulk metadata manipulation

  3. Cardiovascular Therapeutic Brain Injury Schizophrenia SDTM QS Supplements Oncology Virology-Hepatitis C CDASH E2B SAE IG 2009 2008 2007 2006 2012 2010 2005 2003 2004 2002 2011 Diabetes ADaM MD Guide Multiple Sclerosis BRIDG v4.0 Virology BRIDG UG v2 Define.xml IG Validation Define.xml v2.0 Parkinson’s Disease PKD CDASH v2.0 Devices SDTM v1.5 SDTM IG v3.1.5 CDASH v1.2 BRIDG v3.0.3 BRIDG v3.2 SDTM v1.4 SDTM IG v3.1.4 SDTM v3.1.2 Am.1 ADaM Val. Checks v1.0 ADaM Val. Checks v1.2 ADaM General Occurrence Model v1.0 SDTM v1.2 SDTM IG v3.1.2 Alzheimer v1.0 SDTM Associated Persons IG v1.0 SDTM v1.3 SDTM IG v3.1.3 ADaM Integration IG v1.0 BRIDG v3.0.2 SDM.XML v1.0 CDASH v1.0 SEND v3.0.1 SDTM v1.1 SDTM IG v3.1.1 ADaM v2.1 ADaM IG v1.0 Extended ODM PRM XML Schema Tuberculosis ODM v1.3.1 ADaM Val. Checks v1.1 Asthma BRIDG v2.1 Pain Alzheimer v1.1 SDTM.xml v1.0 SDTM v1.0 SDTM IG v3.1 PRM Toolset v1.0 BRIDG v3.0.1 ODM v1.3 BRIDG v1.1 Define.xml v1.0 BRIDG v3.0 BRIDG v2.0 SEND v3.1 ADaM IG v1.1 CDASH v1.1 CDASH UG v1.0 SDTM Devices IG v1.1 Protocol Model v1.0 2013 2014 Protocol Concept Guide ODM v1.2 ODM v1.2.1 ADaM v2.0 BRIDG v1.0 BRIDG v1.1.1 BRIDG v2.2 ODM v1.1 SDTM Device Submission Pilot BRIDG v3.1 SEND v3.0 … The clinical trial challenges With the growth of industry standards, the level of complexity increases. The expected trend is continued increase of complexity. … Content Standards Semantics Technical Standards Therapeutic Areas /

  4. CDISC A business case by Gartner and CDISC

  5. SAS response PROC CDISC : SAS first attempt to support CDISC standards • SAS Clinical Standards Toolkit • SAS Clinical Data Integration, SAS Drug Development

  6. SAS Clinical Research information flow Dictionary coding (TMS) External metadata (RDF, OWL, etc.) Submission data sets EDC (Rave) Adapters / Interfaces Adapters / Interfaces Adapters / Interfaces EDC (Other) Tables, figures and listings SAS Drug Development SDTM ADaM Others SAS Clinical Data Integration ePRO and others Metadata, integration and standardization management Data and analytics platform Metadata Pooled analyses Internal systems SAS Visual Analytics JMP Clinical Labs and other external sources Raw data Transparency initiatives Patient Profiles/ Medical Review Exploration across and beyond trials Raw data Real-world data

  7. PROC CDISC Still supported in SAS 9.4, but stable Support for reading ODM 1.2 and SDTM 3.1 Not flexible enough for custom domains, or for changing standard domains. No library concept – everything built-in in code Advise against deployment and replace by novel SAS technologies

  8. SAS CST SAS Clinical Standards Toolkit The SAS Clinical Standards Toolkit (SAS CST) provides SAS implementation of evolving clinical standards and provide a framework that exploits these standards to meet common clinical research analysis and submission requirements. SAS CST provides support both for CDISC and non-CDISC general clinical standards Support for SAS table and XML files Some Java and XLST inside to manage XML files. SAS Clinical Standards Toolkit 1.6 : released February 2014 based on SAS 9.4

  9. SAS CDI SAS Clinical Data Integration Is targeted for both SAS programmers and clinical data managers SAS Clinical Standards Toolkit “under the hood” SAS Clinical Data Integration capabilities now integrated in SAS Drug Development with code that is generated in SAS CDI can be executed straight from SAS Drug Development • SAS Clinical Data Integration is a data transformation solution designed to help companies organize, standardize and manage their clinical research data and metadata. The solution enables companies to • Integrate data from disparate sources • Integration with EDC systems, e.g. Medidata Rave • Standardize their in-process data to industry models • Migrate legacy data to modern standard models • Leverage standardized data to efficiently prepare data for analysis and submission to regulatory authorities.

  10. SAS Life Science Analytics Framework Data Capture to Data Analysis CONVERSION Compound Info Life Cycle REPOSITORY Protocol Design EDC/CDMS Detailed Data Store, Metadata Store Data Quality Service

  11. SAS Life Science Analytics Framework A new Framework for clinical trial analytics • Primary Platform • Shared repository • Single identity • Partner collaboration • Licensing • Hosting model • Access & audit trail

  12. SAS & CDISC End-To-End in CDISC

  13. SAS & CDISC End-To-End in CDISC : SAS CST 1.6 and SAS CDI 2.5

  14. Define.xml Round Trip • Sponsor • Compares results to study specifications • Sponsor • Creates define.xml based on study specifications DEFINE.XML • Data Management Team(CRO) • Extracts metadata from define.xml file • Sponsor • Extracts metadata from implemented define.xml file • Data Management Team(CRO) • Produces define.xml based on implementation • Data Management Team(CRO) • Implements and populates domains

  15. Reading the Define.xml SAS Clinical Standards Toolkit Source_*.sas7bdat DEFINE.XML %crtdds_read %sdtmutil_createSrc Meta From CRTDDS %cstutil_create Tables From Metadata zero observation Domain data sets %sdtmutil_ Create Formats From CRTDDS Code List SAS Format Catalog SAS representation of CRT-DDS

  16. Reading Thedefine.xml SAS Clinical Data Integration

  17. CDI 2.4 ADaM Support

  18. CDI 2.4 Bulk Metadata Manipulation

  19. Goal SAS provides you with a complete technology and solution framework, not just to use CDISC standards, but to manage and generate clinical standards data with the aim to visualize, analyze, submit, and ensure high quality-clinical data

  20. Visualization