A Coherent and Practical End-to-End Metadata Strategy using Existing Standards and Tools for Clinical Research Stephane AUGER Danone Research, FRANCE

Clinical studies performed in 4 divisions Historically 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 Today i’d like to share with you the results of a project that we’ve had ongoing now for almost 3 years @ Danone Research on implementing a metadata strategy for our clinical studies. …and today i’m going to focus on the metadata strategy that we’ve put in place in our Dariy and Waters divisions.

“First, we need to get more control over our clinical study metadata” 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 And so this metadata strategy project began in 2010 when I received a request from my…. …and what I told them at the time was that we were nowhere near ready to implement a DW. And that a DW was the End-Result of a project that begins with getting …… …and so we launched this project with a few things in mind…..

Key Decision #1: Metadata Standards Management (1) Implementation of a Study Metadata Modeler (SMM) … with a duel use 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 The first key decision that we made is this project was to implement a SMM, …..and the 1st thing that this tool allows us to do is… The tool really provides us with an environment where we can define and manage all of our metadata standards for our CRF moduels Not so easy to do – need to plan for multiple EDCs and limitations of those EDCs – vertical vs. horizontal structure. Eg of Vital Signs

Key Decision #1: Metadata Standards Management (2) Implementation of a Study Metadata Modeler (SMM) … with a duel use 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 The 2nd thing that this tool allows us to do, is to capitalize on our metadata standards library to create a study-specific CRF in a non-programming environment. …and really, the key point here is that.. …we are able to export, from the SMM, the study-specific CRF metadata in ODM format …..which we can later exploit by an EDC tool….which of course needs to be ODM compatible

SMM EDC SMM Functionality CRF DB Structure Simple Edit Checks Workflow Config. ODM DB Structure Complex Edit Checks Simple Edit Checks Database Admin. ODM Visit Layout IWRS Coding TSDV 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 ..Some of the return-on-experience from this phase of the project: We created workgroups in order to define our company-standard CRF forms and variables… with representation from each group of internal stakeholders. With respect to defining the standard DB structure, this part was a little more tricky, and we really relied on our SMM vendor and their experience with different EDC systems, and each of their unique ways of handling data. and this was key, because we wanted ONE standards library to be as flexible as possible

Key Decision #2: ODM-Compliant EDC (1) Implementation of ODM-compliant EDC tool(s) ODM-in Import Study-Specific CRF metadata - ODM file ODM-out Export study metadata & study data in ODM The 2nd Key Decision that we made in this project (as you can guess)– was to select an EDC tool that was ODM compliant. Now i’m not going to get into the debate today of what ODM compliance means - as they only gave me 20 minutes to talk But, generally, the two main things that were looking for was that the EDC could: import our study specific CRF metadata to facilitate the study build …and that we could also Export the study metadata as well as the actual clinical study data

Study Set-up: What’s left to do? SMM EDC CRF Workflow Config. Visit Layout ODM Complex Edit Checks Simple Edit Checks Database Admin. ODM DB Structure So, what parts of the EDC study set-up are still left to configure once we’ve imported our metadata from the SMM? So, highlighted in yellow here are the tasks that still need to be configured in the EDC tool itself before study launch. Medical Coding 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 Our return-on-experience from this phase of the project: As you can imagine, there were …… especially considering that we were implementing After our test phase and our first two implementations, we’ve estimated that…..

Key Decision #2: ODM-Compliant EDC (3) Implementation Experience (2) Impact on EDC budget? 75% decrease in professional service costs 62% decrease in overall EDC budget 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) Database & EDC Set-up CRF = EDC Set-up Reduced Programing Reduced Validation Metadata Control Standardization Efficiency Warehouse-ready data As we are in our 1st few studies with this implementation – we will get a better with the next few studies exactly how the FTEs will be affected, but for the first few studies – no change .so not in the # of man days, but in the time interval from Protocol to EDC Go-Live ..and what are we getting for this 20%

Roles and Responsibilities EDC Vendor CRO Complex Edit Checks Hosting & Support SMM CRF & Study Build Validation Danone (Data Manager) Custom Config. / Reports Workflow Config. In-Study DM Database Admin. EDC ODM In Database Lock Study-Specific validation is greatly reduced since standards are used from the beginning.

Key Decision #3: ODM-Compliant Mapping Tool SMM EDC ?? Study Metadata Standards ODM ODM Study Build ODM

Key Decision #3: ODM-Compliant Mapping Tool Implementation of ODM-compliant Mapping (ETL) tool Maps ODM (from the EDC) to produce: SAS transport datasets (SDTM format) Define.xml Standardized ODM Standard Mapping Metadata Re-Usable mapping scripts Validation = only once

Key Decision #3: ODM-Compliant Mapping Tool EDC a ETL Mapping Tool Data Repository? ODM SAS Datasets Define.xml EDC b ODM ODM

Clinical Study Data & Metadata Flow: Tools Build Conduct Exploit METADATA Metadata Standards & Study Set-up (Formedix) METADATA + STUDY DATA Data Collection (EDC) (Medidata RAVE OpenClinica) Mapping (XML4Pharma) Data Repository

Clinical Study Data & Metadata Flow: Management Build Conduct Exploit METADATA Metadata Standards & Study Set-up (Formedix) METADATA + STUDY DATA Data Collection (EDC) (Medidata RAVE OpenClinica) Mapping (XML4Pharma) Metadata Standards & Management Data Repository

Clinical Study Data & Metadata Flow: Standards Build Conduct Exploit METADATA Metadata Standards & Study Set-up (Formedix) METADATA + STUDY DATA Data Collection (EDC) (Medidata RAVE OpenClinica) SDTM/CDASH Mapping (XML4Pharma) SDTM Data Repository Define.xml ODM

End-to-End metadata standardization and control is possible 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

Thank You!