Standards Implementation: It Should be Simple Right? Thursday January 18, 2018

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1 Standards Implementation: It Should be Simple Right? Thursday January 18, 2018

2 Upcoming MassBio Forums January 18, 2018; 4-6pm: TODAY!! 2018 JP Morgan Recap: An Insiders View BD/Fin & EU February 1, 2018; 8-10am: NASH: A Silent Epidemic Poised to Swamp the BioPharma Industry? DD February 28, 2018; 9-11am: RARE DISEASE DAY FORUM: Shortening the Diagnostic Journey for Children with Rare Diseases L&R

3 Who is in our audience today? In a show of hands

4 What are we talking about? Definitions of Standard Something considered by an authority or by general consent as a basis of comparison; an approved model An object that is regarded as the usual or most common size or form of its kind An average or normal requirement, quality, quantity, level, grade,etc.

5 What are we talking about? Clinical Data Interchange Standards Consortium (CDISC) develops data standards, such as SDTM, ADaM, and CDASH, that enable information system interoperability to improve medical research and related areas of healthcare SDTM Study Data Tabulation Model: The content and tabulation standard for regulatory submission of case report form data tabulations in clinical research studies. CDASH - Clinical Data Acquisition Standards Harmonization Pinnacle21 report - Software, Pinnacle 21 Enterprise (used at FDA under the name DataFit ), which provides biopharmaceuticals a means to test if their submission data is compliant (formerly known as OpenCDISC) Domain- a collection of observations (data) with a common topic Define.xml a document that describes the structure and contents of the data collected during the clinical trial process Controlled terminology - the set of CDISC-developed or CDISC-adopted standard expressions (values) used with data items within CDISC-defined datasets ADaM - Analysis Data Model: The content standard for regulatory submission of analysis datasets and associated files

6 Why would we do it What are the Pros of using standards? Company Department External to company Reduce resource Increase Morale Messaging/reporting simpler Consistency beyond just CRFs / SDTMs Flexibility of assigning resources (Anyone can work on anything) Easier to Validateusing standard tools Consistency is presented to external partners External Partners can build Efficiency into their process

7 Do we have to do it??? Similar to wearing a seat belt in Massachusetts- It is a good practice to do but it is also the law

8 Agenda How to Implement Standards What is the CRO perspective to implementation What is the Sponsor perspective What is needed for a submission Legacy studies versus standard submissions Where will the standards be going next

9 Standards Implementation: It Should be Simple Right? Speakers: Susan Boquist, Associate Director, Statistical Programming, PROMETRIKA, LLC Wendy Mangels, Associate Director, Clinical Data Management, Vertex Pharmaceuticals. Brian Conley, Associate Director, Statistical Programming and Data Management, Clementia Pharmaceuticals Inc. Moderator: Michelle Harrison, Associate Director, Clinical Data Management at Vertex Pharmaceuticals.

10 Making Standard (e)crfs Work Wendy Mangels 18JAN Vertex Pharmaceuticals Incorporated

11 Who Clinical Data Standards Committee Develops and reviews standard (e)crfs, edit checks, CRF Completion Guidelines, external data transfer specs Approves/rejects requests for nonadherence to standards Biostatistics Clinical Operations Clinical Pharmacology Data Management Global Patient Safety Medical Directors Medical Writing Statistical Programming Liaisons from Biomarkers and Regulatory, as needed Steering Committee Approves standards for use Sets expectations that dept follows standards Adjudicates requests for nonadherence which Standards Committee cannot resolve Department heads from functions on Standards Committee Vertex Pharmaceuticals Incorporated

12 What Our standard (e)crf is a Word document right now applies to paper or electronic CRFs platform-independent room for instructions Vertex Pharmaceuticals Incorporated

13 Our Experience with CDASH We rolled out our first standard (e)crfs in 2009 When CDASH 1.0 was released in 2008, we didn t feel it had the same level of maturity as a standard as SDTM or ADaM did Question phrasing can be clunky ( Indicate if ECG was performed ) In many cases, SDTM presents multiple options, but CDASH has one right way Nowhere to put some of the data we collect There seems to be a lag between SDTM releases and relevant CDASH standards Our chosen path involves SDTM-like data collection, rather than CDASH Vertex Pharmaceuticals Incorporated

14 CDISC SDTM Compliance We maintain CDISC-friendly standards Dataset names are SDTM domain names (AE, DM, etc.) SDTM variable names (whenever practical - e.g., flat forms) SDTM Terminology (whenever practical) We don t use a normalized Vital Signs structure in the ecrf, but we make it easy to transpose the data. The variable names (HEIGHT, TEMP, etc.) are the SDTM Vital Signs Test Code (VSTESTCD) Vertex Pharmaceuticals Incorporated

15 Compliance Encouragement Opportunity for input (at our company and at partners) Training Flexibility - standards need to work in actual studies (multiple study drugs, pediatric trials, oncology, ) FAQ document with pre-approved changes Electronic system for requesting non-adherence, or new/modified standards Multiple versions of appropriate (e)crfs Enforcement Department heads approve standards Independent QC Checks of all (e)crfs to ensure standards used correctly Vertex Pharmaceuticals Incorporated

16 Encouraging Compliance: Color-coded FAQs Preapproved Changes NOT Changes Not Change Preapproved Recommended Needs CDSC Review 16 Commonly requested preapproved changes Submit a CDSC request Save time these requests are unlikely to be approved

17 Encouraging Compliance FAQ document with pre-approved changes Vertex Pharmaceuticals Incorporated

18 Encouraging Compliance Electronic system to request non-adherence or modifications (SharePoint list with workflows) Hera Xiao Study XYZ Vertex Pharmaceuticals Incorporated

19 Innovative Clinical Development Solutions

20 Implementation Successes and Challenges from a CRO Perspective Susan Boquist MassBio January 18, 2018

21 CRO Implementation Challenges Misconceptions on the meaning of Standard Sponsors have different flavors of SDTM Sponsors that are overly involved or absent No control on source or content of raw data Late notice of concurrent mapping by other groups Scope creep 21

22 CRO Implementation Successes Clear understanding of the path forward External edc built predictably Efficiencies of code for known data mapping Downstream efficiencies in analysis Resourcing flexibility Cost savings 22

23 CONFIDENTIAL SDTM Challenges From Sponsor Perspective Brian Conley January 18, 2018 CONFIDENTIAL 23

24 Sponsor s Perspective CONFIDENTIAL Communication is important Sponsors need to participate in implementing their standards Encourage CDISC interest in sponsor organization

25 Communication Lessons Learned CONFIDENTIAL Incorrect (old) version of Pinnacle21 is run Vendor set the validation version at the beginning of the study and does not want to fix newly uncovered issues which may have been hidden in an old Pinnacle21 version After many rounds of updates, Issue Log becomes hard to follow Agree on a naming convention, prefer to use date in filename Use the same format Does CRO respond adding columns to the right, or start new rows below the issue? Do not only send issues as s Sometimes ing screenshots along with the spreadsheet helps acrf planned to be completed at the end of the study. Our preference is for creating the acrf before beginning the SDTM programming

26 CONFIDENTIAL Sponsor Participation at Study Startup SDTM Implementation should begin with database development Sponsors are typically closer to database development than SDTM group at vendor SDTM team may be at a different CRO than the Data Managers CRF review is critical time to align with CDISC standards Every field on the CRF should have a home in SDTM Controlled Terminology will come back to haunt you Have internal discussions on whether to be consistent with earlier studies, or fix things in new study Hospitalization events were in custom domain in previous studies, use HO for new study? AEOUT terms do not follow Controlled Terminology 26

27 Sponsor Participation at Study Startup CONFIDENTIAL Provide CRO with as much of the mapping details as possible --TEST/--TESTCDs used in previous studies Custom domains Lab Conversion factors Therapeutic Area User Guide (TAUG) references acrf? 27

28 CONFIDENTIAL Encourage CDISC Interest When CRO delivers SDTM data to the Sponsor, who reviews? At smaller sponsor companies, might be only one person How can we expand CDISC knowledge at our company? Keep an eye out for PhUSE Single Day Events (in Boston April 26 th, 2018!), local PharmaSUG, Boston Area SAS Users Group (BASUG), MassBIO meetings Become a CDISC Member In the Member s Only area of CDISC.org: 28

29 CONFIDENTIAL Legacy Data Submission CONFIDENTIAL

30 CONFIDENTIAL FDA Study Data Technical Conformance Guide dydatastandards/ucm pdf Legacy Data Conversion Plan and Report Sponsors should evaluate the decision involved in converting previously collected nonstandardized data (i.e., legacy study data) to standardized data (i.e., SDTM, and ADaM). Sponsors should provide the explanation and rationale for the study data conversion in the RG. To mitigate traceability issues when converting legacy data, FDA recommends the following procedures: 1. Prepare and Submit a Legacy Data Conversion Plan and Report. 2. Provide an acrf, for clinical data, that maps the legacy data elements. 3. Record significant data issues, clarifications, explanations of traceability, and adjudications in the RG. 4. Legacy data (i.e., legacy acrf, legacy tabulation data, and legacy analysis data) may be needed in addition to the converted data.

31 CONFIDENTIAL Is Legacy Data Submittable Legacy data should be submitted as SAS V5 Transport files Specifications are specified in the Study Data Specifications document on the FDA website tudydatastandards/ucm pdf For an individual study, all dataset names and dataset labels should be unique across both the analysis and tabulation datasets submitted for an individual study. The internal name for an analysis dataset should be the same as the name shown in the data definition file.

32 CONFIDENTIAL Is Legacy Data Submittable (Continued) Variable names may need to be resized: Element Maximum Length in Characters Variable Name 8 Variable Descriptive Label 40 Dataset Label 40 The key variables (e.g., subject identifier and visit for datasets with multiple records per subject) should appear first in the datasets. Each subject should be identified by a single, unique subject identifier within an entire application (including tabulation, listing and analysis datasets). Subjects enrolled in a primary study and then followed into an extension study should retain their unique identifier from the primary study.

33 CONFIDENTIAL acrf for Legacy Data FDA requests that sponsors provide two versions of the annotated CRF One based on Legacy Data One based on SDTM Data The Legacy CRF should include all versions and all forms

34 CONFIDENTIAL Define.pdf for Legacy Data See Section in Study Data Specifications document For datasets not prepared using CDISC specifications, sponsors should include a define.pdf to describe the datasets for each study Also provide definitions of each variable First page should list a table of all datasets, with description and location There should be a hyperlink from this first page to the dataset within the define.pdf Also hyperlink to the SAS XPT file

35 Future of CDISC Susan Boquist MassBio January 18, 2018

36 What CDISC Members are Saying Make documentation easier to use Make it easier to volunteer Resolve the inconsistencies When is the next version getting published? What are you working on? HELP! 36

37 What CDISC is Doing More support for volunteers Improved standards development process Accredited training program 37

38 More Support for Volunteers Consistent onboarding and training Set clear expectations Hours tracking and succession planning CDISC Staff support for foundational teams 38

39 Improved Standards Development Procedure Global Governance Group (GGG) implementation Wiki collaboration space: wiki.cdisc.org CRF Maker SDS Maker Jira issue tracking: JIRA.cdisc.org 39

40 Accredited Training CDISC Education recently received accreditation from the International Association of Continuing Education and Training (IACET) Independent assessment and confirmation of a high quality, well controlled training program 40

41 What s Coming Predictable release schedule New publishing formats Transparency and Predictability Future CDISC Standards 41

42 Predictable Release Schedule (1) Early notice of expected product releases each year Quarterly Controlled Terminology (CT) releases Ad hoc TA User Guide releases with Provisional status Annual Foundational Standards release (first week of November) For standards with finalized components by cut-off date Provisional standards with all content finalized by cut-off date also gain Final status 42

43 Predictable Release Schedule (2) Final now means: Public review completed on: Normative standard Informative examples & text Conformance Rules Controlled terminology Publication-ready updates made Metadata in CDISC SHARE Education components developed 43

44 New Publishing Formats Piloted the release of their first HTML standard CDASHIG v2.0 CDASH Model v1.0 Benefits Much shorter publication time More universally readable than PDF But you can export a PDF if you want one, or save the HTML file for offline use 44

45 Transparency and Predictability Pipeline Volunteer View Wiki Public View Website List of Draft Domains - Website 45

46 Future of CDISC Standards (1) Refine the standards to build more support for new technologies Connect CDASH (and SDTM) with FHIR and other healthcare standards to support esource Align SDTM Pharmacogenomics with global genomics initiatives (GA4GH, HL7 Clinical Genomics, ISA-Tab & Workflow initiatives) Provide standards in new formats (RDF) Support machine readable standards Single instance of each concept, well defined Build biomedical concept templates 46

47 Future of CDISC Standards (2) Expand use cases beyond regulatory submissions Align models with Real World Data (RWD) 47

48 Expected Results Alignment and consistency within and across models Clearly defined concepts to reduce ambiguity and help identify gaps Documented principles will guide future development Higher quality standards CDISC has been building the plane while flying it and now they need help landing it 48

49 Thank you!

50

51 Upcoming MassBio Forums January 18, 2018; 4-6pm: TODAY!! 2018 JP Morgan Recap: An Insiders View BD/Fin & EU February 1, 2018; 8-10am: NASH: A Silent Epidemic Poised to Swamp the BioPharma Industry? DD February 28, 2018; 9-11am: RARE DISEASE DAY FORUM: Shortening the Diagnostic Journey for Children with Rare Diseases L&R

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