ready to adopt the regulatory cdisc standards?...catalog!!!cdisc!in!the!data submission!framework!...
TRANSCRIPT
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www.cytel.com - Ready to adopt the regulatory CDISC Standards? 1
Angelo Tinazzi, Cytel Inc. Geneva – Switzerland
WEBINAR
Ready to Adopt the Regulatory CDISC Standards?
Decisions for Your Next Clinical Trial April 12th, 2018
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CONTENTS Introduction
History and Ra-onale The Concept of Standard Catalog CDISC in the Data Submission Framework More Standard Requirements
Planning Ahead Mee-ng with the « Agency » Study Data Standardiza-on Plan Test Your Submission
Challenges and Success Factors Timing « Make » the reviewer happy Do not loose the control of your data Transparency
Conclusions References
New regulatory expecta-ons are taking shape, including the need for interac-ve and transparent data handling, increased safety data demands and electronic data (CDISC) submission. Clinical trial sponsors must carefully plan their data consolida-on and analysis strategies not only in prepara-on for CDISC-‐compliant submissions, but to respond to market influences and evolving clinical partnership models.
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Introduction History and Ra-onale (FDA). The Concept of Standard Catalog. CDISC in the Data Submission Framework. More Standard Requirements.
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INTRODUCTION: HISTORY AND RATIONALE - FDA
1980s 1980s
FDA Clinical Sta7s7cal Sec7ons
SAS Datasets or ASCII
1999
FDA Support for SAS xpt
CDISC-‐FDA Collabora7on
2012
FDASIA PDUFA V
2014 ---24 Months Later
Final 754(a) Guidance Final eStudy Data Guidance Tech Conformance Guide
Dec 2016
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INTRODUCTION: HISTORY AND RATIONALE - FDA
Final 754(a) Guidance Electronic submission
Final eStudy Data Guidance Use of Standards
Tech Conformance Guide Technical Details
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INTRODUCTION: THE CONCEPT OF STANDARD CATALOG - FDA
Data Exchange Standards
https://www.fda.gov/ForIndustry/DataStandards/StudyDataStandards/default.htm
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https://www.fda.gov/ForIndustry/DataStandards/StudyDataStandards/default.htm
Terminology Standards
INTRODUCTION: THE CONCEPT OF STANDARD CATALOG - FDA
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INTRODUCTION: CDISC IN THE DATA SUBMISSION FRAMEWORK
More standards requirements to
consider. See backup slides
CDISC in the eCTD Folders.
See backup slides
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Planning Ahead Mee-ng with the Agency. Study Data Standardiza-on Plan. Take advantage of the “regulatory” availability: test your submission.
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PLANNING AHEAD
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PLANNING AHEAD: MEETING WITH THE « AGENCY » - Example the PRE-NDA MEETING - FDA The objec-ve of this mee-ng is to obtain guidance on certain aspects of the Sponsor’s plans for NDA submission. Specifically, the Sponsor seeks agreement related to ac-vi-es that must be undertaken prior to the final submission
Does the FDA agree with the Sponsor’s plan regarding the composi7on and format of the clinical data submission for the XXXXXXX eCTD NDA? Do not use «Open Ques-on», always propose solu7ons and ask for confirma-on
Formal Mee-ngs between the FDA and Sponsors or Applicants of PDUFA Products (dra^) https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM590547.pdf
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PLANNING AHEAD: STUDY DATA STANDARDIZATION PLAN (SDP) - FDA
• Expected at the End-‐of-‐Phase 2, if not earlier (pre-‐IND stage) • Issuing and Maintaining the SDSP • Requested in the FDA Data Technical Conformance Guide • Content
o Basic introductory informa-on about the plan o List of non-‐clinical and clinical studies and associated standards o Documenta-on of any FDA standards discussions, and references o An-cipate pooling strategy
! The sponsor (regulatory) is the owner but CRO can help
hRp://www.phusewiki.org/wiki/index.php?7tle=Study_Data_Standardiza7on_Plan_%28SDSP%29
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PLANNING AHEAD: STUDY DATA STANDARDIZATION PLAN - FDA
STUDY AND DATA STANDARDS INVENTORY
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PLANNING AHEAD: STUDY DATA STANDARDIZATION PLAN - FDA
ANTICIPATING THE POOLING STRATEGY – AN EXAMPLE For this updated Integrated Summary of Safety (ISS), the integrated ADaM datasets will be generated by pooling the NEW Study ADaM datasets with the ADaM datasets used to support the integrated safety analyses for the approved NDA XXXXXX, and it will follow the ADaM implementa-on guide 1.1. Given the fact the original ISS integrated ADaM datasets were created from SDTM Ig 3.1.2 datasets with CDISC Terminology YYYY-‐MM-‐DD, and because the original ISS ADaM datasets were following ADaM Ig 1.0, an assessment of key changes in new versions of both data standards and terminology will be made; as such in the new integrated ISS ADaM datasets key ‘up-‐version’ will be made directly in the integrated ADaM datasets, therefore original SDTM datasets submihed for XXXXX NDA will be not modified. An example of possible changes is CDISC CT term no longer exis-ng in the most recent CDISC CT terminology (e.g. ECG parameter).
Across all studies, the adverse events pooled in the integrated ADaM adverse events datasets, will be coded using a single version of the Medical Dic7onary for Regulatory Ac7vi7es (MedDRA) and concomitant medica-ons pooled in the integrated ADaM concomitant medica-ons datasets will be coded using a single version of the World Health Organiza-on -‐ Drug
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PLANNING AHEAD: TEST YOUR SUBMISSION
• Technical ques-ons (i.e. CDISC) sent via email to the eData Group ([email protected])
• Test submission with one study (full eCTD package)
o SDTM and ADaM datasets o Choose a “Tricky” study e.g.
extension study o Good Technical Feedback and
Advice
hRps://www.fda.gov/Drugs/DevelopmentApprovalProcess/FormsSubmissionRequirements/ElectronicSubmissions/ucm174459.htm cder-‐[email protected] or [email protected]
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Challenges and Success Factors Timing. “Make” the Reviewer happy. Do not loose the control of your data. Transparency.
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CHALLENGES AND SUCCESS FACTORS: TIMING • It is never too early to adopt standards. Start Now • Start with CDASH
o Adopt Standard Terminology to help restrict the « range of choice » o Clear « item wording » o Smooth transi-on to SDTM then to ADaM
o 67% of CDASH v2.0 maps directly to SDTM IG variables* o 86% of CDASH maps directly with standard mapping included (e.g. dates) *
* «SDTM vs CDASH: Why You Need Both » Kit Howard, Shannon Labout, CDISC. Presented at PhUSE 2017 (hhps://www.cdisc.org/system/files/all/CDISC_SDTM_and_CDASH_You_Need_Both.pdf)
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CHALLENGES AND SUCCESS FACTORS: TIMING
• Adop-ng standards retrospec-vely (legacy data migra-on) might pose « severe » traceability issues o Following standard recommenda-ons from the beginning « could » help in making
sure you collect everything you need e.g. Seriousness Adverse Event Criteria " almost impossible to collect them retrospec-vely
o Risk not gerng the same results o Traceability if « lost » can compromise or delay the submission -meline
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CHALLENGES AND SUCCESS FACTORS: TIMING – THE RISK WHEN STARTING LATE Retrospec7ve Terminology Adop7on*
Mapping to CDISC (NCI) Controlled Terminology -‐ e.g. Concomitant Medica-ons Route
Source CDISC/NCI CT
INFUSION PARENTERAL Administra-on by injec-on, infusion, or implanta-on
MOUTH/THROAT ORAL Administra-on to or by way of the mouth
TOPICAL-‐EYE OPHTHALMIC
TOPICAL PO TOPICAL
184 unique terms translated to 25 unique terms in CDISC Controlled Terminology
* Looking for SDTM migra-on specialist. A. Tinazzi. PhUSE 2015
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CHALLENGES AND SUCCESS FACTORS: TIMING – THE RISK WHEN STARTING LATE Retrospec7ve Migra7on from Legacy Data to SDTM*
* Looking for SDTM migra-on specialist. A. Tinazzi. PhUSE 2015
SDTM Raw Datasets
AE AE AEAER
CM CMCMR CMPRIOR PRAML BPP
DM DEMO SCEL DS
DS DEMO DS RD ET
EX IFVPR IFCRE
IE IE (only violated criteria)
MH MH CH PSC DX
VS VS PMBSA
…….
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CHALLENGES AND SUCCESS FACTORS: TIMING – THE RISK WHEN STARTING LATE Lost in Traceability Provide a clear , traceable pathway from the primary collec-on documents (e.g. CRF, Diary, External Data) to the raw datasets (SDTM) to the analysis datasets (ADaM)* to your TFL (Table Figures and Lis-ngs) to your CSR (Clinical Study Report)
Data Collection
SDTM
ADaM
TFLs / CSR
What you « try » to achieve /submit
* Optimizing Your Study Data Submissions to FDA – Updates from CDER and CBER, July 2017, http://sbiaevents.com/files/study-data-071217.pdf
Data Collection
Analysis Datasets
TLFs CSR
In reality
X
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CHALLENGES AND SUCCESS FACTORS: « MAKE » THE REVIEWER HAPPY
• Current Standards do not cover all possible medical « situa-ons »
• Regulatory might ask for something different or for something more (e.g. FDA Study Data Technical Conformance Guide) o Flagging Treatment Emergent Adverse Event is not an SDTM requirement*
o Preferences for Laboratory Standard Units might differ across regulatory agencies e.g. FDA vs PMDA " « worldwide » standardiza-on is an ongoing effort
" More examples in the Backup-‐Slides
* FDA requirement seems not applicable anymore from recent Study Data Technical Conformance Guide
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CHALLENGES AND SUCCESS FACTORS: DO NOT LOOSE THE CONTROL OF YOUR DATA • Make sure your partners, both internal and external, understand standard
requirements
• When outsourcing to mul-ple CROs make sure they (and you) ‘do standards’ consistently o Proper use of Controlled Terminology o Conven-ons maintained across studies
• Implement Proper Surveillance
• « Choose » and do not let the « others » choose for you o Develop your own understanding of the standards o Put in place a standard governance process in your company
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CHALLENGES AND SUCCESS FACTORS: TRANSPARENCY • Data and Standards are not perfect
• Validate your data prior to submit o Correct or
o Document (Explain if issues could be not corrected) Make appropriate use of the Reviewer Guide* (for SDTM and for ADaM)
* hhp://www.phusewiki.org/wiki/index.php?-tle=Analysis_Data_Reviewer%27s_Guide and hhp://www.phusewiki.org/wiki/index.php?-tle=Study_Data_Reviewer%27s_Guide
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CHALLENGES AND SUCCESS FACTORS: TRANSPARENCY These are not good explana-ons See also « The Most Common Issues in Submission Data» PharmaSUG 2015 (hhps://www.pharmasug.org/proceedings/2015/SS/PharmaSUG-‐2015-‐SS06.pdf )
Please Fix them !
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CHALLENGES AND SUCCESS FACTORS: TRANSPARENCY Do not hide « changes »
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Conclusions
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CONCLUSIONS: A FINAL SPECIAL DISCLAIMER
• The content of this presentation represents our personal submission experience with “our” sponsors on specific indications
• Although some of the slides contain information coming from existing requirements, such as CDISC standards and FDA guidance, they represent our experience of applying standards and interacting with the FDA
• Topic and timing of submission, as well as reviewer “preferences”, are important factors to consider when submitting data to FDA
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CONCLUSIONS
• Standards are « facilitators » o Ini-al Investment … o … but long-‐term « stability » and more streamlined process o Improve and make faster the review process
• Make use of CDISC Therapeu-c Area User Guide
• Stay tuned: standards and regulatory requirements are evolving rapidly
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CONCLUSIONS: REFERENCES - CDISC
• Accessing CDISC Standards www.cdisc.org • CDISC Discussion Forum www.cdisc.org/forum • NCI EVS Controlled Terminology
www.cancer.gov/cancertopics/terminologyresources/CDISC
• Pinnacle 21 Forum hhps://www.pinnacle21.com/forum • Linkedin Forum
o Official CDISC Forum hRps://www.linkedin.com/groups/56393 o CDISC Advocates hRps://www.linkedin.com/groups/107674 o CDISC SDTM Experts hRps://www.linkedin.com/groups/2758697
o CDISC ADaM hRps://www.linkedin.com/groups/3092582 o CDISC define.xml hRps://www.linkedin.com/groups/4975366
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CONCLUSIONS: REFERENCES - PhUSE
PhUSE Working Groups hhp://www.phuse.eu/op-mizing-‐data-‐standards Op-mizing the Use of Data Standards ! Analysis Data Reviewer’s Guide (ADRG) ! Study Data Reviewers Guide (SDRG) ! Nonclinical SDRG Package ! Best Prac-ces for Data Collec-on Instruc-ons ! Best Prac-ces for Metadata Documenta-on ! Clinical Legacy Data Conversion Plan & Report ! Data Reviewer’s Guide in XML ! Define-‐XML V2.0 Comple-on Guidelines & Style Sheet Recommenda-ons ! Pooling WHO Drug B3 Format ! SDTM ADaM Implementa-on FAQ ! Standardizing Data Within the Inspec-on Site Selec-on Process ! Study Data Standardiza-on Plan (SDSP)
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CONCLUSIONS: REFERENCES: REGULATORY FDA AND PMDA
• Study Data for Submission to CDER and CBER hhps://www.fda.gov/Drugs/DevelopmentApprovalProcess/FormsSubmissionRequirements/ElectronicSubmissions/ucm248635.htm
• Check for FDA regular events/webinar hhp://sbiaevents.com/
o Op-mizing Your Study Data Submissions to FDA – Updates from CDER and CBER, July 2017 hhp://sbiaevents.com/files/study-‐data-‐071217.pdf
• PMDA Advanced Review with Electronic Data Promo-on Group hhps://www.pmda.go.jp/english/review-‐services/reviews/advanced-‐efforts/0002.html
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Back-up Slides
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INTRODUCTION: MORE « STANDARD » REQUIREMENTS
FDA Portable Document Format (PDF) Specifica7ons • Use of fonts, colors • PDF proper-es
eCTD Specifica7ons
• Specific folder loca-on for your study data • Valida-on Criteria e.g. Filename
o lowercase, lehers, digits and ‘-‐’ (hyphen)
o Max 64 chars
Technical Rejec7on Criteria e.g. what is « mandatory »
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« WORLDWIDE » REGULATORY DATA SUBMISSION REQUIREMENTS
Country/Region Data Submission Requirements
US (FDA) ! Data Packages required ! CDISC required for studies star-ng a^er 2016-‐12-‐17 ! Trial Summary (SDTM .TS) required for all studies (including legacy)
Japan (PMDA) ! Data packages currently not required ! CDISC data packages required for submissions on/a^er 2020-‐04-‐01, but sponsor are
already encouraged to submit data using CDISC standards (PMDA-‐Pilot Phase)
EU (EMA) Under Review, but no other standards will be endorsed when data submission will be required
China (China-‐FDA) ! Data packages currently not required. They have endorsed CDISC ! They requested CDISC data packages for some submissions
Canada ! Data packages currently not required. No CDISC requirement yet ! They requested CDISC data packages for some submissions
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REGULATORY REQUIREMENTS (FDA): CDISC IN THE eCTD STRUCTURE
A standard format for transferring submissions to regulatory agencies (e.g. Folder structure)
Developed by Interna-onal Council for
Harmoniza-on (ICH)
Used in US, Japan, EU, and other
countries
The CTD is organized into five modules
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REGULATORY REQUIREMENTS (FDA): CDISC IN THE eCTD STRUCTURE
Electronic Common Technical Document Specifica7ons hhp://estri.ich.org/eCTD/eCTD_Specifica-on_v3_2_2.pdf
FDA Data Technical Conformance Guide hhp://www.fda.gov/downloads/ForIndustry/DataStandards/StudyDataStandards/UCM384744.pdf
ADaM Analysis Datasets and Programs
Non ADaM Analysis Datasets and Programs
Non-‐SDTM Tabula-on Datasets
SDTM Tabula-on Datasets
Other datasets i.e. look-‐up datasets
ISS/ISE Pooling Folders
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CHALLENGES AND SUCCESS FACTORS: « MAKE » THE REVIEWER HAPPY
More requirements from the FDA Study Data Technical Conformance Guide • USUBJID/SUBJID for subjects par-cipa-ng to mul-ple studies • Adjudica-on Data • Death date in SDTM DS-‐Disposi-on • How to handle logically skipped ques-on in SDTM QS-‐Ques-onnaires • EPOCH for clinical subject data • ADaM recommenda-ons • TS Mandatory for legacy studies
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CHALLENGES AND SUCCESS FACTORS: DO NOT LOOSE THE CONTROL OF YOUR DATA
Beyond the standards: «Conven-ons maintained across studies» e.g. visit numbering conven-ons
Cytel helps customers to improve clinical success rates via optimal study design, effective data management, and accurate statistical analysis.
Learn more at www.cytel.com/services