SlideShare une entreprise Scribd logo
1  sur  34
www.cytel.com
CDISC Electronic Submission
Kevin Lee
JSM
August 6th, 2013
1
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Disclaimer
2
Any views or opinions presented in this
presentation are solely those of the author and
do not necessarily represent those of the
company.
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Why?
3
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Golden Rule by Simon Sinek
4
What
How
Why
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Agenda
5
• Why do we care CDISC electronic submission?
– Recent Regulatory changes
– FDASIA and PDUFA V
• How can we prepare CDISC electronic submission?
– eCTD version 3.2.2 and Data Standard Strategy
• What do we prepare CDISC electronic submission?
– CDISC components
– CDISC electronic submission
• Conclusion
• Questions & Answers
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Current Status of eSubmission in FDA
6
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Current Status in CDISC Submission
7
CDISC submission
• In 2010, CDER received an average of over 650
datasets/week, with 23% of active NDAs containing
CDISC/SDTM data
• In 2011 this number has increased to an average 39%
in SDTM and 32% in ADaM
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Significant Regulatory Changes
8
FDA Safety and Innovation Act
(FDASIA)
• signed into law on July 9, 2012.
• expands the FDA’s authorities and
strengthens the agency's ability to
safeguard and advance public
health.
• Main impacts for us - reauthorizes
the fifth instance of Prescription
Drug User Fee Act (PDUFA V)
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
PDUFA V commitment by FDASIA
9
• Provides FDA with the necessary resources to
maintain a predictable and efficient review process
for human drug and biologic products.
• FDA will continue to receive a source of stable and
consistent funding during fiscal years 2013-2017
that will allow the agency to fulfill its mission to
protect and promote public health by helping to
bring to market critical new medicines for patients
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
PDUFA V commitment in section 7
10
A. To enhance the quality and efficiency of FDA’s review of
NDAs, BLAs, and INDs, FDA shall consult with
stakeholders, including pharmaceutical manufacturers
and other research sponsors, to issue draft guidance on
the standards and format of electronic submission of
applications by December 31, 2012.
B. FDA will issue final guidance no later than 12 months
from the close of the public comment period on the draft
guidance. Such final guidance and any subsequent
revisions to the final guidance shall be binding on
sponsors, applicants, and manufacturers no earlier
than twenty-four months after issuance of the final
guidance.
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
PDUFA V commitment in section 7 (2)
11
C. Requirements for electronic submission shall be
phased in according to the following schedule:
1. Twenty-four (24) months after publication of the
final guidance: All new original NDA and BLA
submissions, all new NDA and BLA efficacy
supplements and amendments, all new NDA and
BLA labeling supplements and amendments, all
new manufacturing supplements and
amendments, and all other new NDA
submissions.
2. Thirty-six (36) months after publication of the
final guidance: All original commercial INDs and
amendments
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
PDUFA V commitment in section 7 (3)
12
D. ….., initial FDA guidance shall specify the format of
electronic submission of applications using eCTD version
3.2.2 unless, after notice and an opportunity for
stakeholder comment, FDA determines that another
version will provide for more efficient and effective
applicant submission or FDA review.
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
PDUFA V commitment in section 7 (4)
13
E. Clinical Terminology Standards: …., FDA shall develop
standardized clinical data terminology through open
standards development organizations (i.e., the Clinical
Data Interchange Standards Consortium (CDISC)) with
the goal of completing clinical data terminology and
detailed implementation guides by FY 2017.
1. FDA shall develop a project plan for distinct therapeutic
indications, prioritizing clinical terminology standards
development within and across review divisions.
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
More Updates from FDA on DIA 2013
14
• FDA is currently developing eCTD v 4.0.
• Implementation Target – Mandatory eCTD submission
– NDA and BLA : March 2016
– Commercial INDs : March 2017
• Based on the current implementation schedule, FDA
begins receiving eCTD v 4.0 submission in 2016
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
How do we prepare CDISC eSubmission?
15
• eCTD(Electronic Common Technical Document) v
3.2.2 for electronic submission
• Data Standard Strategy for CDISC
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Electronic Common Technical Document
16
• Introduction of eCTD – an interface for industry to
agency transfer of regulatory information
• Most recent version – v3.2.2
• Define
– Module and its contents
• Module 1 – Administrative information
• Module 2 – eCTD summary document
• Module 3 – Quality
• Module 4 – Non-clinical Study Reports
• Module 5 – Clinical Study Reports
– File formats (i.e., pdf, txt, xml, xpt and etc)
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Electronic Common Technical Document
17
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Data Standard Strategy
18
• Purpose – to reinforce CDER’s on-going commitment
to the development, implementation and maintenance
of data standard program on regulatory submissions.
• Objectives
– Development of TA standards
– Replacement of SAS XPORT files
– Requirement of eSubmission
• Data Standard
– CDER initiated 55 key TA domains
– CDISC will be implemented and enhanced to support TA
standard development
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
TA Data Standard Prioritization
19
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Data Standard Strategy
20
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
What do we prepare
for CDISC eSubmission?
21
• CDISC components
according to CDISC
compliances
• Its electronic formats
according to eCTD
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
CDISC Clinical Trial Process
22
PRN
(Protocol)
eCRF
ODM.xml, L
AB
SDTM TFLADaM
SAP
CDASH
CSR
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
CDISC components in eSubmission
23
• Protocol
• SAP
• eCRF
• SDTM
• ADaM
• SEND
• CSR
• Define.xml
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Additional components in eSubmission
24
• ADaM SAS programs
• Efficacy SAS programs (sometimes)
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Formats of files according to eCTD
25
• Protocol – pdf (i.e., study001-protocol.pdf)
• SAP – pdf (i.e., sutdy001-sap.pdf)
• eCRF – pdf (i.e., sutdy001-blankecrf.pdf)
• SDTM – xpt (i.e., dm.xpt, ae.xpt, ds.xpt, and etc)
• ADaM – xpt (i.e., adsl.xpt, adae.xpt, adtteos.xpt, and etc)
• SEND – xpt (i.e., dm.xpt, se.xpt, bw.xpt, and etc)
• CSR – pdf (i.e., sutdy001-csr.pdf)
• Define.xml – xml or pdf (i.e., define.xml/define.pdf)
• ADaM SAS programs – txt (i.e., c-adsl-sas.txt)
• Efficacy SAS programs – txt (i.e., t-14-01-001-ds-sas.txt )
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Naming convention of files
according to eCTD
26
• Lower case of letter from “a” to “z”
• Number from “0” to “9”
• “-” hypen
• No special character ( #, %, $ and etc)
• File name should be less than or equal to 64
characters including the appropriate file extension
• The length of entire path of the file should not exceed
230 characters. (m5/datasets/study001/sdtm/ae.xpt)
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
pdf file guideline according to eCTD
27
• Version – 1.4 thru 1.7 are acceptable
• Fonts
– Standard : Arial, Courier New, Times Roman
– Sizes : range from 9 to 12 point ( Times New Roman 12-point
font is recommended for narrative text )
• Page
– Print area : 8.5 inches by 11 inches
– Margin : at least ¾ inch
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
SAS xpt file guideline according to eCTD
28
• Length
– Variable length is less than or equal to 8
– Variable label is less than or equal to 40
– Dataset length is less than or equal to 8
– Dataset label is less than or equal to 40
• Dataset Size – less than 1 GB (LB1, LB2, and so on)
• The length of character variables should be minimized
(i.e., if the maximum length of USUBJID is 20 character
long, keep the length as 20, not 200)
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Module 5 CSR Reports
29
CSR, SAP, Protocol
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
CDISC Datasets eSubmission
30
ADaM datasets, Define.xml
ADaM SAS programs
SDTM
datasets, Define.xml, SDTM
annotated blank eCRF
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
CDISC compliance
31
• SEND : config-send-3.0.xml
• SDTM : config-sdtm-3.1.3.xml
• ADaM : config-adam-1.0.xml
• Define : config-define-2.0.xml
• CDISC compliance by OpenCDISC
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Conclusion
32
• Before : “should” in FDA documents means
that something is suggested or
recommended, but not required.
• After : “should” could mean required.
• CDISC electronic submission will be
mandatory sometime in 2016 or 2017.
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Contacts
33
• Email address : Kevin.lee@cytel.com
• Linkedin :
– Profile : www.linkedin.com/in/kevinlee1995/
– Group : CDISC ADaM
• Tweet : @kevinlee_pharma or @cdisc_adam
www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd.
Questions?
34

Contenu connexe

En vedette

Successful Pediatric Studies: Key Study Design and Site Selection Considerations
Successful Pediatric Studies: Key Study Design and Site Selection ConsiderationsSuccessful Pediatric Studies: Key Study Design and Site Selection Considerations
Successful Pediatric Studies: Key Study Design and Site Selection Considerationsjbarag
 
Presentation on CDISC- SDTM guidelines.
Presentation on CDISC- SDTM guidelines.Presentation on CDISC- SDTM guidelines.
Presentation on CDISC- SDTM guidelines.Khushbu Shah
 
CDISC Related Services
CDISC Related ServicesCDISC Related Services
CDISC Related ServicesIstvan Janosi
 
Data mining (DM) in the pharmaceutical industry
Data mining (DM) in the pharmaceutical industryData mining (DM) in the pharmaceutical industry
Data mining (DM) in the pharmaceutical industrylurdhu agnes
 
Trial Design Domains
Trial Design DomainsTrial Design Domains
Trial Design DomainsAnkur Sharma
 
SDTM modelling: from study protocol to SDTM-compliant datasets
SDTM modelling: from study protocol to SDTM-compliant datasets SDTM modelling: from study protocol to SDTM-compliant datasets
SDTM modelling: from study protocol to SDTM-compliant datasets Angelo Tinazzi
 
Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Ankur Khanna
 
Cdisc sdtm implementation_process _v1
Cdisc sdtm implementation_process _v1Cdisc sdtm implementation_process _v1
Cdisc sdtm implementation_process _v1ray4hz
 
Regulations for drug approval in USA, E.U & India
Regulations for drug approval in USA, E.U & IndiaRegulations for drug approval in USA, E.U & India
Regulations for drug approval in USA, E.U & IndiaDr. Pankaj Bablani
 
Regulatory agencies
Regulatory agenciesRegulatory agencies
Regulatory agenciesUrmila Aswar
 
SDTM (Study Data Tabulation Model)
SDTM (Study Data Tabulation Model)SDTM (Study Data Tabulation Model)
SDTM (Study Data Tabulation Model)SWAROOP KUMAR K
 
Clinical Data Standards and Data Portability
Clinical Data Standards and Data Portability Clinical Data Standards and Data Portability
Clinical Data Standards and Data Portability Nrip Nihalani
 

En vedette (15)

Successful Pediatric Studies: Key Study Design and Site Selection Considerations
Successful Pediatric Studies: Key Study Design and Site Selection ConsiderationsSuccessful Pediatric Studies: Key Study Design and Site Selection Considerations
Successful Pediatric Studies: Key Study Design and Site Selection Considerations
 
Presentation on CDISC- SDTM guidelines.
Presentation on CDISC- SDTM guidelines.Presentation on CDISC- SDTM guidelines.
Presentation on CDISC- SDTM guidelines.
 
CDISC Related Services
CDISC Related ServicesCDISC Related Services
CDISC Related Services
 
Data mining (DM) in the pharmaceutical industry
Data mining (DM) in the pharmaceutical industryData mining (DM) in the pharmaceutical industry
Data mining (DM) in the pharmaceutical industry
 
Trial Design Domains
Trial Design DomainsTrial Design Domains
Trial Design Domains
 
Regulatory bodies & CRO
Regulatory bodies & CRORegulatory bodies & CRO
Regulatory bodies & CRO
 
SDTM modelling: from study protocol to SDTM-compliant datasets
SDTM modelling: from study protocol to SDTM-compliant datasets SDTM modelling: from study protocol to SDTM-compliant datasets
SDTM modelling: from study protocol to SDTM-compliant datasets
 
Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma Data Mining and Big Data Analytics in Pharma
Data Mining and Big Data Analytics in Pharma
 
Cdisc sdtm implementation_process _v1
Cdisc sdtm implementation_process _v1Cdisc sdtm implementation_process _v1
Cdisc sdtm implementation_process _v1
 
Regulatory bodies
Regulatory bodiesRegulatory bodies
Regulatory bodies
 
Regulations for drug approval in USA, E.U & India
Regulations for drug approval in USA, E.U & IndiaRegulations for drug approval in USA, E.U & India
Regulations for drug approval in USA, E.U & India
 
Regulatory agencies
Regulatory agenciesRegulatory agencies
Regulatory agencies
 
SDTM (Study Data Tabulation Model)
SDTM (Study Data Tabulation Model)SDTM (Study Data Tabulation Model)
SDTM (Study Data Tabulation Model)
 
Komatsoulis Jhu
Komatsoulis JhuKomatsoulis Jhu
Komatsoulis Jhu
 
Clinical Data Standards and Data Portability
Clinical Data Standards and Data Portability Clinical Data Standards and Data Portability
Clinical Data Standards and Data Portability
 

Plus de Kevin Lee

Leading into the Unknown? Yes, we need Change Management Leadership
Leading into the Unknown? Yes, we need Change Management LeadershipLeading into the Unknown? Yes, we need Change Management Leadership
Leading into the Unknown? Yes, we need Change Management LeadershipKevin Lee
 
How to create SDTM DM.xpt using Python v1.1
How to create SDTM DM.xpt using Python v1.1How to create SDTM DM.xpt using Python v1.1
How to create SDTM DM.xpt using Python v1.1Kevin Lee
 
Enterprise-level Transition from SAS to Open-source Programming for the whole...
Enterprise-level Transition from SAS to Open-source Programming for the whole...Enterprise-level Transition from SAS to Open-source Programming for the whole...
Enterprise-level Transition from SAS to Open-source Programming for the whole...Kevin Lee
 
How I became ML Engineer
How I became ML Engineer How I became ML Engineer
How I became ML Engineer Kevin Lee
 
Artificial Intelligence in Pharmaceutical Industry
Artificial Intelligence in Pharmaceutical IndustryArtificial Intelligence in Pharmaceutical Industry
Artificial Intelligence in Pharmaceutical IndustryKevin Lee
 
Tell stories with jupyter notebook
Tell stories with jupyter notebookTell stories with jupyter notebook
Tell stories with jupyter notebookKevin Lee
 
Perfect partnership - machine learning and CDISC standard data
Perfect partnership - machine learning and CDISC standard dataPerfect partnership - machine learning and CDISC standard data
Perfect partnership - machine learning and CDISC standard dataKevin Lee
 
Machine Learning : why we should know and how it works
Machine Learning : why we should know and how it worksMachine Learning : why we should know and how it works
Machine Learning : why we should know and how it worksKevin Lee
 
Big data for SAS programmers
Big data for SAS programmersBig data for SAS programmers
Big data for SAS programmersKevin Lee
 
Big data in pharmaceutical industry
Big data in pharmaceutical industryBig data in pharmaceutical industry
Big data in pharmaceutical industryKevin Lee
 
How FDA will reject non compliant electronic submission
How FDA will reject non compliant electronic submissionHow FDA will reject non compliant electronic submission
How FDA will reject non compliant electronic submissionKevin Lee
 
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...Kevin Lee
 
Are you ready for Dec 17, 2016 - CDISC compliant data?
Are you ready for Dec 17, 2016 - CDISC compliant data?Are you ready for Dec 17, 2016 - CDISC compliant data?
Are you ready for Dec 17, 2016 - CDISC compliant data?Kevin Lee
 
SAS integration with NoSQL data
SAS integration with NoSQL dataSAS integration with NoSQL data
SAS integration with NoSQL dataKevin Lee
 
Introduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersIntroduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersKevin Lee
 
Standards Metadata Management (system)
Standards Metadata Management (system)Standards Metadata Management (system)
Standards Metadata Management (system)Kevin Lee
 
Data centric SDLC for automated clinical data development
Data centric SDLC for automated clinical data developmentData centric SDLC for automated clinical data development
Data centric SDLC for automated clinical data developmentKevin Lee
 
Beyond regulatory submission - standards metadata management
Beyond regulatory submission  - standards metadata managementBeyond regulatory submission  - standards metadata management
Beyond regulatory submission - standards metadata managementKevin Lee
 
Two different use cases to obtain best response using recist 11 sdtm and a ...
Two different use cases to obtain best response using recist 11   sdtm and a ...Two different use cases to obtain best response using recist 11   sdtm and a ...
Two different use cases to obtain best response using recist 11 sdtm and a ...Kevin Lee
 
Metadata becomes alive via a web service between MDR and SAS
Metadata becomes alive via a web service between MDR and SASMetadata becomes alive via a web service between MDR and SAS
Metadata becomes alive via a web service between MDR and SASKevin Lee
 

Plus de Kevin Lee (20)

Leading into the Unknown? Yes, we need Change Management Leadership
Leading into the Unknown? Yes, we need Change Management LeadershipLeading into the Unknown? Yes, we need Change Management Leadership
Leading into the Unknown? Yes, we need Change Management Leadership
 
How to create SDTM DM.xpt using Python v1.1
How to create SDTM DM.xpt using Python v1.1How to create SDTM DM.xpt using Python v1.1
How to create SDTM DM.xpt using Python v1.1
 
Enterprise-level Transition from SAS to Open-source Programming for the whole...
Enterprise-level Transition from SAS to Open-source Programming for the whole...Enterprise-level Transition from SAS to Open-source Programming for the whole...
Enterprise-level Transition from SAS to Open-source Programming for the whole...
 
How I became ML Engineer
How I became ML Engineer How I became ML Engineer
How I became ML Engineer
 
Artificial Intelligence in Pharmaceutical Industry
Artificial Intelligence in Pharmaceutical IndustryArtificial Intelligence in Pharmaceutical Industry
Artificial Intelligence in Pharmaceutical Industry
 
Tell stories with jupyter notebook
Tell stories with jupyter notebookTell stories with jupyter notebook
Tell stories with jupyter notebook
 
Perfect partnership - machine learning and CDISC standard data
Perfect partnership - machine learning and CDISC standard dataPerfect partnership - machine learning and CDISC standard data
Perfect partnership - machine learning and CDISC standard data
 
Machine Learning : why we should know and how it works
Machine Learning : why we should know and how it worksMachine Learning : why we should know and how it works
Machine Learning : why we should know and how it works
 
Big data for SAS programmers
Big data for SAS programmersBig data for SAS programmers
Big data for SAS programmers
 
Big data in pharmaceutical industry
Big data in pharmaceutical industryBig data in pharmaceutical industry
Big data in pharmaceutical industry
 
How FDA will reject non compliant electronic submission
How FDA will reject non compliant electronic submissionHow FDA will reject non compliant electronic submission
How FDA will reject non compliant electronic submission
 
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...
End to end standards driven oncology study (solid tumor, Immunotherapy, Leuke...
 
Are you ready for Dec 17, 2016 - CDISC compliant data?
Are you ready for Dec 17, 2016 - CDISC compliant data?Are you ready for Dec 17, 2016 - CDISC compliant data?
Are you ready for Dec 17, 2016 - CDISC compliant data?
 
SAS integration with NoSQL data
SAS integration with NoSQL dataSAS integration with NoSQL data
SAS integration with NoSQL data
 
Introduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmersIntroduction of semantic technology for SAS programmers
Introduction of semantic technology for SAS programmers
 
Standards Metadata Management (system)
Standards Metadata Management (system)Standards Metadata Management (system)
Standards Metadata Management (system)
 
Data centric SDLC for automated clinical data development
Data centric SDLC for automated clinical data developmentData centric SDLC for automated clinical data development
Data centric SDLC for automated clinical data development
 
Beyond regulatory submission - standards metadata management
Beyond regulatory submission  - standards metadata managementBeyond regulatory submission  - standards metadata management
Beyond regulatory submission - standards metadata management
 
Two different use cases to obtain best response using recist 11 sdtm and a ...
Two different use cases to obtain best response using recist 11   sdtm and a ...Two different use cases to obtain best response using recist 11   sdtm and a ...
Two different use cases to obtain best response using recist 11 sdtm and a ...
 
Metadata becomes alive via a web service between MDR and SAS
Metadata becomes alive via a web service between MDR and SASMetadata becomes alive via a web service between MDR and SAS
Metadata becomes alive via a web service between MDR and SAS
 

Dernier

Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsMark Billinghurst
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Patryk Bandurski
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr LapshynFwdays
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 3652toLead Limited
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLScyllaDB
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsSergiu Bodiu
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesZilliz
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfAddepto
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsMiki Katsuragi
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfRankYa
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfAlex Barbosa Coqueiro
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Manik S Magar
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024Stephanie Beckett
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...Fwdays
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxhariprasad279825
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 

Dernier (20)

Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Human Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR SystemsHuman Factors of XR: Using Human Factors to Design XR Systems
Human Factors of XR: Using Human Factors to Design XR Systems
 
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
Integration and Automation in Practice: CI/CD in Mule Integration and Automat...
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365Ensuring Technical Readiness For Copilot in Microsoft 365
Ensuring Technical Readiness For Copilot in Microsoft 365
 
Developer Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQLDeveloper Data Modeling Mistakes: From Postgres to NoSQL
Developer Data Modeling Mistakes: From Postgres to NoSQL
 
DevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platformsDevEX - reference for building teams, processes, and platforms
DevEX - reference for building teams, processes, and platforms
 
Vector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector DatabasesVector Databases 101 - An introduction to the world of Vector Databases
Vector Databases 101 - An introduction to the world of Vector Databases
 
Gen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdfGen AI in Business - Global Trends Report 2024.pdf
Gen AI in Business - Global Trends Report 2024.pdf
 
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
Vertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering TipsVertex AI Gemini Prompt Engineering Tips
Vertex AI Gemini Prompt Engineering Tips
 
Search Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdfSearch Engine Optimization SEO PDF for 2024.pdf
Search Engine Optimization SEO PDF for 2024.pdf
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 
Unraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdfUnraveling Multimodality with Large Language Models.pdf
Unraveling Multimodality with Large Language Models.pdf
 
Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!Anypoint Exchange: It’s Not Just a Repo!
Anypoint Exchange: It’s Not Just a Repo!
 
What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024What's New in Teams Calling, Meetings and Devices March 2024
What's New in Teams Calling, Meetings and Devices March 2024
 
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks..."LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
"LLMs for Python Engineers: Advanced Data Analysis and Semantic Kernel",Oleks...
 
Artificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptxArtificial intelligence in cctv survelliance.pptx
Artificial intelligence in cctv survelliance.pptx
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 

CDISC FDA Electronic Submission

  • 2. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Disclaimer 2 Any views or opinions presented in this presentation are solely those of the author and do not necessarily represent those of the company.
  • 3. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Why? 3
  • 4. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Golden Rule by Simon Sinek 4 What How Why
  • 5. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Agenda 5 • Why do we care CDISC electronic submission? – Recent Regulatory changes – FDASIA and PDUFA V • How can we prepare CDISC electronic submission? – eCTD version 3.2.2 and Data Standard Strategy • What do we prepare CDISC electronic submission? – CDISC components – CDISC electronic submission • Conclusion • Questions & Answers
  • 6. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Current Status of eSubmission in FDA 6
  • 7. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Current Status in CDISC Submission 7 CDISC submission • In 2010, CDER received an average of over 650 datasets/week, with 23% of active NDAs containing CDISC/SDTM data • In 2011 this number has increased to an average 39% in SDTM and 32% in ADaM
  • 8. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Significant Regulatory Changes 8 FDA Safety and Innovation Act (FDASIA) • signed into law on July 9, 2012. • expands the FDA’s authorities and strengthens the agency's ability to safeguard and advance public health. • Main impacts for us - reauthorizes the fifth instance of Prescription Drug User Fee Act (PDUFA V)
  • 9. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. PDUFA V commitment by FDASIA 9 • Provides FDA with the necessary resources to maintain a predictable and efficient review process for human drug and biologic products. • FDA will continue to receive a source of stable and consistent funding during fiscal years 2013-2017 that will allow the agency to fulfill its mission to protect and promote public health by helping to bring to market critical new medicines for patients
  • 10. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. PDUFA V commitment in section 7 10 A. To enhance the quality and efficiency of FDA’s review of NDAs, BLAs, and INDs, FDA shall consult with stakeholders, including pharmaceutical manufacturers and other research sponsors, to issue draft guidance on the standards and format of electronic submission of applications by December 31, 2012. B. FDA will issue final guidance no later than 12 months from the close of the public comment period on the draft guidance. Such final guidance and any subsequent revisions to the final guidance shall be binding on sponsors, applicants, and manufacturers no earlier than twenty-four months after issuance of the final guidance.
  • 11. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. PDUFA V commitment in section 7 (2) 11 C. Requirements for electronic submission shall be phased in according to the following schedule: 1. Twenty-four (24) months after publication of the final guidance: All new original NDA and BLA submissions, all new NDA and BLA efficacy supplements and amendments, all new NDA and BLA labeling supplements and amendments, all new manufacturing supplements and amendments, and all other new NDA submissions. 2. Thirty-six (36) months after publication of the final guidance: All original commercial INDs and amendments
  • 12. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. PDUFA V commitment in section 7 (3) 12 D. ….., initial FDA guidance shall specify the format of electronic submission of applications using eCTD version 3.2.2 unless, after notice and an opportunity for stakeholder comment, FDA determines that another version will provide for more efficient and effective applicant submission or FDA review.
  • 13. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. PDUFA V commitment in section 7 (4) 13 E. Clinical Terminology Standards: …., FDA shall develop standardized clinical data terminology through open standards development organizations (i.e., the Clinical Data Interchange Standards Consortium (CDISC)) with the goal of completing clinical data terminology and detailed implementation guides by FY 2017. 1. FDA shall develop a project plan for distinct therapeutic indications, prioritizing clinical terminology standards development within and across review divisions.
  • 14. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. More Updates from FDA on DIA 2013 14 • FDA is currently developing eCTD v 4.0. • Implementation Target – Mandatory eCTD submission – NDA and BLA : March 2016 – Commercial INDs : March 2017 • Based on the current implementation schedule, FDA begins receiving eCTD v 4.0 submission in 2016
  • 15. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. How do we prepare CDISC eSubmission? 15 • eCTD(Electronic Common Technical Document) v 3.2.2 for electronic submission • Data Standard Strategy for CDISC
  • 16. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Electronic Common Technical Document 16 • Introduction of eCTD – an interface for industry to agency transfer of regulatory information • Most recent version – v3.2.2 • Define – Module and its contents • Module 1 – Administrative information • Module 2 – eCTD summary document • Module 3 – Quality • Module 4 – Non-clinical Study Reports • Module 5 – Clinical Study Reports – File formats (i.e., pdf, txt, xml, xpt and etc)
  • 17. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Electronic Common Technical Document 17
  • 18. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Data Standard Strategy 18 • Purpose – to reinforce CDER’s on-going commitment to the development, implementation and maintenance of data standard program on regulatory submissions. • Objectives – Development of TA standards – Replacement of SAS XPORT files – Requirement of eSubmission • Data Standard – CDER initiated 55 key TA domains – CDISC will be implemented and enhanced to support TA standard development
  • 19. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. TA Data Standard Prioritization 19
  • 20. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Data Standard Strategy 20
  • 21. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. What do we prepare for CDISC eSubmission? 21 • CDISC components according to CDISC compliances • Its electronic formats according to eCTD
  • 22. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. CDISC Clinical Trial Process 22 PRN (Protocol) eCRF ODM.xml, L AB SDTM TFLADaM SAP CDASH CSR
  • 23. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. CDISC components in eSubmission 23 • Protocol • SAP • eCRF • SDTM • ADaM • SEND • CSR • Define.xml
  • 24. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Additional components in eSubmission 24 • ADaM SAS programs • Efficacy SAS programs (sometimes)
  • 25. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Formats of files according to eCTD 25 • Protocol – pdf (i.e., study001-protocol.pdf) • SAP – pdf (i.e., sutdy001-sap.pdf) • eCRF – pdf (i.e., sutdy001-blankecrf.pdf) • SDTM – xpt (i.e., dm.xpt, ae.xpt, ds.xpt, and etc) • ADaM – xpt (i.e., adsl.xpt, adae.xpt, adtteos.xpt, and etc) • SEND – xpt (i.e., dm.xpt, se.xpt, bw.xpt, and etc) • CSR – pdf (i.e., sutdy001-csr.pdf) • Define.xml – xml or pdf (i.e., define.xml/define.pdf) • ADaM SAS programs – txt (i.e., c-adsl-sas.txt) • Efficacy SAS programs – txt (i.e., t-14-01-001-ds-sas.txt )
  • 26. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Naming convention of files according to eCTD 26 • Lower case of letter from “a” to “z” • Number from “0” to “9” • “-” hypen • No special character ( #, %, $ and etc) • File name should be less than or equal to 64 characters including the appropriate file extension • The length of entire path of the file should not exceed 230 characters. (m5/datasets/study001/sdtm/ae.xpt)
  • 27. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. pdf file guideline according to eCTD 27 • Version – 1.4 thru 1.7 are acceptable • Fonts – Standard : Arial, Courier New, Times Roman – Sizes : range from 9 to 12 point ( Times New Roman 12-point font is recommended for narrative text ) • Page – Print area : 8.5 inches by 11 inches – Margin : at least ¾ inch
  • 28. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. SAS xpt file guideline according to eCTD 28 • Length – Variable length is less than or equal to 8 – Variable label is less than or equal to 40 – Dataset length is less than or equal to 8 – Dataset label is less than or equal to 40 • Dataset Size – less than 1 GB (LB1, LB2, and so on) • The length of character variables should be minimized (i.e., if the maximum length of USUBJID is 20 character long, keep the length as 20, not 200)
  • 29. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Module 5 CSR Reports 29 CSR, SAP, Protocol
  • 30. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. CDISC Datasets eSubmission 30 ADaM datasets, Define.xml ADaM SAS programs SDTM datasets, Define.xml, SDTM annotated blank eCRF
  • 31. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. CDISC compliance 31 • SEND : config-send-3.0.xml • SDTM : config-sdtm-3.1.3.xml • ADaM : config-adam-1.0.xml • Define : config-define-2.0.xml • CDISC compliance by OpenCDISC
  • 32. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Conclusion 32 • Before : “should” in FDA documents means that something is suggested or recommended, but not required. • After : “should” could mean required. • CDISC electronic submission will be mandatory sometime in 2016 or 2017.
  • 33. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Contacts 33 • Email address : Kevin.lee@cytel.com • Linkedin : – Profile : www.linkedin.com/in/kevinlee1995/ – Group : CDISC ADaM • Tweet : @kevinlee_pharma or @cdisc_adam
  • 34. www.cytel.com ©2013 Cytel Statistical Software & Services Pvt. Ltd. Questions? 34