Post on 12-Mar-2020
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STIJN ROGIERS - SAS SENIOR INDUSTRY CONSULTANT
GLOBAL PRACTICE, HEALTH & LIFE SCIENCES
CDISC Italian User Network Day – 21Oct2016
(Data standard e loro applicazione)
SAS Life Science Analytics Framework
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AGENDACDISC ITALIAN
USER NETWORK DAY
1. Introduction to SAS Life Science Analytics Framework (LSAF)
2. CDISC Standards & Study Metadata
Demo - Generation of Empty Datasets & Define.XML
3. End-2-End flow
SAS LSAF + Extensions through LSAF API
SDTM transformation
Cross-functional Review (structural & content checks, visualizations)
4. Use Cases
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INTRODUCTION
LIFE SCIENCE ANALYTICS FRAMEWORK
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CDISC ITALIAN
USER NETWORK DAY
SAS LIFE SCIENCE ANALYTICS FRAMEWORK
KEY FACTS (1/3)
Managing, analyzing, reporting, and reviewing (clinical) research information in the same analytical environment
Repository provides seamless integration with the SAS program development (authoring environment)
and execution environment, along with workflow capabilities
-- NEW Authoring Environment compared to SAS DRUG DEVELOPMENT (SDD)
-- NEW Business Process Model and Notation (BPMN) 2.0 standard support compared to SAS DRUG DEVELOPMENT (SDD)
Cloud based
Provides more flexibility, lower costs, greater scalability, ease of use and, if done correctly,
increased security and disaster recovery
IT seen as an ‘Innovator’ supporting the rest of the company to achieve its goals
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CDISC ITALIAN
USER NETWORK DAY
SAS LIFE SCIENCE ANALYTICS FRAMEWORK
PROGRAM AUTHORING & EXECUTION
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CDISC ITALIAN
USER NETWORK DAY
SAS LIFE SCIENCE ANALYTICS FRAMEWORK
WORKFLOW (SUPPORT BPMN STANDARD)
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SAS LIFE SCIENCE ANALYTICS FRAMEWORK
KEY FACTS (2/3)
Collaboration & Accessibility
internally and externally (geographically remote)
direct access to research content, clearly organized and searchable
Configurable User Interface
Highly flexible (configurable) permission model privileges & permissions
High-performance (Remote) Application Programming Interface (extend & automate)
Java API and SAS Macro API, moving to RESTful API
Complete audit history and robust version control system managing change history of all files
Job concept and Manifest file
Job Concept reproducibility and usability (for non-technical savvy users)
Manifest File transparency and traceability
CDISC ITALIAN
USER NETWORK DAY
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REPOSITORY AND CREATION OF JOB
EXAMPLECDISC ITALIAN
USER NETWORK DAY
Create Job from existing SAS files + Run and Populate
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REPOSITORY AND CREATION OF JOB
EXAMPLE
CDISC ITALIAN
USER NETWORK DAY
Create Job from existing SAS files + Run and Populate
“Run and Populate” scans all SAS programs to produce “Input & Outputs” automatically (example of Inputs/Outputs on next slide).
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JOB MANIFEST FILE
EXAMPLECDISC ITALIAN
USER NETWORK DAY
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SAS LIFE SCIENCE ANALYTICS FRAMEWORK
KEY FACTS (3/3)
Standards metadata management (driving automation) -- NEW compared to SAS DRUG DEVELOPMENT (SDD)
Standard (Global) Level (SDTM & SEND) “ Data Standards ” Module
Study Level Study Specification: Empty Datasets + Define XML 2.0 creation “ Studies ” Module
Support Visual Analytics (integration) -- NEW compared to SAS DRUG DEVELOPMENT (SDD)
Expanding Suite of Extensions (optional modules build on robust LSAF API)
E.g. ‘Templates’ extension to automate creation of folder structure
within repository incl. administration/security.
Note: See also additional extensions slides related to end-2-end flow.
CDISC ITALIAN
USER NETWORK DAY
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CLINICAL STUDIES VISUALIZATION
EXAMPLE
32
1
1. Direct link to Patient Profile
2. Drop down list showing
# of subjects in a site
3. Drop down list showing #
of subjects who died in study
Aggregate Panel Review
CDISC ITALIAN
USER NETWORK DAY
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1
2
3
4
5
5
6
7
8
9
101. DM domain view
2. SV domain view
3. SE domain view
4. DS domain view
5. CM domain view
6. AE domain view
7. MH domain view
8. LB domain view
9. VS domain view
10. Visits view
11. Link back to
Demographic view
11
CLINICAL STUDIES VISUALIZATION
EXAMPLE
Patient Profile
CDISC ITALIAN
USER NETWORK DAY
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CDISC STANDARDS AND STUDY METADATA
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GLOBAL STANDARDS
STANDARDS MANAGEMENT – STUDY METADATA – DATA PROCESSING – REVIEW – ANALYSIS
External /
Other Data
eSHARE
Standards
IMPORT eSHARE CDISC
STANDARDS
CREATE CUSTOMER STANDARDS
Global Standards
DEFINE
STUDY LEVEL METADATA
CREATE SUBMISSION
READY SDTM DEFINE.XML
SHARE WITH INTERNAL & EXTERNAL
STAKEHOLDERS
Study Metadata
Sensors/
Wearables
Protocol
EDC DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Other DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Event Streaming
(SAS® Event Stream Process
Engine)
Extraction & Transformation
Specifications
EDC
SDTM
Transformation(Life Science Analytics
Framework
Extension/App)
Specifications
Cross-Functional Review
Final Deliverables
Deliverables (Internal sharing of SDTM data after Structure ‘automated’ verification)
Automated + Manual Review Activities
(Life Science Analytics Framework Programs/Jobs + SAS® Visual
Analytics + Pinnacle 21 (~Open CDISC), ...)
1 2
3
3
3
45
Cross-Functional Review Tracking
(Life Science Analytics Framework Extension/App)
Review Input
PROGRAMS-JOBS
DEVELOPMENT
* CREATION, QC & USAGE
(INCL. VERSION
CONTROL)
* SIGN-OFF
* AUTOMATION VIA
WORKFLOW
• RUNNING “R” CODE
THROUGH PROC IML
VISUALIZATIONS
(SAS® Visual Analytics, ...)
ADAPTIVE DESIGN
AUTOMATION
( Life Science Analytics
Framework Extension/App )
Internal
system(s) /
customersOutbound data
( Life Science Analytics Framework Extension/App )
7
8
6
CDISC ITALIAN
USER NETWORK DAY
Analysis Activities
PROGRAMMING
TRACKING & PROGRESS
( Life Science Analytics Framework
Extension/App )
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STUDY METADATA
STANDARDS MANAGEMENT – STUDY METADATA – DATA PROCESSING – REVIEW – ANALYSIS
External /
Other Data
eSHARE
Standards
IMPORT eSHARE CDISC
STANDARDS
CREATE CUSTOMER STANDARDS
Global Standards
DEFINE
STUDY LEVEL METADATA
CREATE SUBMISSION
READY SDTM DEFINE.XML
SHARE WITH INTERNAL & EXTERNAL
STAKEHOLDERS
Study Metadata
Sensors/
Wearables
Protocol
EDC DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Other DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Event Streaming
(SAS® Event Stream Process
Engine)
Extraction & Transformation
Specifications
EDC
SDTM
Transformation(Life Science Analytics
Framework
Extension/App)
Specifications
Cross-Functional Review
Final Deliverables
Deliverables (Internal sharing of SDTM data after Structure ‘automated’ verification)
Automated + Manual Review Activities
(Life Science Analytics Framework Programs/Jobs + SAS® Visual
Analytics + Pinnacle 21 (~Open CDISC), ...)
1 2
3
3
3
45
Cross-Functional Review Tracking
(Life Science Analytics Framework Extension/App)
Review Input
PROGRAMS-JOBS
DEVELOPMENT
* CREATION, QC & USAGE
(INCL. VERSION
CONTROL)
* SIGN-OFF
* AUTOMATION VIA
WORKFLOW
• RUNNING “R” CODE
THROUGH PROC IML
VISUALIZATIONS
(SAS® Visual Analytics, ...)
ADAPTIVE DESIGN
AUTOMATION
( Life Science Analytics
Framework Extension/App )
Internal
system(s) /
customersOutbound data
( Life Science Analytics Framework Extension/App )
7
8
6
CDISC ITALIAN
USER NETWORK DAY
Analysis Activities
PROGRAMMING
TRACKING & PROGRESS
( Life Science Analytics Framework
Extension/App )
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SAS LIFE SCIENCE ANALYTICS FRAMEWORK
STANDARDS MANAGEMENT
CDISC ITALIAN
USER NETWORK DAY
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SAS LIFE SCIENCE ANALYTICS FRAMEWORK
STUDY METADATA MANAGEMENT
CDISC ITALIAN
USER NETWORK DAY
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END-2-END FLOW (LSAF + EXTENSIONS)
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END-TO-END FLOWCDISC ITALIAN
USER NETWORK DAY
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Analysis Activities
SDTM TRANSFORMATION
STANDARDS MANAGEMENT – STUDY METADATA – DATA PROCESSING – REVIEW – ANALYSIS
External /
Other Data
eSHARE
Standards
IMPORT eSHARE CDISC
STANDARDS
CREATE CUSTOMER STANDARDS
Global Standards
DEFINE
STUDY LEVEL METADATA
CREATE SUBMISSION
READY SDTM DEFINE.XML
SHARE WITH INTERNAL & EXTERNAL
STAKEHOLDERS
Study Metadata
Sensors/
Wearables
Protocol
EDC DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Other DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Event Streaming
(SAS® Event Stream Process
Engine)
Extraction & Transformation
Specifications
EDC
SDTM
Transformation(Life Science Analytics
Framework
Extension/App)
Specifications
Cross-Functional Review
Final Deliverables
Deliverables (Internal sharing of SDTM data after Structure ‘automated’ verification)
Automated + Manual Review Activities
(Life Science Analytics Framework Programs/Jobs + SAS® Visual
Analytics + Pinnacle 21 (~Open CDISC), ...)
1 2
3
3
3
45
Cross-Functional Review Tracking
(Life Science Analytics Framework Extension/App)
Review Input
ANALYSIS PROGRAMS-
JOBS
* CREATION, QC & USAGE
(INCL. VERSION CONTROL)
* SIGN-OFF
* AUTOMATION THROUGH
WORKFLOW
* RUNNING “R” CODE THROUGH
PROC IML
VISUALIZATIONS
(SAS® Visual Analytics, ...)
ADAPTIVE DESIGN
AUTOMATION
(Life Science Analytics Framework
Extension/App)
Internal
system /
PartnerOutbound data
7
8
6
CDISC ITALIAN
USER NETWORK DAY
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END-2-END FLOW:
SDTM TRANSFORMATION (LSAF EXTENSION)
Supported by SAS Solutions On Demand
Current Flow Overview (all details can be provided during a demo)
Publish manual mapping to Auto-mapping definitions for future (~ machine learning).
Over time this will reduce manual mapping efforts significantly.
Generate Program Templates with Pre-Code, Mapping information and Post-Code
CDISC ITALIAN
USER NETWORK DAY
Define StudyIdentify CDISC
Mapping Standard
Identify Data Sources
Understand / browse
through raw data
Table to Domain mapping
Variable Mapping
(Auto-mapping and manual +
Progress)
Publish Mappings
Transformation Program
‘Templates’
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CDISC ITALIAN
USER NETWORK DAY
END-2-END FLOW:
SDTM TRANSFORMATION (LSAF EXTENSION)
Define StudyIdentify CDISC
Mapping Standard
Identify Data Sources
Understand / browse through
raw data
Table to Domain mapping
Variable Mapping
(Auto-mapping and manual +
Progress)
Publish Mappings
Transformation Program
‘Templates’
• Generate Program Templates with Pre-Code, Mapping information and Post-Code
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Analysis Activities
CROSS-FUNCTIONAL REVIEW
STANDARDS MANAGEMENT – STUDY METADATA – DATA PROCESSING – REVIEW – ANALYSIS
External /
Other Data
eSHARE
Standards
IMPORT eSHARE CDISC
STANDARDS
CREATE CUSTOMER STANDARDS
Global Standards
DEFINE
STUDY LEVEL METADATA
CREATE SUBMISSION
READY SDTM DEFINE.XML
SHARE WITH INTERNAL & EXTERNAL
STAKEHOLDERS
Study Metadata
Sensors/
Wearables
Protocol
EDC DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Other DATA EXTRACTION
(Life Science Analytics Framework
Extension/App)
Event Streaming
(SAS® Event Stream Process
Engine)
Extraction & Transformation
Specifications
EDC
SDTM
Transformation(Life Science Analytics
Framework
Extension/App)
Specifications
Cross-Functional Review
Final Deliverables
Deliverables (Internal sharing of SDTM data after Structure ‘automated’ verification)
Automated + Manual Review Activities
(Life Science Analytics Framework Programs/Jobs + SAS® Visual
Analytics + Pinnacle 21 (~Open CDISC), ...)
1 2
3
3
3
45
Cross-Functional Review Tracking
(Life Science Analytics Framework Extension/App)
Review Input
ANALYSIS PROGRAMS-
JOBS
* CREATION, QC & USAGE
(INCL. VERSION CONTROL)
* SIGN-OFF
* AUTOMATION THROUGH
WORKFLOW
* RUNNING “R” CODE THROUGH
PROC IML
VISUALIZATIONS
(SAS® Visual Analytics, ...)
ADAPTIVE DESIGN
AUTOMATION
(Life Science Analytics Framework
Extension/App)
Internal
system /
PartnerOutbound data
7
8
6
CDISC ITALIAN
USER NETWORK DAY
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CDISC ITALIAN
USER NETWORK DAY
CROSS-FUNCTIONAL REVIEW:
AUTOMATED (1/4)
Review Tracking Rules
(= Compliance Rule(s) ~Structural , Global Content Rule(s), Trial Specific Content Rule(s))
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CDISC ITALIAN
USER NETWORK DAYCROSS-FUNCTIONAL REVIEW: AUTOMATED (3/4)
Review Tracking Output (Follow-Up)
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CDISC ITALIAN
USER NETWORK DAYCROSS-FUNCTIONAL REVIEW: AUTOMATED (4/4)
Review Tracking Output (Follow-Up) - Details including History, Attached Files.
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CDISC ITALIAN
USER NETWORK DAYCROSS-FUNCTIONAL REVIEW: MANUAL
Opportunity to raise Manual findings
e.g. Visualizations (medical review); looking at output, listings; etc. …
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USE CASES
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MAJOR PHARMACEUTICAL
PROCESS IMPROVEMENT
2010 - 2016
BUSINESS ISSUE(S)
• Needed better Quality Control on Data Management CROs
• ability to handle changing CDISC data standards (standards management)
• be able to create Study Level Metadata (Define.XML) and provide to DM-CRO as clear specifications
• wanted automated review process of DM CROs deliverables (SDTM data + Define.XML) prior to data
being given to data management
• Needed new Data Management platform (in the Cloud) to facilitate new DM processes
• clean the data (focusing on Primary & Secondary endpoints; Standard work done by DM-CRO)
• be able to run CDISC Compliance Checks on the data received from the DM-CRO
• be able to explore the datasets within the same platform
• Transfer data from/to other stakeholders - systems (e.g. External Data such as but not limited to
Central ECG or Central Lab; DM-CRO’s end deliverables; Feeds of data into DWH of sponsor; etc.)
• Repository for all their Clinical Trial Data (incl. Audit Trail, Version Control, Part 11 compliant,
Workflow Management)
• handle growth to allow other areas of clinical R&D to access information and do their analysis in same
platform/environment.
USE CASE 1 (PAGE 1/3)
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MAJOR PHARMACEUTICAL
PROCESS IMPROVEMENT
2010 - 2016
SOLUTION
• SAS Drug Development + Custom Application Development by 3rd party
[ Java UI + Oracle DB using SDD API’s ]
RESULTS
PHASE I (2010-2014)
• Automated DM-CRO review process (less time and review cycles by customer)
• Quality increase of DM-CRO deliverables (through clear specifications)
• Increase of Traceability (Job Manifests) & Reproducibility (Jobs)
PHASE II (2015-2016)
• Scalable environment has allowed them to provide access to new teams (Statistical Programmers &
Statisticians) for new clinical trials with no new investment in hardware
• Increase collaboration (partnering) between DM and Stats Programmers/Statisticians
• Migration of all ongoing clinical trials to LSAF (from own internal Servers / SAS environment) = Recently
Started.
FUTURE STEPS
• Provide access to other teams (scale up)
• As more standards functionalities become available in LSAF (compared to SDD), transition from
the Custom Application to LSAF Build-in (standard) functionalities started
USE CASE 1 (PAGE 2/3)
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MAJOR PHARMACEUTICAL
PROCESS IMPROVEMENT
2010 - 2016
SOME FIGURES
• Users on SDD
• Current Status (including external company users): +1000
• By End 2016: +1500
[ Data Management & Statistical Programming/stats ]
USE CASE 1 (PAGE 3/3)
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VACCINES SUBSIDIARY OF
MAJOR PHARMACEUTICAL
COMPANY
SOLUTION
• SAS Drug Development
RESULTS
• All data management and statistical programming
• Strict hierarchy set up to complete separate DM (Data Standards Programming and Study-
Specific) and statistical work
• Data transferred from EDC system (Inform) to SAS solution
• Using Spotfire to help out with clinical data management review process, SAS to clean data
• Integration with safety system
• Integrations with Oracle user management database (trial access) and program lifecycle
management database
• SAS solution is also being used by trial operations and clinicians as central and operational-
critical hub for accessing clinical trial data and support trial analytics
About +/- 1500 users in total, of which about 300 concurrent in the environment
USE CASE 2
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AS A
REFERENCE
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THANK YOU !
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STIJN.ROGIERS@SAS.COM
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@STIJNROGIERS
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