phuse computational science symposium working groups an experiment in collaboration
DESCRIPTION
PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration. What is PhUSE?. Pharmaceutical Users Software Exchange Global group of programmers, statisticians, and data scientists Vendor neutral, Inclusive, and Open www.phuse.eu Mission: - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/1.jpg)
PhUSE Computational Science Symposium
Working GroupsAn Experiment in Collaboration
![Page 2: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/2.jpg)
What is PhUSE?
Pharmaceutical Users Software Exchange• Global group of programmers, statisticians, and data
scientists • Vendor neutral, Inclusive, and Open• www.phuse.euMission:Provide platform for creating & sharing ideas, implementing tools & standards around data, and exploring innovative methods and technologies
![Page 3: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/3.jpg)
Old Paradigm
FDA
Please tell us what to do
![Page 4: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/4.jpg)
Paradigm Shift
FDA
Pharma
CDISC
Vendors
CROs
Academia
![Page 5: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/5.jpg)
CSS Timeline2013/14: Annual CSS Meetings
![Page 6: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/6.jpg)
What CSS WGs Are?
•Work on best practices for standards and technology implementation•Discuss and summarize challenges with implementation
Implementation
•Try ideas using new technology e.g., semantic modeling, cloud-based implementation•Test and provide feedback on new standards and processesIncubator
•Open forum for sharing ideas across FDA, Industry, and other organizations•Provide platforms (wikis, code libraries) for sharing informationCollaboration
![Page 7: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/7.jpg)
What CSS WGs are Not
•Projects do not create, define and/or recommend policy or guideline changes•FDA individuals provide input onlyPolicy•CDISC, HL7 and other SDOs create standards;•CSS Working Groups tackle implementation and best practices around standardsStandards
•Projects are not a place to ‘market’ technology•Open collaboration in a non-competitive environment
Commercial
![Page 8: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/8.jpg)
Optimizing Use of Data Standards
Emerging Technologies
Standar
d Scri
pts f
or
Re
por
ti
ng a
nd
Analysis
Non-Clinical Roadmap and Implementation
Steering Committee
CSS Working Groups
![Page 9: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/9.jpg)
Steering Committee
Industry• Chris Decker – Industry PM (d-Wise)• Scott Bahlavooni (Biogen Idec)• Anne Russotto – (Celgene)• Michael Brennan (J&J)• Jim Johnson – Optimizing Standards Liaison
(Summit Analytical)• Susan DeHaven – Non-Clinical Liaison
(Sanofi)• Mary Nilsson – Standard Scripts Liaison (Eli
Lilly)• Frederik Malfait – Emerging Technologies
Liaison (IMOS Consulting)
FDA • Crystal Allard – FDA PM • Lilliam Rosario• Steve Wilson• Suzie McCune
![Page 10: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/10.jpg)
Working Group Leadership Teams
• Emerging Technologies– Frederik Malfait (Roche)– Isabelle deZegher (Paraxel)– Matteo Ditommaso (Pfizer)– Crystal Allard, FDA Liaison
• Optimizing Data Standards– Jim Johnson (Summit
Analytical– Jingyee Kou, FDA Liaison– Steve Wilson, FDA Liaison
• Standard Scripts– Mary Nilsson (Eli Lilly)– Hanming Tu (Accenture)– Steve Wilson, FDA Liaison
• Non-Clinical – Susan DeHaven (Sanofi)– Bob Dorsam, FDA Liaison
Lot of other volunteers leading projects!
![Page 11: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/11.jpg)
Overview:The development and implementation of data standards has shown significant promise in improving efficiencies in the product submission and review process. However, there are challenges in the interpretation and use of the standards. This working group identifies specific gaps and best practices to enable FDA and industry to maximize the benefits of standards implementation.
Optimizing the Use ofData Standards
![Page 12: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/12.jpg)
Optimizing Data Standards Active Projects
Traceability and Data Flow
ADaM Data Reviewer’s
Guide
Best Practices
Study Data Standardization
Plan
![Page 13: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/13.jpg)
Traceability and Data Flow • Leaders: Paul Bukowiec, Sandra Minjoe, Tanja
Petrowitsch, Natalie Reynolds• This project will discuss and define traceability
considerations and best practices for study level dataset and integrated datasets conversion for a variety of different data flow scenarios.
ODS Projects
![Page 14: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/14.jpg)
Traceability and Data Flow • Meeting Accomplishments:
– Developed first draft of Study Level Traceability white paper
– Noted specific traceability details to be added to current Basic Linear Data Flow white paper
– Determined the need to develop a template for the Legacy Data Conversion Plan (mentioned in the new draft FDA Study Data Technical Conformance Guide)
ODS Projects
![Page 15: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/15.jpg)
Analysis Data Reviewer’s Guide (ADRG)• Leaders: Susan Kenny, Gail Stoner• Development of an ADRG template and instructions for
industry to consider that will enable consistent and usable ADaM documentation in submissions.
ODS Projects
![Page 16: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/16.jpg)
Analysis Data Reviewer’s Guide (ADRG)• Accomplished at Meeting
– Completed final review of Template– Completed final review of Completion Guideline– Presented poster and expect to receive additional comments.
Comments due by MARCH 28.– Began review of one ADRG example
• By April 30: – Complete review and updates to 2 examples– Finalize ALL documents (template, guidelines, samples)– Post all materials to PhUSE Wiki
ODS Projects
![Page 17: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/17.jpg)
Best Practices for Standards Implementation (NEW)• Leaders: Mike Molter, Lisa Lyons• Goal: develop a set of recommendations for best practices in
optimizing the data standards. • Each topic will be ~3-5 months duration for delivery of the
recommendation• Each best practice will have a sub-team• First topics include:
– Lab Unit Standardization– EPOCH/VISITNUM assignments– USUBJID assignments
ODS Projects
![Page 18: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/18.jpg)
• Future Best Practices Topics Identified– Programming Documentation– Reference Range Standardization– Unit Standardization Beyond Labs– Trial Design Setup– Treatment Emergent Flags– ARM/ARMCD assignment and standard implementation– Others welcome – Will be a place to identify new topics
on Best Practices Wiki
Data Optimization: Best Practices
![Page 19: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/19.jpg)
• Study Data Standardization Plan (SDSP)– New Project Starting in 2014– Goal of the Project is to develop a Template to be
made available for Industry– Template Model will follow a similar development as
the SDTM and ADaM Reviewer’s Guide
ODS Project
![Page 20: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/20.jpg)
Overview: The development and implementation of data standards provides a great opportunity to develop standard analyses and displays to support the needs of FDA medical and statistical reviewers. This working group will identify potential standard scripts for data transformation, analyses, and displays.
Standard Scripts for Analysis and Programming
![Page 21: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/21.jpg)
• P01: Look for existing scripts and store them in the repository - Work on FDA scripts first • P02: Define qualification steps for scripts in the repository• P03: Maintain and enhance platform (repository) for sharing scripts• P04: Create templates and metadata for documenting scripts and coding practices • P05: Implement and further develop communication plan for standard scripts• P06: Create white papers providing recommended display and analysis including Table, List and Figure shells
Refined Projects
![Page 22: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/22.jpg)
• Scriptathon – Success!!!!– 26 attendees/15 coders– 13 Scripts developed– Volunteers for the remaining scripts– Organize local and annual events
Scriptathon Summary
![Page 23: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/23.jpg)
• White Papers– Great Discussion!– Six whitepapers
• ECG, Vitals, Labs – Central Tendency: finalized in 2013• ECG, Vital, Labs – Outlier/Shifts• Adverse Events• Demographics, Disposition, Medications• Hepatotoxicity• PK
– One additional white paper planned to be added (QT Studies)
– Look for writing support
Whitepaper Summary
![Page 24: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/24.jpg)
• Continue to build Script Repository– Continue creating code for tables and figures as outlined in white papers– Look for other existing code sharing libraries
• Continue white paper development– Consider updating the first white paper– Finalize PK white paper this month– Finalize remaining 4 white papers in 2014– Consider additional white papers to develop
• Communications– Presentations at various conferences– Implement other ideas to increase awareness
Plans for Upcoming Year
![Page 25: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/25.jpg)
Non-Clinical Roadmap and Impacts on Implementation
Overview:A need exists to improve nonclinical assessments and regulatory science by identifying key needs and challenges then establishing an innovative framework for addressing them in a collaborative manner. This working group establishes the collaborative framework and identifies and executes projects to support nonclinical informatics and specific implementation solutions for SEND.
![Page 26: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/26.jpg)
Nonclinical Working Group
6 projects with significant accomplishments over the past year
- White paper published (3/14):
“Interconnectivity of Disparate Nonclinical Data Silos for Drug Discovery and
Development”
- Manuscript developed on industry use of Nonclinical Historical Control
Data
- Expansion of SEND Wiki, with QA perspectives on SEND – poster
- Compared Clinical vs Nonclinical Study Data Reviewer’s Guide –
poster
- Development and testing of interorganizational flow of e-data – 2
posters
- “How to Design a Custom SDTM Domain for Nonclinical Data”
![Page 27: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/27.jpg)
CSS PhUSE 2014 ThemeDeveloping Collaborations
Our Sessions1. Panel discussion – “How are clinical and nonclinical data coming together
in your environment?” • 3 presenters shared experiences (vendors, sponsors, consortia)
2. Develop collaborations across PhUSE and others – • Interactive discussion on possible projects with Emerging Technologies,
IMIeTox, and Transcelerate • Goal to increase potential for collaborative new projects
3. Team time• Opportunity for NC projects to get feedback from full WG on
accomplishments and future directions• New project idea triage and action plans
4. Leveraging Deliverables• “Table Teams” contributed their experience Socializing the Deliverables
![Page 28: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/28.jpg)
Actions for 2014
• AND……..Turbocharge the SEND Implementation User Group!
– New members, WIKI tools, communication subteams
![Page 29: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/29.jpg)
Emerging Technologies
Overview:Regulatory science, drug, biologic, and new device development challenged present a unique opportunity to apply underutilized existing technologies and/or new and emerging technologies. This working group provides an open, transparent, pre-competitive forum for the exploration and application of said technologies.
![Page 30: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/30.jpg)
30
Metadata Definition
Leader: Isabelle deZegher
• No formal meeting • Finalize document through TC – Available Apr2014
![Page 31: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/31.jpg)
• Review the current draft model• Discuss modeling of study parameters/parameter
groups, study activities and planned activities• Discuss next steps for the RDF model
– Do not want it to become another “under-used” representation of structured protocol content
ST: Representing PRM/SDM.xml in RDF
![Page 32: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/32.jpg)
• Introduce team and concept to the broader community
• Developed draft metadata for count and summary statistic analysis procedures
• Identified central tendency, t-test, ANOVA as next analyses to develop
• Identified strategy for researching publically available existing models
• Identified alignment needs with the define.xml team and standard scripts repository white paper team
ST: Analysis Results Metadata
![Page 33: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/33.jpg)
Summary
• Great opportunity for FDA and Industry to work together
• Evolving and changing• Typical Challenges of volunteers and time• Exciting interactions and discussion
![Page 34: PhUSE Computational Science Symposium Working Groups An Experiment in Collaboration](https://reader036.vdocument.in/reader036/viewer/2022081507/56816618550346895dd969bf/html5/thumbnails/34.jpg)
Get Involved
• See the PhUSE CSS Dashboard for an overview of active projects– http://www.phuse.eu/CSS-dashboard.aspx
• More detailed project and working group information is available on the PhUSE Wiki– http://www.phusewiki.org/wiki/index.php?title=PhUSE_Wiki
• Email and working group lead or sign up for a mailing list– http://
www.phusewiki.org/wiki/index.php?title=Listbox_Instructions