Modeling Endpoints: How to Model Anti-Drug Antibody Data in Nonclinical Studies
- 1 Working Group Overview
- 2 Plans
- 3 Deliverables
- 4 Participation Needs
- 5 Work Group Participants
- 6 Conference Calls and Minutes
- 7 Webinar Presentations
Welcome to the site for the "Investigating Endpoint Modeling - How to Model Anti-Drug Antibody Data in Nonclinical Studies" project group.
This page describes high-level project management details on the group, including purpose, milestones, attendees, and so on. We are part of the FDA/PhUSE Computational Sciences Nonclinical Working Group. Learn more about the larger working group at Non-Clinical Road-map and Impacts on Implementation.
Working Group Overview
Withing the SEND Model, SENDIG version 3.0 and SENDIG version 3.1, the model does not dictate a clear methodology for reporting and tabulating Anti-Drug Antibody Data in Nonclinical Studies.
As the model develops, these considerations are taken into account, but prior recommendations and possible solutions are needed.
To provide recommendations for modeling Anti-Drug Antibody utilizing SENDIG V3.0 and SENDIG V3.1 Domains and variables. Create a landscape of possible solutions and provide recommendations. Consider appropriateness for visualization for ADA at a high level. Investigate the current SDTM practices and recommendations.
- Determine endpoints
- Call for Participants
- Maintain wiki (ongoing)
- Research CDISC ADA
- Poster - Scope of Poster - SENDIG v3.0 recommendation and then provisional recommendation for SENDIG v3.1 - January 12th draft, abstract with summary due - Final poster presented at PhUSE CSS 2018 http://www.phusewiki.org/wiki/images/1/11/PP_-_Modelling_of_ADA_in_SEND_-_PhUSE_CSS_18_final.pdf
- White Paper to follow
Call For Participants for Nonclinical Topics Working Group “Modeling Endpoints: How to Model Anti-Drug Antibody Data in Nonclinical Studies” Project The team was established at the PhUSE CSS March 2017. What is the Goal/Focus? To provide recommendations for modeling Anti-Drug Antibody utilizing SENDIG V3.0 and SENDIG V3.1 Domains and variables. Create a landscape of possible solutions and provide recommendations. Consider appropriateness for visualization for ADA at a high level. This will included investigating what clinical is doing and/or recommending and how this can be harmonized into SEND datasets.
Who are we looking for to participate? SEND Core, Preclinical CROs/Bioanalytical labs, Industry (Pharma and biotechnology for preclinical), SEND software vendors, and SEND service vendors.
Call for participation! What is the commitment? Time (minimum of 1 hour every two weeks for team meetings, up to 3 hours / month) Expected to contribute, not just be a spectator Contribution of viewpoints and content Wiki - creating/reviewing page content If you would like to participate, please contact the co-leads for this group: Mike Wasko (email@example.com), Gretchen Dean (firstname.lastname@example.org) and/or Thomas Gade Bjerregaard (email@example.com).
Work Group Participants
- Michael Wasko - firstname.lastname@example.org
- Gretchen Dean - email@example.com
- Thomas Gade Bjerregaard - firstname.lastname@example.org
- Thomas Gade Bjerregaard, Novo Nordisk
- Alan Brown, Novartis
- Kathy Brown, Sanofi
- Christine Connolly, EMD Serono
- Gretchen Dean, Pfizer
- Jennifer Emenegger, Merck
- Anthony Fata, SNBL
- Joyce Ford, Janssen
- Wendy Freeburn, Bristol-Myers Squibb
- William Houser, Bristol-Myers Squibb
- Trina Jiao, Janssen
- Rihab Kordane, Charles River Laboratories
- Christy Kubin, MPI Research
- Jordan Li, National Institutes of Health
- Ralf Loebbert, Abbvie
- Leslie Lorello, Pfizer
- Stephen MacMannis, Pfizer
- Kennan Marsh, Abbvie
- Janessa Pierce, Merck
- Anna Pron-Zwick, AstraZeneca
- Jason Rogers, Envigo
- Susan Steen, Bristol-Myers Squibb
- Dennis Stocker, Bristol-Myers Squibb
- Joleen White, EMD Serono
- Lauren White, PhUSE
Conference Calls and Minutes
CDISC Cross Collaboration with CDISC Microbiology Team in regards to ADA
Last revision by Mwasko79, 2018-03-6