1. Standard Analyses and Code Sharing Summary for the Best Practices for Data Collection Instructions Project Team
Mary Nilsson
20 March 2017

2. Working Group Vision/Goals
Leverage crowd-sourcing to improve the content and implementation of analyses for medical research, leading to better data interpretations and increased efficiency in the clinical drug development and review processes.
Establish and maintain a publicly available repository for storing program code to be used as analytical tools for medical research.
Where gaps exist, develop recommendations for analyses and displays in areas that could benefit from crowd-sourcing.
Where gaps exist, develop code for recommended analyses and displays that could benefit from crowd-sourcing (to reside in the repository).

3. Vision: Fill the Gap on Analysis and Display Standards
Data Collection Systems
Observed Datasets
Analysis Datasets
Tables, Figures and Listings
Clinical Data
Flow
Trial Design
PRM
SDTM
ADaM
No Standards Exist
Industry
Standards
Alignment
CDASH
A lot of progress has been made with respect to standardization – mostly in the collection and data space. There’s a gap with respect to analyses and displays. CFAST = Coalition for Accelerating Standards and Therapies
(Therapeutic Areas)

4. Vision: Script Repository (Shared Reusable Code Library)
FDA
Industry
Academia
Script Repository in Github
Vision of the Script Repository – Reusable code library – Utilizing crowd-sourcing to maintain. All inclusive. Assumes SDTM/ADaM data structure. Currently SAS and R focus but not intended to be limited to those. Getting code associated with the white papers is a current focus. Adding some standard code that FDA medical reviewers use is also a focus. Can also be a place to share code for ADaM derivations.
Test Data
SAS, R, Spotfire, Etc.
Code Test Environment
White Paper Scripts
Contributed Scripts

5. Three Focus Areas, 6 active projects
Script Repository (4 projects)
Script Discovery and Acquisition (SDA, Rebeka Revis, Alfredo Rojas)
Repository Content and Delivery (RCD, Gustav Bernard, Andrew Miskell)
Repository Governance and Infrastructure (RGI, Mike Carniello, Hanming Tu)
Test Data Factory (TDF, Peter Schaefer)
Analyses and Display White Papers (ADW, Mary Nilsson)
Communication, Promotion, Education (CPE, Jared Slain and Wendy Dobson)

6. Analysis and Display White Papers Project Team
Version 1
Version 2
Public
Review
Published
Public Review
Vital Signs, Labs, ECG –
Central Tendency
Oct 2013
Q4 2017
Non-Compartmental PK
March 2014
Demographics, Disposition, Medications
Oct 2014
Q3 2017
Outliers / Shifts
Sept 2015
QT/QTc Studies
March 2016
Adverse Events
Feb 2017
Treatment-Emergent Definitions
Hepatotoxicity
Questionnaires
Events of Special Interest

7. Discussion Points for Collection Instructions Project Team
Variations in collection instructions limit our ability to achieve some of our standard analyses, and limits the ability to fully realize the vision with sharing and co-developing scripts
Creating best practices in collection instructions should facilitate additional standardization
Will potentially lead to increased efficiency (site personnel won't have to learn as many collection methods) and fewer queries (less confusion by site personnel)

8. Adverse Events
See Section 10.3 of the AE white paper for outline of some collection topics that impact AE analyses
Our initial thinking: Ideal collection method would tell us what’s going on with the patient (events and at what severity and if serious) during the study from start to finish
Allows for multiple displays (eg, TEAE tables AND patient profile)
Allows for flexibility in TEAE definition
Allows for TE determination in multi-phase studies

10. Symbol for seriousness included

11. Medical History
We should know about all events that are ongoing at the time of study start
Is this predominant industry practice, or do some companies ask for only those that are “relevant”?
For some TE definitions and for the graphical patient profiles, severity of events that start before the study but are still ongoing into the study is required

12. Concomitant Medications
See Section 6.4 of the demographic/disposition/medication white paper
FYI- The white paper will be updated given the changes in expectations for active ingredients and ATC class
Think about the patient profile for individual case reviews!
Project Idea submitted March 2017:
Implementing the WHO Drug B3 Format - Best Practices for Integrated Databases
In a March 2015 Federal Register Notice, the FDA encouraged sponsors to provide World Health Organization (WHO) Drug Dictionary codes for concomitant medication data in investigational studies provided in regulatory submissions.  The request indicated that codes should include the drug product trade name (where available), the active ingredient(s) and the Anatomical Therapeutic Chemical (ATC) class.  As indicated in the May 2015 Data Standards Catalog, the expectation for its requirement begins March 2018.  Additional  information was provided in the October 2015 Study Data Technical Conformance Guide.  Other regulatory agencies have communicated similar notices.    In order to facilitate the population of active ingredients, the Uppsala Monitoring Centre, who maintains the WHO Drug Dictionary, updated the dictionary (B3 and C3 formats) to improve the structure for multi-ingredient drugs.  While this change will greatly improve the efficiency of reviewing, analyzing, and reporting medication data, it introduces several challenges when creating an integrated database.  Hence, this project team will create a white paper outlining best practices for creating an integrated database with medication data collected in different formats (B2 and B3 formats).  The goal would be to complete the white paper by the end of 2017, in time for the regulatory requirement for implementation by March 2018.

13. Pregnancy
Companies want to track pregnancies, but collection seems to vary
AE or not AE?
Pregnancy an option in disposition?
Seems like an easy place to achieve some consistency!

14. Reasons for Treatment and Study Discontinuation
See Section 6.3 of the demographic/disposition/medication white paper
For analyses, we want reason for treatment AND reason for study discontinuation (can and should be different in many cases) for each phase (ie, epoch)
Submission Data Standards (SDS) subteam worked out solutions for having multiple disposition events per epoch and how to handle the situation when multiple drugs are given in a study and a subject discontinues only a part of the regimen (will be reflected in SDTM version 3.3)
The choices for discontinuing study should be limited
National Research Council 2010, O’Neill and Temple 2012
R T O'Neill and R Temple. The Prevention and Treatment of Missing Data in Clinical Trials: An FDA Perspective on the Importance of Dealing With It. Clinical Pharmacology & Therapeutics (2012); 91 3, 550–554. doi: /clpt
The Panel on Handling Missing Data in Clinical Trials; National Research Council. The Prevention and Treatment of Missing Data in Clinical Trials. National Academies Press, 2010 <