Difference between revisions of "Open Source Technologies in Clinical Research"

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|Recruit Volunteers || July 1st 2019  
 
|Recruit Volunteers || July 1st 2019  
 
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|Deliverable – Community Priority Pulse Survey ||30Jul to 30Aug
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|Deliverable – Paper Presentation || US PhUSE Connect 2020 (March 2020)
 
|Deliverable – Paper Presentation || US PhUSE Connect 2020 (March 2020)

Revision as of 10:15, 18 August 2019


Project Overview

Mission Open Source Technologies in Clinical Research aims to provide guidance to the use of open source technologies in regulatory environments within the pharmaceutical industry, including but not limited to R and Python. Our intent is to be a repository of knowledge for:
• Use Cases
• Implementation and validation guidance
• Best Practices

Our goal is to broaden the acceptance and general level of comfort with these technologies in the industry to assist in increasing their level of adoption.

Scope As open source languages and tools become more common across the data science landscape, opportunities to leverage these tools grows as well. Open source languages tend to be on the cutting edge, among other things enabling teams to explore the latest statistical techniques. R and Python are also prominent in the world of big data, connecting into powerful tools like Spark and Hadoop for distributed computing. Both of these languages also have impressive packages available in the world of machine learning and deep learning, bringing modern analytical tools to programming teams at little or no cost. Furthermore, R offers Shiny and R Markdown as advanced reporting tools enabling delivery of static or dynamic data dashboards. At the most basic levels, Python offers automation capabilities – and it is likely already available in most programming environments. These technologies have very much to offer, before even getting close to considering them as an organization’s submission or reporting language of choice.

This project will investigate the methods an organization can use to ensure the thoughtful use of these tools within regulatory environments. These methods will include the proper installation and deployment of open-source languages, validation of frameworks and packages used in development and analysis, quality control of in-house software development, and assurance of GxP compliance. Topics will be discussed at a higher level, veering the basic concepts behind techniques for installation deployment, and validation, as well as the specifics of how these things can be put into practice. The project will walk through proper installation the choice of development environment, and the implications of those choices. The risks of misunderstand what these tools can do given the environment they have been implemented in can be subtle and result in unexpected failures of applications, therefore proper validation is essential within a regulated space

The third element of this project involves the provision of best practices and guidelines that practitioners can use as resources when working with open source technologies in clinical research. One example will develop PhUSE specific coding style guides for open source programming languages, built on Google’s R Style guide, the tidyverse style guide, or for Python, the PEP-8 Style Guide. Most clinical programming departments have well defined Good Programming Practices (GPP) for SAS programming, as does PhUSE, and adoption of open source languages in the pharmaceutical industry will require similar guidance. A second example will provide guidance around the identification of common packages or common repositories that are determined safe to use within a programming environments when reporting on clinical trials, leveraging the work already being done by PharmaR. Furthermore, a clear understanding of packages selection and version control is essential to this process. The open source nature of these technologies, juxtaposed against the high standards of validation within the industry, necessitates the establishment of a trust mechanism for any open source element of the technology.

Project Leads

Name Role Organisation Deliverable Sub-team
Gayathri Kolandaivelu Steering Committee / Sub-Team Lead JNJ Community Priority Pulse Survey
Frank Menius Steering Committee Covance Inc
Eli Miller Steering Committee Covance Inc
Michael Rimler Steering Committee GSK
Michael Stackhouse Steering Committee / Sub-Team Lead Covance Inc US Connect 2020

How to Get Involved

We have an All Hands Call on the First Tuesday of every month at 11am Eastern Time (New York).

A link to the meeting can be found here: https://global.gotomeeting.com/join/742139861

The all hands meeting is open to all who want to attend.

Please contact the Steering Committee to be added to the calendar invite, mailing list, and other resources. ostcr.leads@phuse.eu

Sub-teams will have meetings as needed and set by the team leads. Please contact sub-team leads to participate in projects.

To propose a new Sub-team or project please contact the steering committee ostcr.leads@phuse.eu and attend the All Hands Call.

Project Updates

Community Priority Pulse Survey

US Connect 2020

Objectives and Timelines

List proposed project deliverables and timelines.

Recruit Volunteers July 1st 2019
Deliverable – Community Priority Pulse Survey Aug
Deliverable – Paper Presentation US PhUSE Connect 2020 (March 2020)

Meeting Minutes


March 21st, 2019
April 4th, 2019
April 18th, 2019

Recent Meeting Minutes and recordings are collected on the PhUSE Teamwork application. Please contact the steering committee ostcr.leads@phuse.eu to become involved with the project and added to the Teamwork application and other resources.

Helpful Links

Slack Workspace: For informal discussions within our community. Please email the steering committee ostcr.leads@phuse.eu for access.
PharmaSUG

Project Members

Delivery Sub-Teams: 1 Community Priority Pulse Survey; 2 US Connect 2020


Clinical Programming

Name (Organisation) Name (Organisation)
James Kim (Pfizer) Benno Kurch (Covance)
Frank Menius Steering Committee (Covance) Gayathri Kolandaivelu Steering Committee (JNJ) 1
Harivardhan Jampala (Covance) James Gunter (Covance)
Matthew Travell (GSK) Michael Rimler Steering Committee (GSK) 2
Michael Stackhouse Steering Committee (Covance) 2 Nicholas Masel (JNJ)
Sonakshi Shankar (OCS Life Sciences for Danone Nutricia Utrecht) Tulasi Marrapu (GSK)
Yuichi Nakajima (Novartis)

Other

Name (Organisation) Focus Area
Andy Nicholls (GSK) Statistical Data Sciences
Brian Di Pace (GSK) Clinical Statistics
Eanna Kiely (ClinBuild) Data Standards Governance
Eli Miller Steering Committee (Covance) Data Management
Terek Peterson (YPrime) 2 Clinical Analytics & Data Strategies

Unspecified

Name (Organisation) Name (Organisation)
Aldir Medeiros Filho Bruce Wienckowski (GSK) 2
Hanming Tu (Frontage) Hatim Qais (FDA)
Jorine Putter Kristy Lauderdale (CSG)
Niels Gronning (SAS) Nurcan Coskun
Russell Gibson (CROS NT) Sangram Parbhane
Tatiana Scetinina (AstraZeneca) V Ashwin (GSK)
Walter Jessen (LabCorp) Yufei Du (GSK)