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Pharmaverse: Regulatory Submission Process Flow
Metadata > OAK > Admiral > Define.xml > TLGs (rtf/pdf) > Submissions > Shiny
Pharmaverse Common FAQs - Your Guide to Leveraging Pharmaverse Packages- Where do you start? What is your task/objective?
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- As pharmaverse continues to grow, there are packages for the full clinical trial workflow process:
- Metadata > OAK > Admiral > Define.xml > TLGs (rtf/pdf) > Submissions > Shiny
- Who are the key players?
- Pharma industry leaders setting ‘new standards in R and submissions’ since they are key developers of pharmaverse packages
- Genentech, GSK, Merk, J&J
- CDISC
- PHUSE, Atorus, Appsilon, ProCogia
- Do you have to use all of the pharmaverse packages?
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- No, organizations can choose and priority packages to test and install
- Organizations can continue to use tidyverse and dplyr for in-house developed R scripts
- Which are the top 5 most popular pharmaverse packages?
- How different are pharmaverse packages to tidyverse?
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- Pharmaverse packages are built from up to 50% of tidyverse packages so can easily learn pharmaverse packages
- What methods can I learn and apply pharmaverse packages?
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- R-Guru.com/pharma is a designed for the collecdtion and curation of:
- Videos
- Examples
- Case Studies
- Documentation
- What about pharmaverse shiny apps?
- Why should i use pharmaverse packages?
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- Organizations can save development time, money and SMEs
- Are there risks in using pharmaverse packages?
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- Yes, organizations are responsible for their own risk management
- Pharmaverse packages undergo rigorous tests to help assure robust and reliable results
CDISC Support R Packages- defineR (define.xml - read.me)
- TidyCDISC (Shiny App: Data Reviewer, Table Generation)
- CDISC Pilot Project
Admiral (ADaM in R Asset Library) Package, Workflow, Datasets, Releases, Workshop
- CDISC Hackathon - Recording, Outline
- Github
- YouTube - R/Pharma 2021 Day 1, HOW, Admiral
- Creating ADaM Subject-Level Analysis Datasets (ADSL) with the Pharmaverse: Part 1, Part 2
- Date/Time Functions and Imputation
- Derived_Joined(), Derived_Vars_Joined()
- Questionnaire Domain
- R-Based Submission Package Submitted to FDA [Index, Github, Update]
Github - PhUSE, IQ-OQ [R Scripts]
PHUSE: Data Visualization and Open Source Technology [Site Resource]
Admiral - CDISC Open Source, Example
Roche: Shifting to an Open-Source Backbone in Clinical Trials [Video]
RStudio: Regulatory Compliance and Validation Issues [FDA, Updated Version]
R: Regulatory Compliance and Validation Issues A Guidance Document for the Use of R in Regulated Clinical Trial Environments [FDA, Pilot Project]
tidyverse, tidymodels, r-lib, and gt R packages: Regulatory Compliance and Validation Issues [FDA]
shiny and rmarkdown R packages: Regulatory Compliance and Validation Issues [FDA]
R: Software Development Life Cycle A Description of R’s Development, Testing, Release and Maintenance Processes [FDA, Validation]
Introduction to sendigR [Enable Cross-Study Analysis of CDISC SEND Datasets]
Get Started with {tidyCDISC} [Quick Table Generation & Exploratory Analyses on ADaM-Ish Datasets]
xportr [Utilities to Output CDISC SDTM/ADaM XPT Files]
envsetup [auto source files from full path folders]
logrxpackage - install.packages('logrx')
axecute(my_script.R')
Checklist for CRAN submissions [Auto tests]
Patient Profiles: Introduction, Template
Electronic common technical document submission with analysis using R
R Submissions Working Group [R Consortium]
Auditing Open-source Software Framework in a Regulatory Environment: Challenges, Gaps and Recommendations, Shahrzad Talebian, Rafiq Furniturewala, Thomas Joseph Carpenter, Uday Preetham Palukuru [Presentation]
Revolutionizing SDTM Transformation in Pharma: Introducing {sdtm.oak} – An Open-Source R Package, Rammprasad Ganapathy, Susheel Arkala, Edgar Manukyan [Presentation]
{admiral} - from open source through to company implementation, Ross Farrugia [Presenation]
Exploring R Package Validation in Life Sciences: Appsilon's Collaboration with the R Validation Hub
Exploring the Top 5 pharmaverse Packages [Appsilon Blog, rtables, admiral, teal, riskmetric, tidyCDISC, xportr]
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A Guide to R Package Validation in Pharma [Appsilon Blog, Riskmetric]
Git Gud: Version Control Best Practices [Appsilon Blog]
R XML: How To Work With XML Files In R
Flavors of the pharmaverse [Posit Conference Workshop 2024]
Analyzing change in assessed risk across package releases, Brid Roberts [Presentation]
Software Engineering Good Practices (GSEP) in FDA Submissions - 7 Categories to Follow [Appsilon Blog]
A Guide to R Package Validation in Pharma [Appsilon Blog, Riskmetrics]
Open-Source-in-New-Drug-Applications-NDAs-FDA [Posit Blog, Phil Bowsher]
What is GxP in Clinical Software Development? [Appsilon Video]