ICPE Pre-Conference Course

Let’s git it started

Janick Weberpals, RPh, PhD
jweberpals.academic@gmail.com

August 23, 2025

Welcome to ICPE 2025

Meet Your Faculty

Janick Weberpals,
RPh, PhD Associate Director, Oncology Data Science & AI, AstraZeneca

Shirley Wang,
PhD Associate Professor, Brigham & Women’s Hospital, Harvard Medical School

Anna Schultz
PhD, MSc Assistant Professor, London School for Hygiene and Tropical Medicine

John Tazare,
PhD Assistant Professor, London School for Hygiene and Tropical Medicine

Disclosures

Disclosure

  • Janick Weberpals is an employee at AstraZeneca and own shares in AstraZeneca. The views and opinions expressed in this presentation are those of the author and do not necessarily reflect the official policy or position of AstraZeneca. The author is presenting in a personal capacity.

Warm up survey

What is your background?

  • Epidemiology
  • Biostatistics
  • Pharmacy/Pharmacology
  • Medicine
  • Health Services Research
  • Computer Science
  • Other

Which sector are you working in?

  • Academia
  • Industry
  • Regulatory/HTA
  • Tech
  • Other

How far did you have to travel to D.C.?

  • North America
  • South America
  • Europe
  • Middle East
  • Asia
  • Africa
  • Oceania

Have you ever worked with git or any other system to version-control your analytic code?

  • Yes
  • No

Have you ever shared your own code via git?

  • Yes
  • No

Have you ever re-used someone else’s code?

  • Yes
  • No

Introduction to the topic

Transparency and reproducibility standards across the RWE lifecycle

Study conceptualization and pre-specification using HARPER1

Figure 1: HARPER protocol template

Study implementation
guidelines, training and engagement are lacking in non-interventional healthcare research community

Figure 2: Study implementation resources are still lacking (illustration generated by ChatGPT).

Study reporting
guidelines like RECORD(-PE)2 and STROBE3

Figure 3: RECORD(-PE) study reporting
Figure 4: STROBE study reporting

Our agenda today

Time Topic Instructor Description
14:30 - 14:40 Welcome and introduction Janick Weberpals Welcome, housekeeping, and introduction to the topic
14:40 - 15:00 DESIGN STAGE: HARPER template Shirley V. Wang A harmonized protocol template to enhance reproducibility of hypothesis evaluating real-world evidence studies on treatment effects (HARPER protocol)
15:00 - 16:10 ANALYSIS STAGE: Git and GitHub Anna Schultze, John Tazare Introduction to the Git distributed version control system and remote repositories (e.g., GitHub) to track changes, collaborate, disseminate and archive analytic source code through dedicated project repositories that maintain a complete audit trail of all relevant study documents including code lists. This will be followed by interactive case study for part in which every course participant can try git hands-on.
16:10 - 16:40 COFFEE BREAK - Take a break and enjoy a tasty coffee
16:40 - 17:20 ANALYSIS STAGE: Github Copilot Janick Weberpals, Anna Schultze, John Tazare Introduction to AI-based tools to support and augment code development, quality control, transparency and reproducibility
17:20 - 17:50 REPORTING STAGE: Quarto introduction Janick Weberpals Introduction and examples of literate programming using the Quarto technical reporting system
17:50 - 18:00 COURSE CONCLUSION Janick Weberpals Future direction and trends & resources for where to go to learn more

Course materials

You can find all course materials, setup instructions and further useful resources at:

https://janickweberpals.github.io/icpe-git-2025/

Figure 5: Landing page of ICPE 2025 course website.

PDS Special Issue

Figure 6: PDS Special Issue on Transparency and Reproducibility in Pharmacoepidemiology4

Technical Setup

…

Course focus

What this course is about

  • Giving recommendations on how to enhance transparency and reproducibility across different stages of a RWE study implementation
  • What to consider when pre-specifying your study design and analyses
  • Version control of analytic code and computational reproducibility
  • Making your study report more transparent to others & future you

What this course is NOT about

  • Any specific programming language
  • Statistical programming language bootcamp
  • Any specific study design or statistical analysis considerations

Why is this important?

Increasing expectations and policies from various stakeholders regarding the provenance, sharing and audit trial of study documents including analytic code

  • Regulatory

“Sponsors should ensure that RWD and associated programming codes and algorithms submitted to FDA are documented, well-annotated, and complete, which would allow FDA to replicate the study analysis using the same dataset and analytic approach” (FDA5)

  • Publishing

“We will make code sharing mandatory too.” (BMJ6)

References

1.
Wang SV, Pottegård A, Crown W, et al. HARmonized protocol template to enhance reproducibility of hypothesis evaluating real-world evidence studies on treatment effects: A good practices report of a joint ISPE/ISPOR task force. Value in Health 2022; 25: 1663–1672.
2.
Benchimol EI, Smeeth L, Guttmann A, et al. The REporting of studies conducted using observational routinely-collected health data (RECORD) statement. PLoS medicine 2015; 12: e1001885.
3.
Von Elm E, Altman DG, Egger M, et al. The strengthening the reporting of observational studies in epidemiology (STROBE) statement: Guidelines for reporting observational studies. International journal of surgery 2014; 12: 1495–1499.
4.
Wang SV, Pottegård A. Advancing research transparency and reproducibility in pharmacoepidemiology. Pharmacoepidemiology and Drug Safety 2025; 34: e70096.
5.
US food and drug administration. Considerations for the use of real-world data and real-world evidence to support regulatory decision-making for drug and biological products. 2023. Available at: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/considerations-use-real-world-data-and-real-world-evidence-support-regulatory-decision-making-drug.
6.
Abbasi K. A commitment to act on data sharing. BMJ 2023; 382: p1609. Available at: https://www.bmj.com/content/382/bmj.p1609.