6–9 Jul 2026
Europe/Warsaw timezone

Reproducible Clinical Data Review: A Modular R and Quarto Workflow for Transparent Reporting

7 Jul 2026, 16:10
5m
Lightning Talk (5 minutes) Lightning Talks

Speaker

Mr Winkle Lu

Description

During clinical trials, EDC data must be reviewed regularly — from routine medical review reports to formal audit and inspection scenarios. In these contexts, reviewers do not explore data freely. They follow a predictable, structured process and need a document that clearly records what was seen, under what conditions, and what conclusions were drawn. This core distinction shapes the design philosophy presented in this talk.

This lightning talk introduces a two-layer modular framework built with R and Quarto for clinical data review. The first layer provides pre-built review modules covering demographics, adverse events, medication records, and study endpoints — each encapsulating domain knowledge and visualization logic. The second layer allows reviewers to combine modules and map Case Report Form (CRF) fields through a YAML file, without modifying the main codebase.

A key design decision is to use raw CRF data as input rather than CDISC-compliant datasets. This lowers the cognitive barrier for non-programmer reviewers while maintaining flexibility across different trials.
Every Quarto report produced by this workflow is a decision snapshot: YAML parameters and review conditions are fully preserved, creating a natural record without additional effort.
The workflow will be demonstrated using simulated CRF data, with discussion of practical design trade-offs in programmer-reviewer collaboration settings.

If you used AI tools or services to support the preparation of this submission, please state the name and reason for using each of them.

Claude (Anthropic) — used to support critical thinking and iterative refinement during abstract preparation, helping to strengthen the clarity and completeness of this submission.

Keywords: Please list up to 5 keywords to help us find the right session for your contribution. Quarto, clinical data review, reproducibility, audit trail, visualization
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