Clinical R in Practice
The Open-Source Stack Behind Regulated Drug Development
Title page
A practical map of the open-source R stack used in regulated clinical development.
Pharma R is not “R plus some packages” — it is R under a legal reading of traceability, and that framing changes every tool choice. This book maps the whole stack the way it exists in production: the CDISC data chain, the pharmaverse toolchain, regulatory-grade reporting, risk-based validation, and the AI frontier that has to climb the same validation wall.
Author: Jaime Yan · Online practice edition · Free and open
Read the preface Choose a reading path Start at Chapter 1
Five parts, one stack
| Part | Question you will address | After this part you can… |
|---|---|---|
| I — The Lay of the Land | What flows where, who builds the tools, and what switching costs? | Draw the data flow from clinic to regulator and place R at each stage |
| II — The Data Chain | How do standards-compliant datasets get built? | Build ADaM datasets from composable, traceable derivation bricks |
| III — The Reporting Engine | How do datasets become regulatory-grade output? | Choose table tooling with evidence, and speak ARD in a pipeline |
| IV — Engineering Under Supervision | What separates a demo from something QA can sign? | Run a risk assessment, rebuild analyses as replayable pipelines, validate a Shiny app |
| V — The Frontier | What can LLM agents really do in trial programming? | Read capability claims as dated evidence, with the verification wall in view |
Prerequisites
You should be comfortable reading R code — filtering and summarizing data, writing small functions, and following a pipeline. Clinical vocabulary (SDTM, ADaM, TLF) is introduced in Chapter 1, so domain newcomers can start at the beginning. You do not need prior experience with the pharmaverse, validation frameworks, or LLM tooling.
Series, book, and companion volume
Every chapter pairs the series text with exercises and a case study. The selection checklists in each chapter are designed to be stolen for your next validation meeting. See Further reading for the official documentation and standards behind each part.
This is the clinical companion to Modern R in Practice, which teaches the general-purpose R engineering skills this book builds on. Read that one for functions, testing, and delivery craft; read this one for the regulated stack.