Further Reading: The Standards and the Stacks Behind Them

This reading map points to the official documentation, standards bodies, and community resources behind each part of the book. Follow an entry when the corresponding problem arises, and return with a small artifact of your own — a rebuilt dataset, a checklist adapted to your shop, a qualification memo draft. You do not need to finish any of these resources before starting the chapters here.

Standards and governance (Part I)

CDISC standards. The CDISC library is the authoritative source for SDTM, SDTMIG, ADaM, and ADaMIG. The chapters in this book teach you to navigate these documents, not to memorize them. Read with a question: which of your shop’s conventions is actually a standard, and which is a house rule that calcified? Write down three of each; the distinction matters at audit time.

The pharmaverse. pharmaverse.org maintains the curated package map that Chapter 2 walks through, including each package’s maintainers and maturity. Read with a question: for the three packages your pipeline depends on most, who owns them, and what is the succession plan if a maintainer steps back?

R Consortium working groups. The Submissions Working Group publishes the pilot submissions that proved R-generated deliverables can pass through regulatory doors. Chapter 3 cites these as evidence; reading the primary sources lets you argue migration from documents, not anecdotes.

The data chain (Part II)

admiral. The admiral documentation — especially the function reference grouped by derivation family — is the companion reference for Chapter 4. The admiral* extension packages (admiralonco, admiralvaccine, and others) show how the same brick pattern specializes per therapeutic area. Read with a question: which three derivations in your current study would benefit most from being rewritten as named bricks?

metacore and xportr. The metacore and xportr documentation covers the spec-as-code workflow of Chapter 5. Read with a question: where does your define.xml disagree with your datasets today, and which side is wrong? The metacore checks in the chapter are the fastest way to find out.

Reporting (Part III)

rtables, gt/gtsummary, flextable. The official docs — rtables, gt, gtsummary, flextable — are the references behind the Chapter 6 showdown. Do not read all four; read the one the chapter’s decision tree points you to, and revisit when your constraints change.

cards and the ARD standard. The cards documentation defines the analysis-results-data format of Chapter 7. Read with a question: which of your recurring tables could be regenerated from a stored ARD instead of re-run from raw data, and what would that save at QC time?

Quarto. The official Quarto guide — parameters, project execution, and freeze — underpins Chapter 8. Read with a question: when a data cut changes, which layers of your CSR pipeline should re-run, and which must provably not?

Validation and engineering (Part IV)

R Validation Hub. The R Validation Hub publishes the white paper that Chapter 9’s risk framework operationalizes, plus the riskmetric and riskassessment tooling. This is the closest thing the field has to a shared vocabulary for “fit for use” — cite it in your qualification memos.

targets. The targets manual is the reference for Chapter 10, especially the chapters on debugging and on what invalidates the cache. Read with a question: which target in your pipeline is silently over- or under-invalidated, and how would you prove it?

rhino and GxP Shiny. The rhino documentation covers the scaffold of Chapter 11. Pair it with Mastering Shiny’s chapters on the reactive graph and modules when the app’s behavior, not its structure, is what needs defending.

The frontier (Part V)

Part V’s sources are deliberately perishable, and each frontier chapter carries its own last-verified date and in-text citations. Treat the vendor and tool claims there as a snapshot. The durable reading for this part is Part IV: the verification wall does not move, even as the tools climbing it do.

The companion volume

Modern R in Practice covers the general-purpose engineering foundation this book assumes: functions, iteration, testing, debugging, packaging, dashboards, and AI workflows outside the regulated context. Its clinical reading path ends roughly where this book begins.

Sources and use

Links point to the official sites of the respective projects and organizations, checked on 2026-09-30. Package documentation and standards documents retain their own licenses and terms. The reading guidance and questions on this page are original to this book and published under CC-BY-SA 4.0.