README

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regulog

Every analytical action taken in a consequential R environment should be documented — who did it, what they did, when, and why. In practice, almost none of it is.

regulog fills that gap. It records every action, change, note, and decision into a tamper-evident, hash-chained audit trail stored as newline-delimited JSON. Every entry is attributed to a named user, time-stamped in UTC, and linked to the previous entry via SHA-256 — so any modification after the fact, however subtle, is detectable by verify_log().

Works for regulated pharmaceutical environments (21 CFR Part 11, EU Annex 11), internal data pipelines, multi-user Shiny applications, and any context where accountability and traceability matter.

Installation

# Install from GitHub
pak::pak("repro-stats/regulog")

Quick start

library(regulog)

# Initialise a session
log <- regulog_init(
  app     = "primary-analysis",
  version = "1.0.0",
  user    = "analyst",
  path    = "logs/audit.rlog"
)

# Log actions, changes, and decisions
log_action(log,
  action = "data_read",
  object = "adsl.sas7bdat",
  reason = "Reading ADSL for primary efficacy analysis"
)

log_change(log,
  object = "alpha",
  field  = "value",
  before = "0.05",
  after  = "0.025",
  reason = "Updated per protocol amendment 2"
)

log_note(log,
  "Outlier in subject 01-042 retained per SAP section 8.3 —
   discussed with medical monitor 2026-06-20"
)

# Log data reads, scoped to a block — read() is logged automatically
with_log(log, {
  adsl <- read(haven::read_sas, "data/adsl.sas7bdat")
  adae <- read(haven::read_sas, "data/adae.sas7bdat")
})

# Apply an electronic signature
log_signature(log,
  "I certify this analysis is accurate and complete per SAP version 2.0")

# Verify tamper integrity
verify_log(log)
#> regulog: Log intact: 5 entries, chain unbroken

# Query the log
filter_log(log, type = "SIGNATURE")
filter_log(log, action = "data_read", from = "2026-06-01")

# Export for submission
export_audit_trail(log, format = "csv", signed = TRUE,
                   path = "outputs/audit_trail.csv")

Key functions

The hash chain

Function	Purpose
`regulog_init()`	Initialise an audit logging session
`log_action()`	Log a discrete action
`log_change()`	Log a before/after field change
`log_note()`	Log a free-text annotation or analytical decision
`log_signature()`	Apply an electronic signature
`rl_read()`	Explicit, logged read of any data source
`with_log()`	Scoped convenience: `read()` calls inside the block log automatically
`verify_log()`	Verify SHA-256 hash chain integrity
`filter_log()`	Query entries by type, user, action, or date
`export_audit_trail()`	Export to CSV or JSON, with optional signing
`regulog_shiny_init()`	Initialise inside a Shiny server function
`regulog_observer()`	Auto-log Shiny reactive input events

Any modification to any field in any entry breaks the chain from that point forward. verify_log() recomputes every hash and reports the first broken link — and works offline from the .rlog file, without an active R session.

Entry types

Validation

Deploying any software in a regulated environment requires documented evidence that it is installed correctly, operates as specified, and performs reliably under real-world conditions. This is the IQ/OQ/PQ qualification process required under 21 CFR Part 11, EU Annex 11, and GAMP 5 before a tool can be used in GxP workflows.

Type	Created by	Purpose
`ACTION`	`log_action()`	Discrete events: reads, runs, approvals
`CHANGE`	`log_change()`	Before/after field modifications
`NOTE`	`log_note()`	Decisions and free-text rationale
`SIGNATURE`	`log_signature()`	Named, dated, meaningful sign-off

regulog ships pre-written, executable qualification protocols. Instead of authoring validation documents from scratch — a process that typically takes weeks of internal effort — your team runs three commands and receives a complete, signed qualification record:

source(system.file("validation/IQ_regulog.R", package = "regulog"))
source(system.file("validation/OQ_regulog.R", package = "regulog"))
source(system.file("validation/PQ_regulog.R", package = "regulog"))

Each protocol is self-contained and produces a pass/fail summary against explicit acceptance criteria:

Protocols are version-controlled alongside the package and updated with every release that affects qualified behaviour.

The qualification record produced by each run — including the platform, R version, date, and pass/fail status — can be retained as documented evidence of system qualification in your validated environment.

Regulatory coverage

Protocol	What it covers	Tests
IQ — Installation Qualification	R version, package installation, dependency integrity, file system access	10
OQ — Operational Qualification	All 21 CFR §11.10 requirements: hash chain, tamper detection, user attribution, timestamps, export, signatures	26
PQ — Performance Qualification	End-to-end clinical workflows: data review, regulatory export, multi-user sessions, 500-entry load test, inspector query simulation	7

Regulation	Clause	Coverage
21 CFR Part 11	§11.10(e)	Hash-chained, time-stamped, user-attributed entries
21 CFR Part 11	§11.10(b)	`export_audit_trail()` CSV and JSON
21 CFR Part 11	§11.100	`log_signature()` signer identity
21 CFR Part 11	§11.200	Signature components: identity, timestamp, meaning
EU Annex 11	Clause 9	Date, time, user, action on every entry
EU Annex 11	Clause 11	`verify_log()` periodic integrity evaluation

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.