The platform

The infrastructure layer
pharma R&D has been missing.

Reprosia is not a reporting tool. It is the AI-native foundation that makes pharmaceutical analyses trustworthy, reproducible, and submission-ready by design.

Architecture

How the platform
fits together.

Three layers: your existing R environment, the Reprosia AI audit engine, and regulatory-ready output. No migration required.

Layer 1
Your R Environment

Existing scripts, packages, data pipelines. RStudio, Posit, CI/CD. No change required.

Layer 2
Reprosia AI Engine

Audit, validate, lock, certify. AI-powered compliance scanning and environment management.

Layer 3
Regulatory Output

eCTD-ready packages, IQ/OQ/PQ docs, CDISC outputs, estimand documentation.

Platform pillars

Three pillars of
analytical integrity.

01 — Validate

Your environment,
certified.

AI-assisted IQ/OQ/PQ validation of your R environment and packages. Every function call, parameter, and result documented automatically with cryptographic audit trails compliant with 21 CFR Part 11 and GxP requirements.

  • Installation Qualification (IQ) — system and package verification
  • Operational Qualification (OQ) — function behaviour testing
  • Performance Qualification (PQ) — end-to-end workflow validation
  • Tamper-evident audit trail with digital signatures
  • User-attributed action logging with timestamps
  • Automated validation report generation for agency review
21 CFR Part 11 GxP IQ/OQ/PQ reproducr regulog
# Audit script for behavioural risks
library(reproducr)
report <- audit_script("analysis.R")
Files scanned: 1
Calls detected: 23
risks <- risk_score(report)
HIGH: 0 MEDIUM: 1 LOW: 2
# Certify outputs and detect drift
certify(outputs=list(coefs=coef(model)), tag="v1")
certified 3 output(s) under tag 'v1'
check_drift(outputs=list(coefs=coef(model)), against="v1")
Verdict: ALL OUTPUTS MATCH
02 — Reproduce

Results that
don't drift.

Consistent reproducibility across environments, teams, and time. Locked package versions, containerised execution, and continuous drift monitoring ensure your analysis at database lock is traceable and verifiable at submission.

  • Environment snapshots and lockfiles at any analysis stage
  • Continuous drift detection — alerts on any environmental change
  • Cross-site reproducibility for multi-centre trials
  • Hash-verified script and data integrity
  • Containerised execution for submission reproducibility
  • Historical replay — re-run any analysis from any point in time
Environment lock Drift detection lineager reproducr
# Certify outputs at database lock
certify(
outputs = list(
coefs = coef(model),
r_squared = summary(model)$r.squared
),
tag = "DBL",
script = "analysis.R"
)
certified 2 output(s) under tag 'DBL'
# At submission — check for drift
check_drift(
outputs = list(coefs = coef(model), r_squared = summary(model)$r.squared),
against = "DBL"
)
Verdict: ALL OUTPUTS MATCH
OK: 2 Drifted: 0
03 — Submit

Submission packages
built to pass.

Regulatory-ready outputs for FDA and EMA submissions. CDISC-compatible data structures, ICH E9(R1) estimand documentation, and pre-built eCTD templates — generated directly from your existing R analysis pipeline, with full traceability back to source data.

  • SDTM and ADaM compatible output generation
  • ICH E9(R1) estimand specification documentation
  • eCTD-ready submission package assembly
  • Define.xml and reviewer's guide generation
  • Full lineage from raw data to submission dataset
  • FDA and EMA reviewer-friendly output formats
CDISC ICH E9(R1) eCTD estimandr bayprior
# Define estimand (ICH E9R1)
library(estimandr)
define_estimand(
population = "ITT",
variable = "HbA1c change",
ice_strategy= "hypothetical",
summary = "mean difference"
)
certify("submission")
eCTD package: ready
CDISC validation: passed
Define.xml: generated
Submission ready for FDA
Workflow

From first line of R to
approved submission.

01

Connect your environment

Integrates with existing R workflows in minutes. Works alongside RStudio, Posit Workbench, and CI/CD pipelines. No migration required.

reproducr regulog
02

AI audits your pipeline

Automatic scanning for reproducibility risks, undocumented dependencies, environment drift, and compliance gaps — before they become submission failures.

lineager estimandr
03

Lock, certify, document

Freeze your environment at database lock. Generate automated IQ/OQ/PQ validation documentation and full audit reports ready for agency review.

IQ / OQ / PQ
04

Package and submit

One command to generate your eCTD-compatible submission package. Full audit trail, reproducibility proof, and regulatory documentation included.

FDA EMA ICH
Integrations

Works with your
existing stack.

Reprosia wraps around your existing R infrastructure. No rip and replace.

R
Base R & Tidyverse
Full support for R 4.x and all tidyverse packages
IDE
RStudio / Posit
Native RStudio add-in and Posit Workbench integration
CI
GitHub Actions
Automated validation in CI/CD pipelines
SAS
SAS Bridging
Equivalence testing for SAS to R migration
BAY
bayprior
Bayesian prior elicitation and regulatory reporting — FDA 2026 aligned
Compliance coverage

Every requirement,
covered.

Built against real regulatory requirements from the ground up.

Standard Coverage Feature
21 CFR Part 11FullElectronic records, audit trail, digital signatures, access controls
ICH E9(R1)FullEstimand specification, intercurrent event strategies, SAP documentation
GCP / GLPFullGood Practice workflow integration, validation SOPs, change control
CDISC SDTMFullStudy data tabulation model output, define.xml, reviewer's guide
CDISC ADaMFullAnalysis dataset model, ADSL, ADAE, ADTTE derivation tracking
eCTDFullModule 5 statistical output packaging, bookmarking, hyperlinking
EMA GuidelinesFullCHMP statistical guidelines, conditional approval requirements
GDPRCommittedEU-based operation, privacy-by-design approach, data subject rights on request
Early access

Ready to see Reprosia
in your environment?

We work directly with pharma and biotech teams. Request early access and we'll be in touch within 48 hours.

Or reach us at team@reprosia.com