Open-source · Regulated · Reproducible
ReproStats builds open-source R packages and provides specialist consulting for teams that need their analyses to be reproducible, auditable, and regulation-ready — from clinical trials to pharma manufacturing.
Open-source packages
All packages are free and open source. Production-ready tools ship to CRAN; packages in active development are available from GitHub.
Audit R scripts for reproducibility risks — breaking package changes, missing seeds, locale-sensitive operations. Certify outputs and detect drift across runs and environments.
DocumentationTamper-evident, hash-chained audit logging for R applications operating under 21 CFR Part 11 and EU Annex 11. Built for GxP Shiny deployments with full IQ/OQ/PQ validation documentation.
GitHubRow-level data provenance for dplyr pipelines. Tracks where every row in your analysis dataset came from and what happened to it — answering the audit question regulators actually ask.
GitHubICH E9(R1) estimand framework for clinical trials. Specify intercurrent event strategies, generate submission-ready estimand tables, and scaffold sensitivity analyses in a tidy R API.
GitHubConsulting
We help pharma, biotech, and clinical research teams deploy R safely in regulated contexts — from GxP Shiny applications to regulatory submission support.
Deploy R and Shiny in GxP-compliant environments. System validation, 21 CFR Part 11 audit logging, and user access controls built in from the start.
Independent audit of R analysis pipelines against reproducibility risk criteria — package versions, stochastic functions, locale sensitivity, and output certification.
Validation documentation for R packages used in regulated contexts. Requirements traceability, qualification scripts, and summary reports ready for regulatory inspection.
ICH E9(R1) estimand framework implementation for clinical trials. Pre-specification of intercurrent event strategies, sensitivity analyses, and submission-ready estimand tables.
Statistical equivalence validation for teams migrating from SAS to R. Formal equivalence testing across methods and formal documentation for regulatory submission.
Workshops on R in regulated environments — reproducible workflows, package version management, audit logging, and regulatory submission best practices.
Who we work with
Our packages and consulting are designed for contexts where analytical results have real-world consequences.
Pharma & Biotech
Clinical statisticians
Reproducible clinical trial analyses, estimand specification, and regulated Shiny deployment.
Regulatory affairs
Submission teams
Package validation documentation, audit trails, and R-to-SAS equivalence for FDA/EMA submissions.
Research
Academic & CRO teams
Reproducible pipelines, output certification, and drift detection for long-running studies.
About ReproStats
R is becoming the standard for statistical analysis in clinical trials and pharmaceutical research. But the infrastructure for using R in regulated environments — audit logging, reproducibility certification, estimand tooling — barely exists.
ReproStats was founded to close that gap. We build the open-source packages the R community needs for rigorous, regulation-ready work, and we offer the consulting expertise to implement them correctly in the environments where they matter most.
All our core packages are open source and free. We believe good scientific infrastructure should be a public good.
Whether you need a package, a validation document, or a full implementation — we can help.
Get in touch