Clinical data work rarely breaks down in a single task. It breaks down in the spaces between tasks, such as:
- Manual exports
- Pipelines that are rebuilt every study
- Files passed around in email threads
- Jumping to a separate tool every time someone needs to visualize a result
Each handoff adds setup, and setup adds risk.
The Atorus Fall 2026 Products Release helps close those gaps. Across Ageirein™ and OpenVal®, it advances a core idea: one configured environment where your study team follows the data from intake to insight without leaving the system.
Ageirein is the environment your team works in. OpenVal is the validated R package foundation. The two are standalone products but also complementary, and this release strengthens both.
One environment for your clinical data workflow
This release extends Ageirein across clinical data workflow, so the path from data intake to submission-ready output stays inside one configured environment.
Pull data straight from the systems you already run
New EDC connections pull data directly from major EDC systems including Medidata Rave and Veeva Vault into Ageirein in a single action. Clinical data management teams get the snapshots they need, and biometrics teams get data extracts before and after database lock.
The outcome is a shorter path from EDC to analysis, with one less rebuilt export standing between your team and clean, current data.
Keep the study team in one project
R, SAS®, Python, and Shiny all run inside the environment, work stays in one project and one dataset while each role keeps the tools they require.
Ageirein Files brings a familiar file browser into the platform. Data managers and reviewers navigate the file system, move data, and preview files, all under the access controls set in Ageirein Projects. Files also move data in and out, for example through Egnyte, so external files reach the right destination folder. For teams that have been stitching a clinical data repository together across shared drives, this lets governed file work happen in one place.
Application linking connects hosted visualization apps and Shiny dashboards to a specific study. Administrators set access in a few clicks, and users open the dashboard straight from the Ageirein Project they are already in.
That shared space – project – is what transforms clinical data analytics from a multi-legged relay between systems into one continuous piece of work
- Data managers browse, preview, and review data
- Statisticians and statistical programmers run R, SAS®, and Python
- Clinical reviewers open linked visualization applications without switching platforms
Automate R and SAS® pipelines end to end
Ageirein Flow now runs combined R and SAS® steps in a single workflow. Production runs that used to consume a whole workday complete in one hands-off pass, executing scripts in dependency order and, in parallel, from start to finish.
Flow Migration adds independent file promotion, so statistical programming teams move exactly the files they choose between stages: development ® testing ® production. This keeps versioning tidy across the study life cycle and makes every promotion a deliberate, traceable step.
A validated R package foundation for clinical data analytics
OpenVal is the validated R package foundation for any organization running open-source R in a regulated setting – as a standalone product and as part of the Ageirein™. Not a CRAN mirror. Not a framework to run. Not a tool to configure. Packages and evidence, ready to use on day one.
Package and dependency management is one of the biggest blockers to running open-source R at scale under GxP. Around three quarters of packages change version in a year – and OpenVal removes that maintenance burden with a growing library of validated, GxP-ready open-source R packages, maintained and re-validated with every release.
This release brings the library to 700+ validated packages and their dependencies, covering packages for datasets, tables and figures, statistical methods, survival and missing data, Bayesian and dose-finding, PK/PD, interactive results, and utilities and metadata. Every package arrives risk-assessed, tested, and ready to use, with the package validation work already done.
Most frameworks tell you a package passed. Atorus tells you why – examining the package and its dependencies, resolving issues directly with authors, and excluding anything that falls short of regulatory standards. Under the hood, a rebuilt validation kit and updated test execution make each release rigorous than the last.
See what Ageirein and OpenVal can do for your team
Talk with Atorus about bringing one configured environment to your clinical data analytics workflow, from data intake through submission-ready output.
Frequently asked questions
The release covers Ageirein and OpenVal. Ageirein gains in-platform file management with data transfer, direct EDC connections, linked visualization application inside projects, combined R and SAS® runs in Ageirein Flow and independent file promotion. OpenVal expands its validated open-source R package library and strengthens the validation process underneath it.
Existing Ageirein customers receive the update through the standard release process. Reach out to your Atorus contact for details. OpenVal customers receive access instructions by email following the release.
Clinical data management, biometrics, and statistical programming teams see the most immediate value, along with clinical reviewers who work in linked visualization applications. Teams standardizing on a single statistical computing environment across R, SAS®, and Python benefit across the board.
Yes. Direct connections pull data from major EDC systems into Ageirein in one action, giving data management teams snapshots and biometrics teams the extracts they need before and after database lock.
OpenVal explains why each package passes, not just that it passed. Every package and its dependencies are examined, issues are resolved with authors, and packages that fall short of regulatory standards are kept out – giving your submissions a foundation you can defend in an audit.