Clinical Data Automation

From clinical data to submission-ready evidence—faster.

Automate the work between raw clinical trial data and regulatory analysis outputs without giving up control. Healytex combines AI-assisted data standardization, metadata-driven ADaM and TLF generation, continuous quality checks, and experienced biometrics specialists in one traceable workflow.

CDISC-native Human-verified Traceable by design Built for regulated clinical workflows

The last mile of clinical data is still too manual.

Clinical teams collect more data from more vendors than ever, but the path from database extracts to standardized datasets and analysis outputs still depends on fragmented specifications, repetitive programming, handoffs, and late-stage QC.

That creates avoidable rework exactly when timelines matter most.

Study Data Pipeline — Status Overview
DomainStatusFindings
DMComplete0
AEIn Review3
LBComplete0

One workflow from source data to analysis outputs.

Unify Data

Bring every source together

Bring EDC, laboratory, eCOA/ePRO, imaging, safety and specialty-vendor data into a governed study workspace with clear lineage.

Accelerate SDTM

AI-assisted mapping

Use AI-assisted mapping and reusable sponsor standards to move source data into CDISC SDTM with expert review and controlled execution.

Generate ADaM

Traceable analysis datasets

Turn approved SDTM and analysis specifications into traceable analysis datasets while preserving derivation logic and provenance.

Build TLFs

Configuration-driven outputs

Create tables, listings and figures from controlled analysis metadata and reusable output templates—without rebuilding routine programming for every iteration.

Validate Continuously

Quality before the crunch

Run quality, conformance and sponsor-specific checks throughout the workflow so issues are surfaced before the submission crunch.

Deliver with Experts

Biometrics extension team

Add experienced data managers, biostatisticians and statistical programmers as an extension of your team when you need hands-on execution.

Source to submission—every step traceable.

Describe the data path precisely: source/raw data → SDTM → ADaM → analysis results/TLFs → submission artifacts.

Raw data

Source Data

EDC, labs, eCOA, imaging, vendors

SDTM

Standardized

CDISC domains & metadata

ADaM

Analysis-Ready

Derivations & populations

TLFs

Analysis Outputs

Tables, listings, figures

Submission

Submission

Datasets, define, packages

Automation where it helps. Human judgment where it matters.

1

Connect your study data

Ingest structured and selected unstructured data from your clinical ecosystem.

2

Review intelligent mappings and specifications

The platform proposes standards mappings and transformation logic with confidence and context for expert review.

3

Generate standardized and analysis-ready outputs

Approved specifications drive repeatable SDTM and ADaM processing and configured analysis outputs.

4

Validate as you go

Automated rules, sponsor standards and QC workflows identify issues early and retain the evidence behind each resolution.

5

Package and deliver

Produce controlled datasets, metadata, documentation and analysis outputs for your regulatory submission workflow.

Built for evidence, not demos.

Clinical automation only matters when sponsors can trust the result. Healytex keeps the mapping, derivation, version, validation finding, resolution and approval history connected.

Your team can see how an output was produced, who approved it, and which rules were applied.

SOC 2
ISO 27001
Traceability — ADaM.ADSL Derivation
StepSourceApproved By
Mapping v2.1DM.SUBJIDJ. Analyst
Derivation v1.4ADSL.TRT01PS. Statistician
QC Check #847Population flagPassed
Version lock2026-08-15DM Lead

Sponsors building submission-ready evidence

Healytex gave us a single view of our data pipeline from vendor extracts through SDTM and ADaM. We caught mapping issues weeks earlier than our previous process.

VP
VP Biometrics
Global Pharmaceutical Sponsor (name withheld)

The traceability story was what sold us. Every derivation, every approval, every QC finding—connected. That's what regulators and our internal QA team need to see.

HD
Head of Data Management
Mid-Size Biotech Sponsor (name withheld)

Common questions

No. The platform is designed to reduce repetitive manual programming and support multiple execution approaches while preserving the specifications, transformations and evidence needed for regulated work. Sponsors can retain SAS where required and introduce other validated technologies where appropriate.
No. AI-assisted features can propose mappings and specifications, but regulated study decisions should be reviewed and approved by qualified users. Approved specifications drive controlled, reproducible processing.
No responsible vendor can guarantee an agency outcome. We design and deliver work to applicable study-data standards and sponsor requirements, maintain traceability and validation evidence, and support the sponsor's submission-readiness process.

Bring us one difficult study.

We'll map the current workflow, identify the manual and quality bottlenecks, and show where automation can compress the path to analysis and submission deliverables.

Request a Submission Acceleration Assessment