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Software for the work of clinical research

We support biometrics, clinical programming, and data management teams across the full path from collected data to a regulatory filing.

Clinical Trial Analytics

See your study clearly while it runs

Safety signals and data quality issues are easier to act on when teams can explore them directly. We build review applications that let medical monitors, data monitoring committees, and study teams work with current trial data without waiting on static reports.

  • Patient profiles and safety dashboardsSubject level views that bring labs, adverse events, and exposure together.
  • Risk based and central monitoringSite level metrics that surface where attention is needed.
  • Pharmacovigilance reviewTools that help safety teams track and assess signals.

Typical outcomes

  • Faster decisionsReview meetings work from live data rather than week old extracts.
  • Fewer surprisesQuality issues are caught during the study, not at database lock.
  • Shared understandingClinical and data teams look at the same numbers.

Standards we work to

  • SDTMStandardized tabulation of collected study data.
  • ADaMAnalysis datasets that trace cleanly to SDTM and source.
  • Define.xmlMachine readable metadata that documents your data.
CDISC Data Standards

Clean, traceable study data

Getting from collected data to compliant SDTM and ADaM datasets is detailed work. We build pipelines driven by metadata and specifications, so the same study can be rebuilt the same way every time.

Traceability runs through the whole process. Any analysis value can be followed back to the record it came from, which makes review and inspection straightforward.

Tables, Listings, and Figures

Reporting that holds up to review

Clinical study reports rest on tables, listings, and figures that have to be correct and reproducible. We build reporting pipelines that produce submission ready output and carry quality control through every step.

  • Reusable output catalogsStandard displays your teams can apply across studies.
  • Submission ready formatsOutput prepared for inclusion in the filing.
  • Double programming supportIndependent checks built into the process.

Why it matters

When reporting is reproducible, a late data change does not mean starting over. The pipeline reruns, the quality checks repeat, and the output is ready again in a fraction of the time manual reporting would take.

What we deliver

  • Reproducible packagesCode and data bundled for review.
  • Transport filesDatasets in the formats authorities expect.
  • Pinned environmentsContainers that reproduce results exactly.
Regulatory Submissions

Filings reviewers can reproduce

A submission is more convincing when a reviewer can rerun it. We prepare packages that follow the practices proven in the recent regulatory pilots, including interactive review applications delivered through the electronic gateway.

The goal is a filing that is complete, traceable, and easy to inspect, which keeps reviews moving and questions to a minimum.

Read about the submission pilots

The platform underneath the work

Analytics in a regulated setting needs an environment that can be qualified, documented, and trusted.

Validated Computing Environments

We stand up qualified R and Python platforms with the controls regulated analytics requires.

  • Validated infrastructure on cloud or on premises
  • Package qualification with documented evidence
  • Audit trails, access control, and 21 CFR Part 11 readiness

Migration and Modernization

Many teams want to move beyond legacy programming languages without disrupting active studies.

  • Assessment of current code and processes
  • Staged migration that keeps studies running
  • Training so your teams own the result

Tell us where your studies need help

Whether it is a single workflow or a portfolio wide change, we can map a practical path forward.

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