Data Quality & Cleaning

CDM Data Quality Application

A CDM-aligned workspace for issue detection, prioritization, traceability and data-driven review

CDM Data Quality Application product preview

What it does

It is a practical CDM review workflow. • Helps reviewers quickly understand what needs attention, where the issue sits, and who should review it. • Connects summary metrics directly to subjects, sites, domains, rules and source records. • Keeps rule-driven detection, raw-data traceability and AI-assisted exploration in one application. • Creates a common review language across CDM Core, Clinical, Medical Monitor, Coding and Local Lab. • Consolidates business-rule findings into one consistent issue-level view.

Problem solved

Pharma companies typically take a long time to review and resolve clinical issues, especially when they involve multiple domains (EDC, Central Labs, Third-party data). They also have challenges to manage the data quality from the CRO.

Best suited for

Small and Mid-sized Pharma companies

Typical use

Pharma companies can use the CDM data quality tools to quickly identify data issues

Deployment

Consulting Supported

Implementation

A practical view of what it may take to use this product in your environment.

Implementation requirements

  • AWS or Azure server
  • * A Windows server
  • * A Database server
  • * An R and R-Shiny Server

Technical considerations

None specified.

Compliance & validation

Product information below is creator-supplied unless ClinExchange explicitly states otherwise.

21 CFR Part 11

Not assessed
A marketplace listing is not a regulatory certification. Sponsors remain responsible for assessing fitness for intended use, validation, and applicable regulatory requirements.

Validation & review information

  • Validation available: No / not stated
  • Security review available: No / not stated

Creator

TL

Thomas Leung

President · TMC Software Inc

Thomas has 30+ years of clinical and statistical analysis experience in the Pharmaceutical Industry. He led TMC in developing clinical data management and monitoring tools to improve clinical development. He also helped clients recruit seasoned Biometric resources, including Biostatisticians, Statistical Programmers, and Clinical Data Managers.