Platform Trial Data Management

Overview

Platform Trial Data Management is a reference pipeline for managing data in multi-site, multi-country adaptive clinical trials. It works through transforming messy EDC exports, 125 CSV files across 25 sites in 5 countries, differing in date conventions, decimal separators, character encodings and units, into a frozen, verifiable dataset suitable for analysis, with a synthetic trial of 2,549 participants as the running example.

What it does

• Encodes validation rules as data (YAML), readable by non-programmers
• Harmonises multi-site exports with differing formats and units
• Logs every data transformation for full auditability
• Produces reproducible, checksummed (“frozen”) data cuts
• Reports endpoint uncertainty arising from missing or unresolved data
• Documents where data management ends and statistical analysis begins

The pipeline is built around a synthetic platform trial (3 clinical domains, 24 months enrolment, 23 validation rules, 419 tests) and documented in:

• runbook.md, operational procedures
• data_management_plan.md, governance documentation
• decisions.md, dated design rationale
• validation_plan.md, rule specifications and consequences

Validation

Rule detection performance is measured against injected synthetic defects (overall 99.3% recall on targeted defect records; as low as 74.2% recall for weight unit errors).

Documentation

The repository is a working reference implementation rather than a slide deck: code, YAML rule configuration, and the documentation files above. The statistical analysis itself is explicitly out of scope, the pipeline ends at producing the frozen data cut.

Repository: https://sufyansuleman.github.io/platform-trial-data-management/