The Evolution of Source Data Verification and Risk-Based Quality Management in Driving Clinical Trial Data Quality
Clinical trial complexity is increasing exponentially with the surge in complex trial methodologies adoption
This paper examines the impact of SDV on a wide-reaching study and how reducing SDV would positively impact data quality, data integrity, compliance, and costs.
As a result, biotech and pharmaceutical companies are seeing increasing operational efficiencies, improved assessments for risks and critical quality factors with more impactful data management and trial outcomes.
You will learn:
- about designing quality into study protocols & processes.
- to adopt Risk Based Monitoring practices for evolving regulatory recommendations.
- how a world leading biotech transitioned from reduced monitoring to true RBQM.
SDV Defined:
Source Data Verification is the process of ensuring that the data reported for analysis accurately reflects the source data at the clinical trial site–a comparison of source data against the Case Report Form (CRF) data (transcription errors). SDV predominantly detects random errors.