Assuring Data Integrity in Clinical Research eLearning Course

Course Summary

Pharmaceutical, biotechnology and medical device companies and clinical researchers need to assure regulatory authorities of the reliability of the data that they generate during product development and testing - that is, to demonstrate data integrity. Practices that provide assurance of data integrity in clinical research are required by law and/or established as expectations in regulatory guidance. The data are reviewed in regulatory applications or during regulatory inspections of clinical trial sponsor and investigational sites. Inadequacies of data integrity are frequently reported by inspectors and result in regulatory actions against the organizations or individuals concerned.

This course explains the requirements and describes principles and practices that should be followed by trial sponsors, investigators and other clinical research personnel to assure regulators of data integrity.

Who will benefit from this module?

This module provides essential learning for all healthcare professionals participating in clinical research, and all clinical development staff of medicinal products and medical device manufacturers

Learning Objectives

• Describe basic principles of data integrity assurance
• Comply with regulatory requirements and good practices for the assurance of paper-based data in clinical research
• Comply with regulatory requirements and good practices for the assurance of electronic data in clinical research

Module Outline

Key topics covered in this module include:

• Data integrity definitions and fundamentals

  What do we mean by data?; What is data integrity?; ALCOA, ALCOA+ and ALCOA++; Source data and metadata; Transcription and transformation of data; Static and dynamic data; Certified copies; Archiving and retention; Validation of computerized systems; Data governance; Safeguarding of blinding; Regulators’ responses to data integrity failings

• Integrity of paper-based data

  Document control; Recording data by hand; Correcting handwritten data; Submitting paper CRFs to sponsor; Storage, archiving and retention of paper records

• Integrity of electronic data

  Electronic source data and originators; Entry of data to an eCRF; Calibration of instruments; Remote data acquisition; Restrictions on access to computerized systems; Manual data entry; Verification of data; Audit trails and other metadata; Modifications and corrections; Review and sign-off of data; Protection of data; Storage, backup and archiving; Data transfer and migration; Electronic signatures

• Assessment
  Multiple-choice assessment.