Risk-Based Monitoring and Fraud Detection in Clinical Trials Using JMP and SAS
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If you're someone working in the life sciences, you know data quality can be a real challenge. The development of quality pharmaceuticals that meet industry standards is extremely complex, and stakeholders must closely monitor clinical trial data to ensure quality and accuracy. Is it bad data, or is it fraud?
Risk-based monitoring makes use of a central computerized review of clinical trial data and site metrics to determine if and when clinical sites should receive more extensive quality review or intervention. The analytical methods covered in this chapter empower clinical trial teams to take a proactive approach to data quality and safety, streamlining clinical development activities and addressing shortcomings in ongoing studies.
Download this chapter for an overview of best practices in monitoring and fraud detection.
In it, expert Richard Zink touches on:
- The need to innovate the data review process for clinical trials.
- The importance of data standards.
- Navigating changing guidelines, standards and practices for clinical trial monitoring.
- Techniques and software that will modernize the process of fraud detection.