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Risk-Based Approaches - Best practices for ensuring clinical data quality

  • 10 September 2013
  • Author: Webmaster1
  • Number of views: 1546
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Risk-Based Approaches - Best practices for ensuring clinical data quality

Companies engaged in commercial clinical research have, since the introduction of formalized good clinical practices (GCP), adopted highly defensive practices around the monitoring of clinical trials.  The reasons, while diverse, include fear based on perception and interpretation of regulatory requirements. These processes have played a very large role in the high costs associated with clinical trials, without delivering commensurate value.  Reasons are many, but surely include propagation of practices established during the years that trials relied on paper-based case report forms (CRFs) without considering optimization of the processes to take advantage of the technology provided by electronic data capture (EDC).  All of this has resulted in the institutionalization of high cost, unproven value, manpower-intensive practices that do little to serve the interests of subject safety or quality data.  Pharmaceutical, biotech, and medical device industries experiencing unprecedented economic upheaval can no longer justify practices that deliver little value at exorbitant cost. Rather than continuing to spend time, energy, and money focusing on minutiae, e.g., the ability of site personnel to properly transcribe observations from one medium to another, those engaged in clinical trial conduct must re-focus their energies on  the aspects of the clinical trial that matter most, such as protocol compliance, subject safety, data timeliness, and data integrity.  Through the use of more up-to-date methodologies and technologies, companies can effectively address these concerns while saving both time and money. This paper addresses the regulatory and business rationales for adopting monitoring-related tools and processes that, if implemented thoughtfully, should deliver higher-quality trial data, faster, and at significantly lower cost.

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