The Growth of Phase IV Trials and the Need to Demonstrate Effectiveness Using Electronic Patient Reported Outcomes Patient centricity is now at the forefront of drug development, from early understanding of Burden of Disease through to Comparative Effectiveness Research and the use of Real World Data to generate evidence on the patients’ perspective of outcomes […]
The Evolution of Source Data Verification (SDV), Source Data Review (SDR), and Risk-Based Quality Management (RBQM) in Driving Clinical Trial Data Quality Explore the transformation of source data verification (SDV) and source data review (SDR) in clinical trials, driven by the increasing adoption of risk-based quality management (RBQM). Traditional approaches, such as 100% SDV, are
Rethinking Your Imaging Strategy Most people involved in medical imaging are aware of the recent upheavals in the industry. Sponsors know that changes to their key Imaging relationships may be imminent. Anticipating these changes and properly handling them may well have an impact on your trial. The current state of the clinical trial imaging industry
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RBQM: The Connective Tissue for Data Quality Risk-Based Quality Management (RBQM) is a strategic approach to overseeing the quality and integrity of clinical trials by focusing on identifying and mitigating risks throughout the study process. This method enhances the efficiency and accuracy of clinical trials by prioritizing critical data and processes that directly impact patient
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A (R)evolutionary Path for Data Managers The complexity of clinical trial data management has surged over the past decade. Data managers are navigating unprecedented challenges in capturing, processing, and analyzing explosive volumes of data from an increasing variety of sources. The new data landscape directly impacts their ability to ensure data quality, implement procedures to
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Picture This: Hassle Free Imaging in Clinical Trials The field of imaging has undergone a dramatic evolution. Today, the entire process is growing ever more efficient, compliant, and accurate with the help of Artificial Intelligence (AI), integrated systems, and unified solutions. These advances are optimizing workflows, reducing timelines, and improving visibility to, and control of,
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