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Comparative Studies | Food Technology | India | Volume 10 Issue 2, February 2021
Risk-based Monitoring and Data Integrity in Clinical Research
Abstract: Today's clinical trials landscape is being shaped by macro trends that include the Covid-19 pandemic, geopolitical uncertainty, and climate pressures. Meanwhile, advancements in adaptive design, personalization and novel treatments mean that clinical trials are more complex than ever. Sponsors seek greater agility and faster time to commercialization while maintaining quality and safety in an evolving global market. Across every stage of clinical research, AI offers optimisation opportunities. Patient recruitment is typically the most time-consuming stage of a clinical trial. Sponsors must find and identify a set of subjects, gather information, and use inclusion/exclusion criteria to filter and select participants. And high-quality patient recruitment is vital to a trial's success. Once patients are recruited, they must be managed effectively. Patient retention has a direct impact on the quality of the trial?s results, so their management is crucial. In today?s clinical trials, these patients can be distributed over more than a hundred sites and across multiple geographies, presenting huge data management challenges for sponsors.
Keywords: Risk-based monitoring, data integrity, clinical trials, predictive analytics, anomaly detection, risk assessment, monitoring strategies, targeted interventions.
Edition: Volume 10 Issue 2, February 2021,
Pages: 1698 - 1704