Efficient positioning of QTL and Secondary Limit thresholds in a clinical trial risk-based monitoring

Abstract

AbstractIn the high-stakes world of clinical trials, where a company’s multimillion-dollar drug development investment is at risk, the increasing complexity of these trials only compounds the challenges. Therefore, the development of a robust risk mitigation strategy, as a crucial component of comprehensive risk planning, is not just important but essential for effective drug development, particularly in the RBQM ecosystem. This emphasis on the urgency and significance of risk mitigation strategy can help the audience understand the gravity of the topic.The paper introduces a novel framework for deriving an efficient risk mitigation strategy at the planning stage of a clinical trial and establishing operational rules (thresholds). This approach combines optimization and simulation models, offering a fresh perspective on risk management in clinical trials. The optimization model aims to derive an efficient contingency budget and allocate limited mitigation resources across mitigated risks. The simulation model aims to efficiently position the QTL/KRI and Secondary Limit thresholds for each risk to be aligned with risk assessment and contingency resources.A compelling case study vividly illustrates the practical application and effectiveness of the proposed technique. This real-world example not only demonstrates the framework’s potential but also instills confidence in its successful implementation, reassuring the audience of its practicality and effectiveness.