RBM – Risk-based monitoring
Risk-Based Monitoring to Ensure Data Quality in Clinical Trials
Risk-Based Monitoring moves away from the traditional approach of frequent on-site visits and 100% source data verification (SDV), toward centralized data collection and monitoring to enhance the quality of clinical trial data and to reduce overall costs.
Risk-based monitoring solutions improve the quality and accuracy of clinical trial data, increase operational efficiency, and reduce regulatory submission risk. Risk-based monitoring solutions are aligned with monitoring recommendations set out by the FDA, EMA and ICH E6 R2 Guidance.
As advised in the FDA Guidance for Industry Oversight of Clinical Investigations — “A Risk-Based Approach to Monitoring ”, there is a growing consensus that risk-based approaches to monitoring focusing on the most critical data elements are more likely to ensure subject protection and overall study quality and will permit sponsors to monitor the conduct of clinical investigations more effectively. The EMA has also issued a similar reflection paper.
› FEWER ERRORS – LOWER COST – BETTER ANALYSIS – MORE TIMELY CLINICAL TRIALS RESULTS
IDDI can provide a full range of Risk-Based Monitoring options
- By partnering with other clinical CROs to provide on-site monitoring
- By assessing data quality with or without the use of independent statistical monitoring tools, like the one marketed by IDDI’s sister company, CluePoints
- By using our EDC system for central data review
- By providing Key Risk Indicators, alongside the sponsor’s trial management tools
“Key Risk Indicators (KRIs) are obviously important, but the guidance also points out that you can use a more comprehensive statistical approach to interrogate the data, and this is exactly what our sister company CluePoints is doing. In fact, if you look at the FDA guidance, it explicitly states that you can target on-site monitoring by identifying higher risk clinical sites with findings that may or may not be related to critical data. So, that means that even non-critical data may be indicative of data problems, and, therefore, a statistical approach that looks at the totality of the data is crucial in addition to KRIs.” Marc Buyse, Scientific Officer, IDDI .