Extended Risk-Based Monitoring Model, On-Demand Query-Driven Source Data Verification, and Their Economic Impact on Clinical Trial Operations

Conclusions:
(1) High-risk sites (identified via analytics) do not necessarily require a higher percent SDV. While high-risk sites require additional resources to assess and mitigate risks, in many cases these resources are likely to be allocated to non-SDV activities such as GCP, training, etc. (2) It is not necessary to combine SDV with the GCP compliance monitoring. Data validation and query management must be at the heart of SDV as it makes the RBM system more effective and efficient. Thus, focusing SDV effort on queries is a promising strategy. (3) Study size effect must be considered in designing the monitoring plan since the law of diminishing returns dictates focusing SDV on "high-value" data points. Relatively lower impact of individual errors on the study results leads to realization that larger studies require less data cleaning, and most data (including most critical data points) do not require SDV. Subsequently, the most significant economy is expected in larger studies.

Source: Therapeutic Innovation and Regulatory Science - December 30, 2015 Category: Drugs & Pharmacology Authors: Tantsyura, V., Dunn, I. M., Waters, J., Fendt, K., Kim, Y. J., Viola, D., Mitchel, J. Tags: Clinical Trials Source Type: research