Abstract Versus Concrete Risk Identification in Clinical Research in Japan: Randomized and Prospective Pilot Research on the Effect of Risk Reduction Activities in a Risk-Based Approach

Ther Innov Regul Sci. 2024 Oct 28. doi: 10.1007/s43441-024-00702-w. Online ahead of print.

Abstract

Background: The risk-based approach (RBA) of clinical trial was first introduced in 2011-2012. RBA necessitates implementing risk reduction activities that are proportionate to risk in order to reduce avoidable quality issues. However, there is no consistent methodology or research for identifying and evaluating risks and planning risk reduction activities. We aimed to evaluate risk reduction activities and their effects by using two risk identification and evaluation methods.

Methods: Among the risk identification and evaluation methods, we selected one method with the lowest number of categories for identifying risks [risk assessment form (RAF)] and one with the highest number [risk assessment tool (RAT)]. Each method was used to identify and evaluate risks in and plan risk reduction activities for the research on ponatinib blood concentration and treatment outcome in patients with chronic phase chronic myelogenous leukemia. RAF and RAT can identify risk using abstract questions and a list of concrete risks, respectively. The sites were randomized into two groups to implement planned risk reduction activities using RAF and RAT and to compare the mean of errors and protocol deviation per subject visit between the two groups.

Results: The mean of errors per subject visit and the mean of protocol deviation per subject visit were lower in the RAF group than in the RAT group.

Conclusions: Our study indicates that risk reductions can be successfully implemented by using a method to identify and evaluate risks in a small number of abstract categories that are critical to quality of clinical research.

Keywords: Quality management system; Risk evaluation; Risk identification; Risk reduction activities; Risk-based approach; Risk-based quality management.