While many risk analysis methods describe how execution or performance risks originate and propagate through pharmaceutical and biopharmaceutical manufacturing processes and systems, few provide methods for efficiently estimating the uncertainty of an execution risk’s occurrence. This article describes prospective causal risk modeling (PCRM) for estimating the risk’s uncertainty of failures associated with executing processes, particularly when little process performance information or data is available. Building upon a basic unit of risk, the process-based system risk structure (SRS) approach is combined with PCRM to provide a method of carrying out quality risk management (QRM) exercises that properly assess both the severity and uncertainty of process execution risks. After the risks are structured using an SRS, PCRM provides a straightforward and effective method for using subjective human judgement and thought experiments to evaluate the risk process’s causal mechanisms for analyzing, evaluating, and controlling the uncertainty, including its likelihood of occurrence, of significant risks associated with developing and manufacturing pharmaceuticals. Using an SRS/PCRM-based QRM exercise, a wide variety of process execution risks can be efficiently evaluated and accepted or rejected so that important risks requiring mitigation can be identified for additional evaluation, control, and eventual acceptance.
Tag: <span>system risk structure</span>
Biopharmaceutical manufacturing process risks can be described as a network of processes that may include some combination of unit operations, equipment, instruments, control systems, procedures, and personnel practices. The system’s risks can be modelled by a system risk structure (SRS) that describes how threats originate and flow through the network to result in negative consequences (risks). The SRS is a quality risk management (QRM) tool a team of subject matter experts can use to prospectively identify and evaluate a wide variety of risks over the product’s entire development and manufacturing lifecycle. Based on the understanding developed from an SRS analysis, control strategies can be developed by modifying or adding new processes to mitigate the threats, thus reducing the likelihood of the risk consequence being realized. The SRS tool extends the ICH Q9 QRM approach described in a series of articles. Two examples are used to demonstrate how an SRS can be assembled and then used to prospectively identify, understand, and reduce significant risks by controlling the source and flow of threats within the systems described…