Process validation is required by cGMP regulations to ensure that process consistency and the ensuing product conforms to
product requirements. A risk-based approach to process validation helps to identify crucial control parameters that affect
product quality. The authors outline different risk-assessment tools, such as Failure-Mode-Effect Analysis (FMEA) and Fault-Tree
Analysis (FTA) to evaluate the crucial factors and parameters affecting product quality, potential failure points, and the
probablity of occurrence for each unit. The authors also review risk assessments performed on different cases from industrial
FDA defines process validation as establishing documented evidence to provide a high degree of assurance that the specific
process will consistently generate a product that meets predetermined specifications and quality characteristics (1). The
International Conference on Harmonization Guideline Q7A defines process validation as "the documented evidence that the process,
operated within established parameters, can perform effectively reproducibly to produce an intermediate or API meeting its
predetermined specifications and quality attributes" (2).
These requirements are essential as they ensure the production of a safe product that minimizes the risk to patients. Risk
analysis in process validation promises to minimize process risk. Risk-assessment tools help to define the process and identify
crucial areas and/or steps in that process, areas of risk and/or hazard, and critical control points (3). Performing risk
assessment of scale-up and/or manufacturing process is recommended as well. The entire risk-management team should include
experts from multiple disciplines to ask the following questions:
- What can go wrong in the process?
- How frequently can it occur?
- What are the consequences if this process goes wrong?
The information obtained from the risk analysis will only be useful, however, if the input is appropriate. The results from
the risk assessment often dictate the number of unit operation steps needed to reduce specific risks to acceptable levels.