What are the steps for managing risks in validation and verification projects?

Risk assessment defines the extent of qualification needed, For example, Analytical Instrument Qualification (AIQ) must be on a scientific basis based on risk, USP divides Analytical Instrument to three groups: Group A: Devices do not give values that can be measured or calibrated. Vverification by visual observation of its operation (Magnetic Stirer). Group B: Devices povide measured values that monitored physical parameters that need calibration (temperature, pressure, or flow)(Balance, water bath). Group C: Automated analytical devices and systems where the functional, operating and performance requirements are specific to the analytical application. They are calibrated through functional and performance tests (HPLC).

Although primarily the risk assessment is driven impact on by 3 basic areas such as patient safety, product quality and data integrity, a structured framework mandated to capture risk assessment ensures lesser chances of missing hidden risks. An organisation should develop a framework around risk management that covers key aspects of risks. The framework should cover risks related to the supplier, business process, functional risks, data security risks, personal data or GDPR related risks, access related risks, data backup and retention related risks, risks involved in regulated process, automation related risks wherever applicable, novelty of systems or solutions, deployment related risks, user management related risks.

While calculating the risks in GMP prospective, we should always consider patient safety, product quality and data integrity.

The Risk analysis is to identify all the hidden or evident risks associated with a process or a system by evaluating the likelihood of occurrence, it's impact and the detectability of the risks. This helps to prioritize the risks based on the severity. However, the most challenging part in risk analysis is that it solely depends upon the individual biases that may be either due to the lack of data, unable to understand the data or the biased interest. Hence, collaboration approach, fostering a cross functional team and experts from different areas is very important for the adequate risk analysis that further helps to define a risk mitigation strategy, and monitoring.

Risk mitigation plan should focus on reducing the risks associated with the process or the system, negating its impact to the possible lowest level and increasing the detectability. This may involve developing the control processes, either technical or procedural that can be regularly monitored for the effectiveness of the risk mitigation strategy.

Before Risk analysis (1st step), we should choose and involve SMEs in that particular area of interest. Analysing the risk for documentation purpose may not solve the purpose. In my opinion, most of the times risk assessment will be conducted to fulfil audit/regulatory compliance.

Staying current with industry standards ensures project alignment with the latest methodologies, anticipating challenges. Fostering continuous improvement involves learning from past projects—analyzing successes and failures to refine processes and boost efficiency. Documenting lessons learned creates a valuable knowledge base, aiding decision-making and preventing recurring issues. Integrating these practices fosters a culture of adaptability, enhancing the resilience and success of future validation and verification projects.

If this is a new process or method that you are bringing into the facility, don't be afraid to embark on additional training or engineering and mock runs to boost the team's confidence and as a dry run to expose any remaining roadblocks that could compromise your validation or verification runs.