What are some advantages of Process Analytical Technology (PAT) in cleaning when transitioning from the lab to online?
Process Analytical Technology (PAT) guidance is a nonbinding FDA document that aims to encourage innovation in cGMP manufacturing. The key advantage of PAT is building quality into products. This is accomplished with robust design, reliability, and ease of use. Advantages of PAT allow for quality by design, demonstrated validation, process understanding, and process control.
Understanding and controlling a cleaning validation program means identifying all variables, managing those variables from the process itself, and accurately and reliably predicting important quality attributes. From there, the process can be controlled and adjusted to maintain a desired, validated state. Programs that demonstrate a high degree of process understanding and control have inherent quality gains. Understanding the process life cycle is important and allows for continuous improvement and data collection. These data can then be used to justify post-approval changes, troubleshooting, or optimization.
Moving from lab to online allows for gains in time, resources, equipment utilization, and efficiencies. The components of sampling, laboratory analysis, and results reporting are replaced with seamless, real-time data reporting. Not only is this a time and resource savings, but it removes the variability of human interaction with samples and analyses. With real-time release, the desired quality attributes are ensured through continuous monitoring. Data can be used to reflect the continuous validated state of the process.
What are some of the change control and validation considerations when moving to online?
To use PAT to its full potential, in-process measurements, test controls, and process end points must be validated. Without proper validation, the value of real-time data is lost.
Equivalency studies/comparability protocols from laboratory to online highlighting the verification and implementation approach are needed. A full method development and validation may not be necessary, but it is important to have a documented implementation strategy for demonstrating equivalency. From there, assess any discrepancies, if applicable. For example, perhaps results are slightly different from lab to online due to a change in temperature or the change in sample handing. Observed changes may be acceptable for the method transfer; however, these types of variances need to be acknowledged and assessed.
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Consider where your data are going if moving to online. A database? Site SCADA? Whatever the choice, the data transfer must be validated. Demonstrate that data are being transferred, reported, and stored per the specification.
Will you be using your data to trigger alarms or automation, such as a reclean or stopping the cycle? If so, alarming or automation should be tested and documented.
You may be using the same or similar method, but this is still a new instrument. Sievers Validation Support Packages I, II, and III are great resources to ensure proper installation, operation, performance, and software qualification of the new instrument. This will give you confidence walking into an audit to defend the validation.
How can data be used to gain a comprehensive assessment of cleanliness?
How many successful validation runs does it take to demonstrate a successful process? Often the magic number is three. But is this enough to give confidence over time? Using the data to continuously demonstrate validation allows for confidence and control of the cleaning validation program. Not only do the data continuously demonstrate validation, but they can provide insight for troubleshooting and process optimization.
Assuming proper validation, data can be used to assess overall cleanliness as well as to troubleshoot and optimize the process. Process monitoring and process control are intended to allow for maintaining a desired state of validation. What are your critical process attributes contributing to product quality? Once you have identified those, design measurement processes that allow for real-time monitoring. Next, establish process controls you can adjust to allow for control of your defined critical process parameters. Lastly, understand and document the relationship between your data and what that means for overall product quality. This is what is meant by building quality into products.
How do data management and Data Integrity tie into cleaning validation?
While the FDA encourages PAT implementation, it will maintain its usual scrutiny and tailor it to the technology. It is important to understand what makes for a compliant process. PAT implementation needs to be able to stand up to the same level of interrogation as any other cGMP process. Data generation and data management practices need to be clearly defined and compliant to Data Integrity regulations.
Data Integrity starts with the degree to which data are complete, consistent, and accurate. These attributes of data must be true and maintained through the lifecycle of the data. Do your data stand up against the requirements of ALCOA+? If so, then that is a good place to start. From there, design your internal approach to Data Integrity to at the very least comply with Data Integrity principles set forth by the FDA. A key component of compliance to Data Integrity is compliance to 21 CFR Part 11. If implementing PAT, electronic records and electronic signatures will be an important element of that process. This is where understanding and complying to 21 CFR Part 11 becomes imperative to successful implementation.
Are there any limitations with online TOC monitoring?
The only notable limitation encountered when moving from laboratory to online for cleaning validation is the restrictive nature of analyzing swab samples. Because the M9 will be directly integrated into the CIP skid, there will be constant flow of either WFI/PW or rinse sample from the cleaning process flowing to the instrument. The online flow can be stopped to analyze one swab sample at a time via the vial port. Due to the fixed position and sample throughput capabilities of online configuration, it may not be efficient or convenient for analysis of numerous swab samples.
Other scenarios that may require additional engineering may depend on your flow rate, pressure, available volume of rinse sample, and timing of rinse sample. For example, the iOS on the Sievers M9 requires a minimum pressure and volume of sample. If collecting from a gravity drain off a CIP skid, this may be difficult to accomplish without a solution unique to each set up. Whether it is time, pressure, or volume limitations, there are customized solutions for M9 TOC and CIP skid integration. For more information, tune in to our next webinar or browse our library of cleaning validation resources.