The efficacy of validation denotes the extent to which an approved process, system, method, equipment, or cleaning practice – that has already been validated – continues to produce intended results on a regular basis. To show that a process is effective within the context of pharmaceutical manufacturing, one needs to have objective proof that the method does produce the required satisfactory results at a consistent level.
The reason why this distinction is essential lies in the fact that while a validation study is a one-time demonstration, GMP control is a continuous process. Continued Process Verification is defined by FDA as a constant assurance for process control functioning during actual production of products, which relies on the flow of data about processes and products together with accompanying analysis of such data.
For instance, the tablet compression process could be successfully qualified based on acceptable assay, dissolution, hardness and weight variation parameters, but further utilization of these processes after a couple of months can lead to their inconsistency due to frequent deviations in the compression force or increase in weight variations.
Thus, validation should always go hand in hand with routine manufacturing statistics and analysis, deviations, investigations of the OOS/OOT situations, changes, service, calibration and CPV.
On the basis of the validation type, teams may contemplate:
In case of a manufacturing process one can say that effectiveness here means key quality attributes remain within established ranges and critical process parameters remain controlled without any kind of unexpected variability. Cleaning validation effectiveness can mean that the validated process is able to meet its established residue and microbiological limits during routine cleaning. The effectiveness of the analytical method means that it remains suitable for its purpose throughout its use.
It is advisable to carry on data collection and analysis related to the process and the product, thus covering the trends in incoming materials, in-process materials, finished products and process performance.
Review changes in formulation, raw materials, suppliers, equipment, software, utilities, batch size, place of manufacturing, analytical techniques, cleaning agents, operating parameters and life activities. Any change should be subject to validation and change control procedures.
For instance, in regard to a cleaning procedure that demonstrated acceptable levels of residues in the past, if later checks show increased levels of residues on swabs, repeating the same procedure does not solve the issue. The study has to review issues like equipment design, hard-to clean places, operator actions, concentration and holding time of the detergent, temperature, condition of instruments and the method of sampling.
With a HPLC method recurring cases of OOS or OOT may lead to the review of certain aspects such as system suitability, performance of the column, preparation of samples and instrument conditions and trends in historical data.
An inspector may inquire about the means used to ensure that the validated process is still considered to be in control. The answer has to be provided based on objective data; mere claiming that the process was validated is not enough.
Useful evidence may include validation reports, summaries of CPV, reports on trends, reports on deviations, change controls, effectiveness checks of CAPA, inspection and maintenance logs and decisions on the review.
The retraining of operators after incidence of repeated cleaning failures is good but demonstration of the effectiveness is conducted through the use of further achieved performance data. In case the failures continue, the cause can be procedural, related to the hardware, or process-related.
In this case, the validation should be considered as part of the validation process, but not as a final step following the protocol implementation.
An example of this lifecycle approach is the following process:
Validation study --> routine monitoring --> evaluation of trends --> investigation --> CAPA or change if necessary --> reassessment of the validated state.
The best strategy combines validation with CPV, deviations, out-of-specification/out-of-trend process data, change control, maintenance, calibration, complaints, CAPA and risk management. The analysis of all such indicators combined allows QA and Validation groups to identify loss of control at an early stage and to take the necessary actions when needed.
Success in validation is different from effectiveness
A validation process can result in a conclusion indicating that all protocol acceptance parameters have been met and, thus, that the study was conducted meeting all essential requirements. However, it does not mean that the respective control system has been operating efficiently during the production.For instance, the tablet compression process could be successfully qualified based on acceptable assay, dissolution, hardness and weight variation parameters, but further utilization of these processes after a couple of months can lead to their inconsistency due to frequent deviations in the compression force or increase in weight variations.
Thus, validation should always go hand in hand with routine manufacturing statistics and analysis, deviations, investigations of the OOS/OOT situations, changes, service, calibration and CPV.
What evidence should be reviewed?
In order to find out what evidence needs to be considered, my first question will be: “How do you know the validated state is still operational?”On the basis of the validation type, teams may contemplate:
- Processes and product quality trends
- Deviations, out of specifications, out of trend and out of expectations
- Trends in batch rejections, reprocessings and yields
- Complaints and any signals regarding product quality
- Changes affecting equipment, materials, methods or process parameters
- Preventive maintenance and calibration records
- Environmental clean and utility trends
- Cleaning validation and verification data
- Analytical methods
- Continuous process verification and statistics
A practical approach to access validation effectiveness
In any assessment, one needs to start by determining what “effective” means with respect to the validation being studied.In case of a manufacturing process one can say that effectiveness here means key quality attributes remain within established ranges and critical process parameters remain controlled without any kind of unexpected variability. Cleaning validation effectiveness can mean that the validated process is able to meet its established residue and microbiological limits during routine cleaning. The effectiveness of the analytical method means that it remains suitable for its purpose throughout its use.
1. Check performance against predefined requirements
It is important to look for relation between acceptance criteria and actual performance. It is not enough to analyze just success/failure results. Several positive results can show steady moving away from target.2. Evaluate variability of the process
Analysis should be conducted in terms of trends rather than separate batches. Correct statistical tools help to notice shifts or increasing variability that are hard to spot using separate batch results.It is advisable to carry on data collection and analysis related to the process and the product, thus covering the trends in incoming materials, in-process materials, finished products and process performance.
3. Evaluate indicators of quality system
Validation should never be considered independently of the pharmaceutical quality system. If there are continual deviations, issues with equipment, abnormal laboratory results or continuous CAPAs regarding the same process, this should prompt assessment of the validation strategy.4. Reevaluate changes
My first query would be whether the process being analyzed is the same process that has been validated.Review changes in formulation, raw materials, suppliers, equipment, software, utilities, batch size, place of manufacturing, analytical techniques, cleaning agents, operating parameters and life activities. Any change should be subject to validation and change control procedures.
When should effectiveness be questioned?
Effectiveness should be doubted when regular results indicate a pattern of repeated or unanticipated fluctuation despite the fact that individual runs are continued within limits.For instance, in regard to a cleaning procedure that demonstrated acceptable levels of residues in the past, if later checks show increased levels of residues on swabs, repeating the same procedure does not solve the issue. The study has to review issues like equipment design, hard-to clean places, operator actions, concentration and holding time of the detergent, temperature, condition of instruments and the method of sampling.
With a HPLC method recurring cases of OOS or OOT may lead to the review of certain aspects such as system suitability, performance of the column, preparation of samples and instrument conditions and trends in historical data.
What should QA expect during an inspection?
What a QA professional needs to keep in mind is that a successful validation program is expected to ensure that the validation knowledge is linked to the current quality system.An inspector may inquire about the means used to ensure that the validated process is still considered to be in control. The answer has to be provided based on objective data; mere claiming that the process was validated is not enough.
Useful evidence may include validation reports, summaries of CPV, reports on trends, reports on deviations, change controls, effectiveness checks of CAPA, inspection and maintenance logs and decisions on the review.
Validation effectiveness and CAPA
CAPA quality and significance is crucial at the time of validation failures and/or continuous occurrence of deviation. Closing CAPA based on the implementation of a corrective measure differs from actually proving that it worked.The retraining of operators after incidence of repeated cleaning failures is good but demonstration of the effectiveness is conducted through the use of further achieved performance data. In case the failures continue, the cause can be procedural, related to the hardware, or process-related.
Maintain validation throughout the lifecycle
Validation practices today are based on the lifecycle concept. According to the FDA, process validation consists of the following three stages: the process design, the process qualification and the continued process verification. A similar message is contained in ICH documents, where the focus is also on lifecycle knowledge, risk management and continuous assessment of process performance.In this case, the validation should be considered as part of the validation process, but not as a final step following the protocol implementation.
An example of this lifecycle approach is the following process:
Validation study --> routine monitoring --> evaluation of trends --> investigation --> CAPA or change if necessary --> reassessment of the validated state.
The best strategy combines validation with CPV, deviations, out-of-specification/out-of-trend process data, change control, maintenance, calibration, complaints, CAPA and risk management. The analysis of all such indicators combined allows QA and Validation groups to identify loss of control at an early stage and to take the necessary actions when needed.
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