REGULATORY IMPACT ON OOS
- Stability study required
- OOS should be reported to RA
- OOS batch should not be sold to the Regulatory market
- OOS batch can not be blended with a fresh approved batch
- OOS batch can not be directly sold to the market
Reporting Test Result Result: Averaging Appropriate Inappropriate Outlier Reporting
Interpretation of investigation results
- The QA is responsible for interpreting the results of the investigation
- The initial OOS result does not necessarily mean the subject batch fails and must be rejected.
- OOS results should be investigated, and the findings of the investigation, including retest results, should be interpreted to evaluate the batch and reach a decision regarding release or rejection.
- Where an investigation has revealed a cause, and the suspect result is invalidated, the result should not be used to evaluate the quality of the batch or lot
- Where the investigation indicates an OOS result is caused by a factor affecting the batch quality (i.e., an OOS result is confirmed), the result should be used in evaluating the quality of the batch or lot. Reporting
- A confirmed OOS result indicates that the batch does not meet established standards or specifications and should result in the batch’s rejection.
For inconclusive investigations — in cases where an investigation
(1) does not reveal a cause for the OOS test result
(2) does not confirm the OOS result The OOS result should be given full consideration in the batch or lot disposition decision.
In the first case (OOS confirmed), the investigation changes from an OOS investigation into a batch failure investigation, which must be extended to other batches or products that may have been associated with the specific failure.
If no laboratory or calculation errors are identified in Phase I and Phase II there is no scientific basis for invalidating initial OOS results in favor of passing retest results. All test results, both passing and suspect, should be reported (in all QC documents and any Certificates of Analysis) and all data has to be considered in batch release decisions.
If the investigation determines that the initial sampling method was inherently inadequate, a new accurate sampling method must be developed, documented, reviewed, and approved by the Quality Assurance responsible for the release.
Consideration should be given to other lots sampled by the same method.
An initial OOS result does not necessarily mean the subject batch fails and must be rejected. The OOS result should be investigated, and the findings of the investigation, including retest results, should be interpreted to evaluate the batch and reach a decision regarding release or rejection which should be fully documented.
Disposition of Batch
In those cases where the investigation indicates an OOS result is caused by a factor affecting the batch quality (i.e., an OOS result is confirmed), the result should be used in evaluating the quality of the batch or lot. A confirmed OOS result indicates that the batch does not meet established standards or specifications and should result in the batch’s rejection and proper disposition. Other lots should be reviewed to assess impact.
For inconclusive investigations — in cases where an investigation:-
(1) does not reveal a cause for the OOS test result and
(2) does not confirm the OOS result
The OOS result should be given full consideration (most probable cause determined) in the batch or lot disposition decision by the certifying QP and the potential for a batch-specific variation also needs considering.
Any decision to release a batch, in spite of an initial OOS result that has not been invalidated, should come only after a full investigation has shown that the OOS result does not reflect the quality of the batch. In making such a decision, Quality Assurance/QP should always err on the side of caution.
Concluding The Investigation
The results should be evaluated, the batch quality should be determined, and a release decision should be made by the QCU. • The SOPs should be followed in arriving at this point.
Once a batch has been rejected, there is no limit to further testing to determine the cause of the failure so that corrective action can be taken. Reporting
The validity of averaging depends upon the sample and its purpose. Using averages can provide more accurate results.
For example, in the case of microbiological assays, the use of averages because of the innate variability of the microbiological test system. The kinetic scan of individual wells, or endotoxin data from a number of consecutive measurements, or with HPLC consecutive replicate injections from the same preparation (the determination is considered one test and one result), however, unexpected variation in replicate determinations should trigger investigation and documentation requirements.
Averaging cannot be used in cases when testing is intended to measure variability within the product, such as powder blend/mixture uniformity or dosage form content uniformity.
Reliance on averaging has the disadvantage of hiding variability among individual test results. For this reason, all individual test results should normally be reported as separate values. Where averaging of separate tests is appropriately specified by the test method, a single averaged result can be reported as the final test result. In some cases, a statistical treatment of the variability of results is reported. For example, in a test for dosage form content uniformity, the standard deviation (or relative standard deviation) is reported with the individual unit dose test results.
In the context of additional testing performed during an OOS investigation, averaging the result (s) of the original test that prompted the investigation and additional retest or resample results obtained during the OOS investigation is not appropriate because it hides variability among the individual results. Relying on averages of such data can be particularly misleading when some of the results are OOS and others are within specifications. It is critical that the laboratory provide all individual results for evaluation and consideration by Quality Assurance (Contract Giver/QP).
All test results should conform to specifications (Note: a batch must be formulated with the intent to provide not less than 100 percent of the labelled or established amount of the active ingredient.
Averaging must be specified by the test method.
An outlier may result from a deviation from prescribed test methods, or it may be the result of variability in the sample. It should never be assumed that the reason for an outlier is an error in the testing procedure, rather than inherent variability in the sample being tested.
Statistical analysis for Outlier test results can be part of the investigation and analysis. However, for validated chemical tests with relatively small variance and that the sample was considered homogeneous it cannot be used to justify the rejection of data.
While OOS guidance is not directly intended for bioassay analysis, it can be used as a starting point for the investigation. Compendia such as the BP, PhEur and USP, provide guidance on outliers for these types of analysis. Reporting
OUT OF TRENDS (OOT)
WHAT IS OUT OF TREND (OOT) ?
A result that does not follow the expected trend, either in comparison with other stability batches or with respect to previous results collected during a stability study.
More complicated than a comparison to specification limits.
CRITERIA TO CONSIDER A RESULT AS OOT
For ASSAY: 5% Change in the initial value of assay.
For IMPURITIES: Between 0.1 to 0.2 % increase or decrease as per initial reports.
OOT CAN BE DUE TO:-
- ASSIGNABLE CAUSE: Laboratory errors
- NON- ASSIGNABLE CAUSE: Non-laboratory errors.
METHOD FOR IDENTIFYING OOT
- For the purpose of this study, data from ongoing stability studies of a final drug product with a shelf life of 36 months is used.
- The ongoing studies were conducted on 10 batches of Product X. (solid dosage form)
- The ongoing studies were conducted for 36 months in stability chambers at a constant temperature of 25 °C ± 2 °C and relative humidity of 60% ± 5% in accordance with the ICH guideline Q1A.
- The analyst should carry out an essay at a time point of 0,3,6,9,12,18,24 and 36 months for all batches.
TYPES OF OOT DETERMINATION:
- Regression-control-chart-method. The regression-control-chart method is used to compare the results within the batch and detect present OOT results. For the purpose of this method, the tenth batch is examined.
- By-time-point method. The by-time-point method is used to determine whether a result is within expectations on the basis of experiences from other batches measured at the same stability time point.
Stability OOS/OOT situations should be escalated as soon as the suspect result is found. Follow the investigation as above for Phase I and Phase II. For OOS Situations Regulatory agencies will require notification within a short time point of discovery due to recall potential.
- If abnormal results are found at any stability interval which predicts that the test results may be OOS before the next testing interval, schedule additional testing before the next scheduled testing interval. This will help better determine appropriate actions to be taken.
- The stability of OOS should link to the Product Recall procedures.
To facilitate the prompt identification of potential issues, and to ensure data quality, it is advantageous to use objective (often statistical) methods that detect potential out-of-trend (OOT) stability data quickly.
OOT alerts can be classified into three categories to help identify the appropriate depth for an investigation. OOT stability alerts can be referred to as:
- Process control, and
- Compliance alerts,
As the alert level increases from analytical to process control to compliance alert, the depth of investigation should increase.
A compliance alert defines a case in which an OOT result suggests the potential or likelihood for OOS results to occur before the expiration date within the same stability study (or for other studies) on the same product.
- The stability of OOS should link to the Product Recall procedures.
- Historical data are needed to identify OOT alerts.
- An analytical alert is observed when a single result is aberrant but within specification limits (i.e., outside normal analytical or sampling variation and normal change over time).