Question? Prior Method Validation (To design a Protocol)

 CONSIDERATIONS PRIOR TO METHOD VALIDATION

Test method validation is a requirement for entities engaging in the testing of pharmaceutical products for the purpose of drug exploration,development, and manufacture for human use. It also of great value for any type of routine testing that requires consistency and accuracy.

Procedure validation is a cornerstone in the process of establishing an analytical procedure. The aim   of procedure validation is to demonstrate that the procedure, when run under standard conditions, will satisfy the requirement of being fit for use. To maximize the likelihood of a successful validation,         It is imperative that all aspects of the procedure be well understood prior to the validation. Surprising discoveries (whether "good" or "bad") during validation should be carefully evaluated to determine whether the procedure was adequately developed. Moreover, pre-validation work can reveal suitable approaches to reduce the total size of the validation experiment without increasing the risk of drawing the wrong conclusion. General principles and plans for sample preparation, general principles, experimental design, data collection, statistical evaluation, and choice of acceptance criteria should be documented in a validation experimental protocol signed before initiation of the formal validation.

Questions considered prior to validation may include the following:

·         What are the allowable ranges for operational parameters, such as temperature and time, that impact the performance of the analytical procedure?

o    Robustness of these ranges can be determined using a statistical design of experiments (DOE).

·         What are the ruggedness factors that impact precision?

o    Factors such as analyst, day, reagent lot, reagent supplier, and instrument that impact the precision of a test procedure are called ruggedness factors. When ruggedness factors impact precision, reportable values within the same ruggedness grouping (e.g., analyst) are correlated. Depending on the strength of the correlation, a statistical analysis that appropriately accounts for this dependence may be necessary. Ruggedness factors can be identified empirically during pre-validation or based on a risk assessment.

·         Are statistical assumptions regarding data analysis reasonably satisfied?

o    These assumptions may include such factors as normality, homogeneity of variance, and independence. It is useful during pre-validation to employ statistical tests or visual representations to help answer these questions.

·         What is the required range for the procedure?

o    The range of an analytical procedure is the interval between the upper and lower levels of an analyte that has been demonstrated to be determined with a suitable level of precision, accuracy, and linearity using the procedure as written.

·     Do accepted reference values or results from an established procedure exist for validation of accuracy?

o    If not, as stated in International Council for Harmonisation (ICH) Q2, accuracy may be inferred once precision, linearity, and specificity have been established.

·   How many individual determinations will compose the reportable value, and how will they be aggregated?

o    To answer this question, it is necessary to understand the contributors to the procedure variance and the ultimate purpose of the procedure. Estimation of variance components during pre-validation provides useful information for making this decision.

·         What are appropriate validation acceptance criteria?

o    The validation succeeds when there is statistical evidence that the assay is no worse than certain pre-specified levels for each relevant validation parameter.

       What defines the assay as fit for use, and how does this relate to acceptance criteria?

·         How large a validation experiment is necessary?

o    Validation experiments should be properly powered to ensure that there are sufficient data to conclude that the accuracy and precision can meet pre-specified acceptance criteria. Computer simulation is a useful tool for performing power calculations.

o    Efficiencies (both cost and statistical) can be gained if assessment of linearity, accuracy, and precision can be combined.

    On the basis of the answers to these and similar questions, one can design a suitable validation experimental protocol.

OOS Investigation Case Study-8 (Organic Impurity)

In Pharmaceutical Industry, OOS investigation and root cause identification is very important topic. If you are not able to identify the exact root cause, then your effort should be looked in your investigation to convince the regulatory auditors.

Here I am sharing another case study to understand it in a better way-

OOS observed in Organic Impurity test.
Description of Event:
OOS result is reported in Organic Impurity.
Result: 0.95%  (Known Impurity: Named X)
-Limit is NMT 0.70%.

Preliminary investigation:
Checked pressure graph,System suitability parameters, Calculation etc. and No laboratory error is identified from preliminary investigation.
Re-measurement  (Hypothesis testing):
Hypothesis testing is performed to rule out instrument error and vial filling error,  etc.
But no any error is identified and all above possibilities are ruled out.

Reviewed the trend of previous 10 released batches and stability trend data of Validation batches and no any failure observed for X impurity, even in ACC (40/75) condition the maximum impurity % is 0.3% and during batch release it never be more than 0.1%

Now what is the next step. . .Based on trend data it  looks like that, this is not a true failure.
But we can not perform the Re-analysis by saying that this is an erratic result.
Then what is our next step as an investigator.
Step- 1
Inject same subject sample on PDA detector along with impurity X preparation and record the spectra and peak purity of the subject impurity (it helps to rule out whether it is impurity X or some other extraneous peak eluted on same RT.

If you have facility of Mass Spectrometer (LC-MS) , develop a MS compatible method and inject the solution on LC-MS to know the Mass and can conclude whether it is Impurity X  or Y (extraneous)              or X+ Y . If it is Y or X+Y then by knowing mass of Y you can suspect the contaminated product.

If it is extraneous peak then we have to rue out whether it come from manufacturing or Laboratory.

First we have to rule out product contamination by injecting all steps previous product (Mfg) on LC-MS.

 Inject all product standard  which are used in manufacturing before this product (cover all equipment) in same chromatographic condition on LC-MS (If LCMS is not available then you can do activity  on PDA detector).

Inference: If root cause is identified from above exercise, then perform the reanalysis and release the batch, if not then.....
Step-2
Review the force degradation study to check in which condition Impurity X is increased and find the possibility for same during analysis in laboratory and rule out same by negative experiment (If required).

Then it's confirmed that this failure is not a product failure, further we have to rule out that this peak is come due to any product contamination during manufacturing to support this statement further follow step-3.
Step-3
Again re-look in laboratory investigation and rule out all probabilities i. e. filter interference (if sample required high pressure during filtration). Rule out all possible reasons through "SYSTEMATIC ROOT CAUSE ANALYSIS TOOLS like 6M, 5Why/2H, Brainstorming, Fault Tree Analysis, Graphical Analysis (Histogram, Pareto, Run chart). etc.
If required keep sample for stability study with reduce testing (3, 12 and 24 months) , which data help you to convince auditor that initial failure was not  product quality issue.

By all these efforts, if we still not have exact root cause, but we find some most probable cause in laboratory then we can do the Re-analysis and if Re-analysis is complying to the specification and with in trend to other previous batches then It will give confidence to auditor that there is no any issue with the product quality (Batch release/reject decision is conscious call of Quality Head).