VALIDATION OF ANALYTICAL PROCEDURES: METHODOLOGY

TABLE OF CONTENTS
INTRODUCTION.................................................................................................................................4
1. Specificity.......................................................................................................................4
1.1. Identification ........................................................................................................5
1.2. Assay and Impurity Test(s) ....................................................................................5
2. LINEARITY ......................................................................................................................6
3. RANGE ..........................................................................................................................6
4. ACCURACY.....................................................................................................................7
4.1. Assay ..................................................................................................................7
4.2. Impurities (Quantitation).........................................................................................8
4.3. Recommended Data..............................................................................................8
5. PRECISION.....................................................................................................................8
5.1. Repeatability.........................................................................................................9
5.2. Intermediate Precision...........................................................................................9
5.3. Reproducibility ......................................................................................................9
5.4. Recommended Data..............................................................................................9
6. DETECTION LIMIT............................................................................................................9
6.1. Based on Visual Evaluation....................................................................................9
6.2. Based on Signal-to-Noise .................................................................................... 10
6.3 Based on the Standard Deviation of the Response and the Slope............................. 10
6.4 Recommended Data............................................................................................ 10
7. QUANTITATION LIMIT..................................................................................................... 11
7.1. Based on Visual Evaluation.................................................................................. 11
7.2. Based on Signal-to-Noise Approach...................................................................... 11
7.3. Based on the Standard Deviation of the Response and the Slope............................. 11
7.4 Recommended Data............................................................................................ 12
8. ROBUSTNESS .............................................................................................................. 12
9. System Suitability Testing............................................................................................... 13
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VALIDATION OF ANALYTICAL PROCEDURES:
METHODOLOGY
INTRODUCTION
This document is complementary to the parent document which presents a discussion of the characteristics
that should be considered during the validation of analytical procedures. Its purpose is to provide some
guidance and recommendations on how to consider the various validation characteristics for each analytical
procedure included as part of a registration application for approval of veterinary medicinal products
submitted to the European Union, Japan, and the United States. In some cases (for example,
demonstration of specificity), the overall capabilities of a number of analytical procedures in combination
may be investigated in order to ensure the quality of the drug substance or drug product. In addition, the
document provides an indication of the data which should be presented in a registration application.
All relevant data collected during validation and formulae used for calculating validation characteristics
should be submitted and discussed as appropriate.
Approaches other than those set forth in this guideline may be applicable and acceptable. It is the
responsibility of the applicant to choose the validation procedure and protocol most suitable for their product.
However it is important to remember that the main objective of validation of an analytical procedure is to
demonstrate that the procedure is suitable for its intended purpose. Due to their complex nature, analytical
procedures for biological and biotechnological products in some cases may be approached differently than
in this document.
Well-characterized reference materials, with documented purity, should be used throughout the validation
study. The degree of purity necessary depends on the intended use.
In accordance with the parent document, and for the sake of clarity, this document considers the various
validation characteristics in distinct sections. The arrangement of these sections reflects the process by
which an analytical procedure may be developed and evaluated.
In practice, it is usually possible to design the experimental work such that the appropriate validation
characteristics can be considered simultaneously to provide a sound, overall knowledge of the capabilities of
the analytical procedure, for instance: specificity, linearity, range, accuracy and precision.
1. SPECIFICITY
An investigation of specificity should be conducted during the validation of identification tests, the
determination of impurities and the assay. The procedures used to demonstrate specificity will depend
on the intended objective of the analytical procedure.
It is not always possible to demonstrate that an analytical procedure is specific for a particular analyte
(complete discrimination). In this case a combination of two or more analytical procedures is
recommended to achieve the necessary level of discrimination.
1.1. Identification
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Suitable identification tests should be able to discriminate between compounds of closely
related structures which are likely to be present. The discrimination of a procedure may be
confirmed by obtaining positive results (perhaps by comparison with a known reference
material) from samples containing the analyte, coupled with negative results from samples
which do not contain the analyte. In addition, the identification test may be applied to materials
structurally similar to or closely related to the analyte to confirm that a positive response is not
obtained. The choice of such potentially interfering materials should be based on sound
scientific judgement with a consideration of the interferences that could occur.
1.2. Assay and Impurity Test(s)
For chromatographic procedures, representative chromatograms should be used to
demonstrate specificity and individual components should be appropriately labelled. Similar
considerations should be given to other separation techniques.
Critical separations in chromatography should be investigated at an appropriate level. For
critical separations, specificity can be demonstrated by the resolution of the two components
which elute closest to each other.
In cases where a non-specific assay is used, other supporting analytical procedures should be
used to demonstrate overall specificity. For example, where a titration is adopted to assay the
drug substance for release, the combination of the assay and a suitable test for impurities can
be used.
The approach is similar for both assay and impurity tests:
1.2.1 Impurities are available
For the assay, this should involve demonstration of the discrimination of the analyte in the
presence of impurities and/or excipients; practically, this can be done by spiking pure
substances (drug substance or drug product) with appropriate levels of impurities and/or
excipients and demonstrating that the assay result is unaffected by the presence of these
materials (by comparison with the assay result obtained on unspiked samples).
For the impurity test, the discrimination may be established by spiking drug substance or drug
product with appropriate levels of impurities and demonstrating the separation of these
impurities individually and/or from other components in the sample matrix.
1.2.2 Impurities are not available
If impurity or degradation product standards are unavailable, specificity may be demonstrated
by comparing the test results of samples containing impurities or degradation products to a
second well-characterized procedure, e.g., pharmacopoeial method or other validated analytical
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procedure (independent procedure). As appropriate, this should include samples stored under
relevant stress conditions: light, heat, humidity, acid/base hydrolysis and oxidation.
- for the assay, the two results should be compared.
- for the impurity tests, the impurity profiles should be compared.
Peak purity tests may be useful to show that the analyte chromatographic peak is not
attributable to more than one component (e.g., diode array, mass spectrometry).
2. LINEARITY
A linear relationship should be evaluated across the range (see section 3) of the analytical procedure. It
may be demonstrated directly on the drug substance (by dilution of a standard stock solution) and/or
separate weighings of synthetic mixtures of the drug product components, using the proposed
procedure. The latter aspect can be studied during investigation of the range.
Linearity should be evaluated by visual inspection of a plot of signals as a function of analyte
concentration or content. If there is a linear relationship, test results should be evaluated by appropriate
statistical methods, for example, by calculation of a regression line by the method of least squares. In
some cases, to obtain linearity between assays and sample concentrations, the test data may need to
be subjected to a mathematical transformation prior to the regression analysis. Data from the
regression line itself may be helpful to provide mathematical estimates of the degree of linearity.
The correlation coefficient, y-intercept, slope of the regression line and residual sum of squares should
be submitted. A plot of the data should be included. In addition, an analysis of the deviation of the
actual data points from the regression line may also be helpful for evaluating linearity.
Some analytical procedures, such as immunoassays, do not demonstrate linearity after any
transformation. In this case, the analytical response should be described by an appropriate function of
the concentration (amount) of an analyte in a sample.
For the establishment of linearity, a minimum of 5 concentrations is recommended. Other approaches
should be justified.
3. RANGE
The specified range is normally derived from linearity studies and depends on the intended application
of the procedure. It is established by confirming that the analytical procedure provides an acceptable
degree of linearity, accuracy and precision when applied to samples containing amounts of analyte
within or at the extremes of the specified range of the analytical procedure.
The following minimum specified ranges should be considered:
- for the assay of a drug substance or a finished (drug) product: normally from 80 to 120 percent of
the test concentration;
- for content uniformity, covering a minimum of 70 to 130 percent of the test concentration, unless a
wider more appropriate range, based on the nature of the dosage form, is justified;
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- for dissolution testing: +/-20 % over the specified range; e.g., if the specifications for a controlled
released product cover a region from 20%, after 1 hour, up to 90%, after 24 hours, the validated
range would be 0-110% of the label claim.
- for the determination of an impurity: from the reporting level of an impurity1 to 120% of the
specification;
for impurities known to be unusually potent or to produce toxic or unexpected pharmacological
effects, the detection/quantitation limit should be commensurate with the level at which the
impurities must be controlled.
Note: for validation of impurity test procedures carried out during development, it may be necessary
to consider the range around a suggested (probable) limit;
- if assay and purity are performed together as one test and only a 100% standard is used, linearity
should cover the range from the reporting level of the impurities1 to 120% of the assay specification;
4. ACCURACY
Accuracy should be established across the specified range of the analytical procedure.
4.1. Assay
4.1.1 Drug Substance
Several methods of determining accuracy are available:
a) application of an analytical procedure to an analyte of known purity (e.g., reference material);
b) comparison of the results of the proposed analytical procedure with those of a second wellcharacterized
procedure, the accuracy of which is stated and/or defined (independent
procedure, see 1.2.);
c) accuracy may be inferred once precision, linearity and specificity have been established.
4.1.2 Drug Product
Several methods for determining accuracy are available:
a) application of the analytical procedure to synthetic mixtures of the drug product components
to which known quantities of the drug substance to be analysed have been added;
b) in cases where it is impossible to obtain samples of all drug product components, it may be
acceptable either to add known quantities of the analyte to the drug product or to compare
the results obtained from a second well-characterized procedure, the accuracy of which is
stated and/or defined (independent procedure, see 1.2.).
c) accuracy may be inferred once precision, linearity and specificity have been established.
1 see chapters AReporting Impurity Content of Batches@ of the corresponding VICH-Guidelines: AImpurities in
New Drug Substances@ and AImpurities in New Drug Products@
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4.2. Impurities (Quantitation)
Accuracy should be assessed on samples (drug substance/drug product) spiked with known
amounts of impurities.
In cases where it is impossible to obtain samples of certain impurities and/or degradation
products, it is considered acceptable to compare results obtained by an independent
procedure (see 1.2.). The response factor of the drug substance can be used.
It should be clear how the individual or total impurities are to be determined, e.g., weight/weight
or area percent, in all cases with respect to the major analyte.
4.3. Recommended Data
Accuracy should be assessed using a minimum of 9 determinations over a minimum of 3
concentration levels covering the specified range (e.g., 3 concentrations/3 replicates each of
the total analytical procedure).
Accuracy should be reported as percent recovery by the assay of known added amount of
analyte in the sample or as the difference between the mean and the accepted true value
together with the confidence intervals.
5. PRECISION
Validation of tests for assay and for quantitative determination of impurities includes an investigation of
precision.
5.1. Repeatability
Repeatability should be assessed using:
a) a minimum of 9 determinations covering the specified range for the procedure (e.g., 3
concentrations/3 replicates each)
or
b) a minimum of 6 determinations at 100% of the test concentration.
5.2. Intermediate Precision
The extent to which intermediate precision should be established depends on the
circumstances under which the procedure is intended to be used. The applicant should
establish the effects of random events on the precision of the analytical procedure. Typical
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variations to be studied include days, analysts, equipment, etc. It is not considered necessary
to study these effects individually. The use of an experimental design (matrix) is encouraged.
5.3. Reproducibility
Reproducibility is assessed by means of an inter-laboratory trial. Reproducibility should be
considered in case of the standardization of an analytical procedure, for instance, for inclusion
of procedures in pharmacopoeias. These data are not part of the marketing authorization
dossier.
5.4. Recommended Data
The standard deviation, relative standard deviation (coefficient of variation) and confidence
interval should be reported for each type of precision investigated.
6. DETECTION LIMIT
Several approaches for determining the detection limit are possible, depending on whether the
procedure is non-instrumental or instrumental. Approaches other than those listed below may be
acceptable.
6.1. Based on Visual Evaluation
Visual evaluation may be used for non-instrumental methods but may also be used with
instrumental methods.
The detection limit is determined by the analysis of samples with known concentrations of
analyte and by establishing the minimum level at which the analyte can be reliably detected.
6.2. Based on Signal-to-Noise
This approach can only be applied to analytical procedures which exhibit baseline noise.
Determination of the signal-to-noise ratio is performed by comparing measured signals from
samples with known low concentrations of analyte with those of blank samples and
establishing the minimum concentration at which the analyte can be reliably detected. A
signal-to-noise ratio between 3 or 2:1 is generally considered acceptable for estimating the
detection limit.
6.3 Based on the Standard Deviation of the Response and the Slope
The detection limit (DL) may be expressed as:
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DL = 3.3 s
S
where s = the standard deviation of the response
S = the slope of the calibration curve
The slope S may be estimated from the calibration curve of the analyte. The estimate of s may
be carried out in a variety of ways, for example:
6.3.1 Based on the Standard Deviation of the Blank
Measurement of the magnitude of analytical background response is performed by analyzing
an appropriate number of blank samples and calculating the standard deviation of these
responses.
6.3.2 Based on the Calibration Curve
A specific calibration curve should be studied using samples containing an analyte in the range
of DL. The residual standard deviation of a regression line or the standard deviation of yintercepts
of regression lines may be used as the standard deviation.
6.4 Recommended Data
The detection limit and the method used for determining the detection limit should be
presented. If DL is determined based on visual evaluation or based on signal-to-noise ratio, the
presentation of the relevant chromatograms is considered acceptable for justification.
In cases where an estimated value for the detection limit is obtained by calculation or
extrapolation, this estimate may subsequently be validated by the independent analysis of a
suitable number of samples known to be near or prepared at the detection limit.
7. QUANTITATION LIMIT
Several approaches for determining the quantitation limit are possible, depending on whether the
procedure is non-instrumental or instrumental. Approaches other than those listed below may be
acceptable.
7.1. Based on Visual Evaluation
Visual evaluation may be used for non-instrumental methods but may also be used with
instrumental methods.
The quantitation limit is generally determined by the analysis of samples with known
concentrations of analyte and by establishing the minimum level at which the analyte can be
quantified with acceptable accuracy and precision.
7.2. Based on Signal-to-Noise Approach
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This approach can only be applied to analytical procedures that exhibit baseline noise.
Determination of the signal-to-noise ratio is performed by comparing measured signals from
samples with known low concentrations of analyte with those of blank samples and by
establishing the minimum concentration at which the analyte can be reliably quantified. A
typical signal-to-noise ratio is 10:1.
7.3. Based on the Standard Deviation of the Response and the Slope
The quantitation limit (QL) may be expressed as:
QL = 10 s
S
where s = the standard deviation of the response
S = the slope of the calibration curve
The slope S may be estimated from the calibration curve of the analyte. The estimate of s may
be carried out in a variety of ways for example:
7.3.1 Based on Standard Deviation of the Blank
Measurement of the magnitude of analytical background response is performed by analyzing
an appropriate number of blank samples and calculating the standard deviation of these
responses.
7.3.2 Based on the Calibration Curve
A specific calibration curve should be studied using samples, containing an analyte in the
range of QL. The residual standard deviation of a regression line or the standard deviation of yintercepts
of regression lines may be used as the standard deviation.
7.4 Recommended Data
The quantitation limit and the method used for determining the quantitation limit should be
presented.
The limit should be subsequently validated by the analysis of a suitable number of samples known to be
near or prepared at the quantitation limit.
8. ROBUSTNESS
The evaluation of robustness should be considered during the development phase and depends on the
type of procedure under study. It should show the reliability of an analysis with respect to deliberate
variations in method parameters.
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If measurements are susceptible to variations in analytical conditions, the analytical conditions should
be suitably controlled or a precautionary statement should be included in the procedure. One
consequence of the evaluation of robustness should be that a series of system suitability parameters
(e.g., resolution test) is established to ensure that the validity of the analytical procedure is maintained
whenever used.
Examples of typical variations are:
- stability of analytical solutions,
- extraction time
In the case of liquid chromatography, examples of typical variations are:
- influence of variations of pH in a mobile phase,
- influence of variations in mobile phase composition,
- different columns (different lots and/or suppliers),
- temperature,
- flow rate.
In the case of gas-chromatography, examples of typical variations are:
- different columns (different lots and/or suppliers),
- temperature,
- flow rate.
9. SYSTEM SUITABILITY TESTING
System suitability testing is an integral part of many analytical procedures. The tests are based on the
concept that the equipment, electronics, analytical operations and samples to be analyzed constitute
an integral system that can be evaluated as such. System suitability test parameters to be established
for a particular procedure depend on the type of procedure being validated. See Pharmacopoeias for
additional information.

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