Validation of analytical methods for active constituents and agricultural products

1. Scope

The objective of validation of an analytical method is to demonstrate that the method, when correctly applied, produces results that are fit for purpose. These guidelines describe the procedures to be carried out to validate the analytical method. The guidelines are included as part of the Part 2 – Chemistry and manufacture dossier for an application for approval of an active constituent and registration of an agricultural chemical product, including those used in storage stability studies. They are not intended to apply to analytical methods for residue analysis, or to analytical methods for biological and biotechnological products. Approaches other than those set forth in this guideline may be acceptable, provided they are supported by adequate scientific justification.

Non-chromatographic analytical methods (e.g. titration methods) are not typically expected to comply with this guideline. However, we expect that users of non-chromatographic methods will provide some form of validation in order to satisfy us that the method is fit for purpose.

2. Providing data to support an analytical method

The following information should generally be included to support the adequacy of the analytical method:

• Method description – this section should contain a full description of the analytical method. The description should include details of all-important operational parameters, such as details of sample preparation and reagents preparation (including method of extraction of the active constituent from the product), and details of the reference standards. You should also provide documentation confirming the purity of the reference materials.
• Validation data and all relevant data collected during validation, including:
  • copies of chromatograms that are clearly labelled with peak-identity and peak-integration data as well as X and Y axes with relevant scales
  • nuclear magnetic resonance spectra, clearly showing chemical shifts and coupling constants
  • formulae
  • examples of calculations used for calculating validation characteristics.

3. Parameters for method validation

To be fit for the intended purpose the method needs to meet certain validation characteristics. Typical validation characteristics that should be considered are:

• selectivity (specificity)
• linearity
• range
• accuracy
• precision
• Limit of detection (LOD) and
• Limit of quantitation (LOQ).

3.1. Selectivity (specificity)

The selectivity of a method refers to the extent to which the method can determine particular analyte(s) in a complex mixture without interference from other components in the mixture. The terms selectivity and specificity have often been used interchangeably. The term selectivity generally refers to a method that provides responses for a number of chemical entities that may or may not be distinguished from each other, while the term specificity refers to a method that produces a response for a single analyte only. Since very few analytical methods respond to only one analyte, the use of the term selectivity is more appropriate than specificity.

The selectivity of the analytical method should be demonstrated by providing data to show that the analyte chromatographic peak is absent from interference peaks with regard to degradation products, synthetic impurities and the matrix (that is, excipients present in the formulated product at their expected levels). Such data include a peak homogeneity test or peak purity test (for example, diode array, or mass spectrometry) that shows the analyte chromatographic peak is not attributable to more than one component.

3.2. Linearity

The linearity is the ability of the analytical method to produce test results that are proportional to the concentration (amount) of analyte in samples within a given concentration range, either directly or by means of a well-defined mathematical transformation. Linearity should be determined by using duplicate determinations at 3 or more concentrations, or a single determination at 6 or more concentrations that span 80% to 120% of the expected nominal concentration.

The linearity of a method should be established by visual inspection of a plot of analytical response as a function of analyte concentration. If there is a linear relationship, test results should be evaluated by appropriate statistical methods (for example, by calculation of the regression line by the method of least squares). In some cases, the test data may need to be subjected to a mathematical transformation prior to regression analysis.

Your report(s) should include the:

• equation of the calibration line
• slope of the line
• intercept
• correlation coefficient (r).

The slope should demonstrate a clear correlation between response and analyte concentrations. The test results should not show a significant deviation from calculated results by the calibration equation – indicated by the correlation coefficient, r – greater than 0.99 over the range (80% to 120%). If r is less than 0.99, you should explain how accurate calibration is to be maintained. In cases where a non-linear response is deliberately used, you should also provide an explanation.

3.3. Range

The specified range is normally derived from the linearity studies. The range of an analytical method is the interval between the upper and lower concentration (amounts) of analyte in the sample for which it has been demonstrated that the analytical method has suitable levels of precision, accuracy and linearity.

The following minimum specified ranges should be considered for the:

• assay of the active constituent of an agricultural chemical product, at least 80% to 120% of the nominal concentration
• determination of an impurity, at least from the specification level to 120% of the specification level.

3.4. Accuracy

The accuracy of an analytical method is defined as the degree to which the determined value of the analyte in a sample corresponds to the true value. Accuracy may be measured in different ways and the method should be appropriate to the matrix. The accuracy of an analytical method may be determined in any of the following ways:

• Analysing a sample of known concentration and comparing the measured value to the 'true' value – you should use a well-characterised sample (for example, a reference standard) for this.
• The placebo (product matrix) recovery method, or ‘spiking’ – whereby a known amount of reference standard is added to a placebo sample (that is, a sample that contains all other ingredients except the active constituent[s]), the resulting mixture is assayed, and the results obtained are compared with the expected result.
• The standard addition method – whereby a sample is assayed, a known amount of reference standard is then added, and the sample is again assayed; the difference between the results of the 2 assays is then compared with the added amount.

Recovery is expressed as the percentage of the observed result to the expected result. The accuracy of a method may vary across the range of concentrations and therefore must be determined at several different fortification concentrations. The accuracy should cover at least 3 concentrations (80%, 100% and 120% of the nominal concentration) in the expected range.

Accuracy may also be determined by comparing test results with results obtained using another validated test method.

The acceptance criteria for the accuracy of the method are based on expected recovery. This depends on the sample matrix, the sample processing procedure and the analyte concentration. The mean percentage recovery of each of the 3 concentrations should be within the ranges listed in Table 1.

3.5. Precision

The precision of an analytical method expresses the closeness of agreement (degree of scatter) between a series of measurements obtained from multiple sampling of the same sample under the same prescribed conditions. Precision may be considered at three levels: repeatability, intermediate precision and reproducibility. For example, repeatability can be obtained by a minimum of 5 independent replicate sample determinations with the same method, on identical test material, on the same equipment, by the same operator in the same laboratory within short intervals of time.

The precision of an analytical procedure is usually expressed as the per cent relative standard deviation of a series of measurements. When applicable, a suitable test for outliers (Dixon's or Grubbs Test) may be applied to the results. You should clearly indicate where outliers have been discarded and attempt to explain the reason for the occurrence of individual outliers.

The levels of precision we recommend are listed in Table 2.

3.6. Limit of detection (LOD)

The limit of detection (LOD) of an analytical method is the lowest amount of an analyte in a sample that can be detected, but not necessarily quantitated as an exact value.

The LOD may be determined by analysing a series of samples with known concentrations of analyte and by establishing the minimum concentration at which the analyte can be reliably detected. That is, the LOD answers 2 questions:

• Is the analyte present and can it be reported?
• Is the analyte not present and can that be reported?

The lowest concentration that produces a detectable peak response corresponding to the analyte should be normally measured with between 6 and 10 replicates. You should calculate the average response (X) and the standard deviation (SD). The LOD is X + (3 × SD).

3.7. Limit of quantitation (LOQ)

The limit of quantitation (LOQ) is the lowest amount of the analyte in the sample that can be quantitatively determined with defined precision under the stated experimental conditions. The limit of quantitation is a parameter of quantitative assays for low levels of analytes in sample matrices and is relevant, particularly for the determination of impurities, degradation products and low levels of active constituent in a product.

If a preliminary study to determine the approximate LOQ is undertaken, then the LOQ may be determined by measuring a reference standard solution that was estimated during the preliminary study. The solution is normally injected and analysed with between 6 and 10 replicates. You should calculate the average response (X) and the relative standard deviation as a per cent (%RSD) of the results. The %RSD should be less than 20%. If the %RSD exceeds 20%, you should prepare a new standard solution of higher concentration and repeat this procedure. The LOQ is X + (10 × SD).

4. Applying the parameters of method validation

The extent to which a method needs to be validated depends on its application.

The tests we recommend for consideration for each of the categories of analytical methods described in the guidelines are listed in Table 3.

5. General notes

5.1. Regulatory analytical methods

The analytical methods for agricultural active constituents and agricultural chemical products described in the following documents are recognised as the regulatory methods:

• Handbooks of the Collaborative International Pesticide Analytical Council (CIPAC).
• The Association of Official Analytical Chemists’ (AOAC International) Manual for agricultural active constituents and agricultural chemical products.

The use of regulatory methods (if one is available) is recommended by the Australian Pesticides and Veterinary Medicines Authority.

We also recommend that, where available, you use the analytical methods described in the above documents for a particular active constituent or formulated product.

The analytical methods described in these documents for a particular active constituent or formulation are regarded as validated and do not require revalidation. However, you must verify the suitability of the method to be used under actual conditions of use (that is, selectivity and accuracy should be demonstrated for the published method when applied to the relevant sample matrix and laboratory conditions) and provide the data.

5.2. Alternative analytical methods

An alternative analytical method is an analytical method proposed by the registration holder for use instead of the regulatory analytical method. You may use an alternative analytical method in place of a regulatory method as long as it is validated in accordance with this guideline.

5.3. Typical characteristics for quantitative Nuclear Magnetic Resonance (NMR) data

Analytical data generated using quantitative NMR methods should be provided. They should include, using Certified Reference Material (CRM):

• a suitable relaxation time
• selectivity
• accuracy
• LOQ.

5.4. Analytical reference standards (Certified Reference Material)

You should use well-characterised analytical reference standards with documented purity throughout the validation study. If analytical reference standards are not available for a given analyte, then this should be reported. If the analytical laboratory has the capacity or has access to a laboratory with the capacity to standardise material for use as Certified Reference Material (CRM), this is acceptable as long as you provide the testing and associated data to demonstrate the appropriateness of certifying such material.

5.5. Good Laboratory Practice

Laboratories undertaking analytical studies as part of the chemistry dossier for an active constituent or product application are not currently required to be accredited for Good Laboratory Practice (GLP).

6. Revalidation

Analytical methods require validation whenever the conditions for which the methods have been developed change. You should revalidate the analytical method in the following circumstances:

• When an existing method is modified to meet special requirements
• When there are changes in the route of synthesis of the active constituent, which may lead to a different impurity profile
• When there are changes to the formulation composition of an agricultural chemical product

You should perform revalidation to ensure that the analytical method maintains its characteristics. The degree of revalidation depends on the nature of the change. For example, a new dosage strength of a product may require validation of the method in terms of recovery and linearity at the new dosage strength if the nominal concentration has not been taken into consideration by the addition of a relevant dilution; however, a new formulation would require a full revalidation.

7. References

Albert, R & Horwitz, W, 1997, A heuristic derivation of the Horwitz curve, Analytical Chemistry, vol. 69, pp. 789–790.

CIPAC handbooks, Collaborative International Pesticide Analytical Council Publications, Black Bear Press, Cambridge, United Kingdom, available at cipac.org/handbooks/handb_n.HTM.

De Bievre et al., 1998, The fitness for purpose of analytical methods: a laboratory guide to method validation and related topics, EURACHEM Guidance document.

Dixon, WJ, 1951, Ratios involving extreme values, Annals of Mathematical Statistics, vol. 22, pp. 68–78.

European Commission, 2000, Technical material and preparations: guidance for generating and reporting methods of analysis in support of pre- and post-registration data requirements for Annex II (part A, Section 4) and Annex III (part A, Section 5) of Directive 91/414, EC Directorate General Health and Consumer Protection.

Green, JM, 1996, A practical guide to analytical method validation, Analytical Chemistry, vol. 68, pp. 305A–1309A.

Grubs, FE & Beck, G, 1972, Extension of sample sizes and percentage points for significance tests of outlying observations, Technometries, vol. 14, pp. 847–854.

Vessman, J et al., 2001, Selectivity in Analytical Chemistry (IUPAC Recommendations 2001), Pure and Applied Chemistry, vol. 73(8), pp. 1381–1386.