Guidance for Industry

Q2B Validation of Analytical

Procedures: Methodology

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or

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U.S. Department of Health and Human Services

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Center for Drug Evaluation and Research (CDER)

Center for Biologics Evaluation and Research (CBER)

November 1996

ICH
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Table of Contents

I. INTRODUCTION ..................................................... 1

II. SPECIFICITY (1) ..................................................... 2

A. Identification (1.1) ............................................... 2

B. Assay and Impurity Test(s) (1.2) ..................................... 2

III. LINEARITY (2) ...................................................... 3

IV. RANGE (3) .......................................................... 4

V. ACCURACY (4) ...................................................... 5

A. Assay (4.1) ..................................................... 5

B. Impurities (Quantitation) (4.2) ...................................... 6

C. Recommended Data (4.3) .......................................... 6

VI. PRECISION (5) ....................................................... 6

A. Repeatability (5.1) ............................................... 7

B. Intermediate Precision (5.2) ........................................ 7

C. Reproducibility (5.3) .............................................. 7

D. Recommended Data (5.4) .......................................... 7

VII. DETECTION LIMIT (6) ................................................ 7

A. Based on Visual Evaluation (6.1) .................................... 7

B. Based on Signal-to-Noise (6.2) ...................................... 8

C. Based on the Standard Deviation of the Response and the Slope (6.3) ........ 8

D. Recommended Data (6.4) .......................................... 8

VIII. QUANTITATION LIMIT (7) ............................................ 8

A. Based on Visual Evaluation (7.1) .................................... 9

B. Based on Signal-to-Noise (7.2) ...................................... 9

C. Based on the Standard Deviation of the Response and the Slope (7.3) ........ 9

D. Recommended Data (7.4) ......................................... 10

IX. ROBUSTNESS (8) ................................................... 10

X. SYSTEM SUITABILITY TESTING (9) ................................... 10
 This guidance was developed within the Expert Working Group (Quality) of the International Conference on 1

Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) and has been

subject to consultation by the regulatory parties, in accordance with the ICH process. This document has been endorsed

by the ICH Steering Committee at Step 4 of the ICH process, November 1996. At Step 4 of the process, the final draft is

recommended for adoption to the regulatory bodies of the European Union, Japan and the United States. This guidance

was published in the Federal Register on May 19, 1997 (62 FR 27464), and is applicable to drug and biological

products. This guidance represents the Agency’s current thinking on the validation of analytical procedures. It does not

create or confer any rights for or on any person and does not operate to bind FDA or the public. An alternative approach

may be used if such approach satisfies the requirements of the applicable statute, regulations, or both.

GUIDANCE FOR INDUSTRY1

Q2B Validation of Analytical

Procedures: Methodology

I. INTRODUCTION

This document is complementary to the ICH guidance entitled Text on Validation of Analytical

Procedures (ICH Q2A), 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. 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 that should be presented in a new drug 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 guidance 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.
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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.

II. SPECIFICITY (1)

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.

A. Identification (1.1)

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 sensible scientific judgment with a consideration of the interferences that could

occur.

B. Assay and Impurity Test(s) (1.2)

For chromatographic procedures, representative chromatograms should be used to

demonstrate specificity, and individual components should be appropriately labeled. 

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 nonspecific 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.
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The approach is similar for both assay and impurity tests:

1. Impurities are available (1.2.1)

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. 

2. Impurities are not available (1.2.2)

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 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).

III. LINEARITY (2)

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 have to be subjected to a mathematical transformation prior to the regression
 See sections on "Reporting Impurity Content of Batches" of the corresponding ICH Q3A guidance entitled 2

"Impurities in New Drug Substances" (61 FR 372; January 4, 1996) and ICH Q3B draft guidance "Impurities in New

Drug Products" (61 FR 11268; March 19, 1996).

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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 five concentrations is recommended. Other

approaches should be justified.

IV. RANGE (3)

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 (e.g., metered dose inhalers), is justified;

• For dissolution testing: +/-20 percent over the specified range; e.g., if the

specifications for a controlled released product cover a region from 20 percent,

after 1 hour, up to 90 percent, after 24 hours, the validated range would be 0-110

percent of the label claim;

• For the determination of an impurity: From the reporting level of an impurity to 2

120 percent of the specification;
Ibid.

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5

• 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 percent

standard is used, linearity should cover the range from the reporting level of the

impurities to 120 percent of the assay specification. 3

V. ACCURACY (4)

Accuracy should be established across the specified range of the analytical procedure.

A. Assay (4.1)

1. Drug substance (4.1.1)

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 well-characterized procedure, the accuracy of which is stated and/or

defined (independent procedure, see section 1.2.);

(c) Accuracy may be inferred once precision, linearity, and specificity have been

established.

2. Drug product (4.1.2)

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

analyzed 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
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the drug product or to compare the results obtained from a second, wellcharacterized procedure, the accuracy of which is stated and/or defined

(independent procedure, see section 1.2);

(c) Accuracy may be inferred once precision, linearity, and specificity have been

established.

B. Impurities (Quantitation) (4.2)

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 section 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.

C. Recommended Data (4.3)

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.

VI. PRECISION (5)

Validation of tests for assay and for quantitative determination of impurities includes an

investigation of precision.

A. Repeatability (5.1)

Repeatability should be assessed using:

(1) A minimum of 9 determinations covering the specified range for the procedure

(e.g., 3 concentrations/3 replicates each); or

(2) A minimum of 6 determinations at 100 percent of the test concentration.
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B. Intermediate Precision (5.2)

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

variations to be studied include days, analysts, equipment, etc. It is not necessary to study

these effects individually. The use of an experimental design (matrix) is encouraged.

C. Reproducibility (5.3)

Reproducibility is assessed by means of an interlaboratory 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.

D. Recommended Data (5.4)

The standard deviation, relative standard deviation (coefficient of variation), and

confidence interval should be reported for each type of precision investigated.

VII. DETECTION LIMIT (6)

Several approaches for determining the detection limit are possible, depending on whether the

procedure is noninstrumental or instrumental. Approaches other than those listed below may be

acceptable.

A. Based on Visual Evaluation (6.1)

Visual evaluation may be used for noninstrumental 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.

B. Based on Signal-to-Noise (6.2)

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.
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C. Based on the Standard Deviation of the Response and the Slope (6.3)

The detection limit (DL) may be expressed as:

 3.3 F

DL= _________________

 S

where F = 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 F

may be carried out in a variety of ways, for example:

1. Based on the standard deviation of the blank (6.3.1)

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.

2. Based on the calibration curve (6.3.2)

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 y-intercepts of regression lines may be used as the standard

deviation.

D. Recommended Data (6.4)

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.

VIII. QUANTITATION LIMIT (7)

Several approaches for determining the quantitation limit are possible, depending on whether the

procedure is noninstrumental or instrumental. Approaches other than those listed below may be

acceptable.
9

A. Based on Visual Evaluation (7.1)

Visual evaluation may be used for noninstrumental 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.

B. Based on Signal-to-Noise (7.2)

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.

C. Based on the Standard Deviation of the Response and the Slope (7.3)

The quantitation limit (QL) may be expressed as:

10 F

QL= ______________________________

 S

where F = the standard deviation of responses

 S = the slope of the calibration curve

The slope S may be estimated from the calibration curve of the analyte. The estimate of F

may be carried out in a variety of ways, for example:

1. Based on standard deviation of the blank (7.3.1)

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.

2. Based on the calibration curve (7.3.2.)

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 y-intercepts of regression lines may be used as the standard

deviation.
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D. Recommended Data (7.4)

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.

IX. ROBUSTNESS (8)

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.

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

X. SYSTEM SUITABILITY TESTING (9)

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.