**64**

**Guidance for Industry**

> **Validation of Analytical Procedures: Methodology**

**FINAL GUIDANCE**

**This guidance document provides recommendations on how to consider
various validation characteristics for each analytical procedure
included as part of registration applications. for approval of
veterinary medicinal products submitted to the European Union, Japan and
the United States. The implementation date is set for October 1999.**

This guidance represents current thinking and 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, regulation, or both.

**Comments and suggestions regarding the document should be submitted to
Carol Haley, Petitions & Regulations Team, Center for Veterinary
Medicine, (HFV-6), Food and Drug Administration, 7500 Standish Place,
Rockville, MD 20855.**

**For questions regarding this final document, contact William G.
Marnane, Center for Veterinary Medicine, (HFV-140), Food and Drug
Administration, 7500 Standish Place, Rockville, MD 20855, 301-594-0678,
E-mail: wmarnane@cvm.fda.gov.**

**U.S. Department of Health and Human Services**

###### Food and Drug Administration

###### Center for Veterinary Medicine

**JULY 1999**

**VICH GL2 [(Validation Methodology)]{.smallcaps}**

**October 1998**

**For implementation Step 7**

Validation of Analytical Procedures:

Methodology

Recommended for Implementation

at Step 7 of the VICH Process

on 22 October 1998

by the VICH Steering Committee

[This Guidance has been developed by the appropriate VICH Expert Working
Group on the basis of the ICH guidelines on the same subject and has
been subject to consultation by the parties, in accordance with the VICH
Process. At Step 7 of the Process the final draft is recommended for
adoption to the regulatory bodies of the European Union, Japan
and]{.smallcaps} USA.

Validation of analytical procedures:

Methodology

TABLE OF CONTENTS

INTRODUCTION **[4]{.underline}**

1\. Specificity **[4]{.underline}**

> 1.1. Identification **[5]{.underline}**
>
> 1.2. Assay and Impurity Test(s) **[5]{.underline}**

2\. LINEARITY **[6]{.underline}**

3\. RANGE **[6]{.underline}**

4\. ACCURACY **[7]{.underline}**

> 4.1. Assay **[7]{.underline}**
>
> 4.2. Impurities (Quantitation) **[8]{.underline}**
>
> 4.3. Recommended Data **[8]{.underline}**

5\. PRECISION **[8]{.underline}**

> 5.1. Repeatability 9
>
> 5.2. Intermediate Precision **[9]{.underline}**
>
> 5.3. Reproducibility **[9]{.underline}**
>
> 5.4. Recommended Data **[9]{.underline}**

6\. DETECTION LIMIT **[9]{.underline}**

> 6.1. Based on Visual Evaluation **[9]{.underline}**
>
> 6.2. Based on Signal-to-Noise **[10]{.underline}**
>
> 6.3 Based on the Standard Deviation of the Response and the Slope
> **[10]{.underline}**
>
> 6.4 Recommended Data **[10]{.underline}**

7\. QUANTITATION LIMIT **[11]{.underline}**

> 7.1. Based on Visual Evaluation **[11]{.underline}**
>
> 7.2. Based on Signal-to-Noise Approach **[11]{.underline}**
>
> 7.3. Based on the Standard Deviation of the Response and the Slope
> **[11]{.underline}**
>
> 7.4 Recommended Data **[12]{.underline}**

8\. ROBUSTNESS **[12]{.underline}**

9\. System Suitability Testing **[13]{.underline}**

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 

> 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 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;
>
> \- 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 impurity^1^ 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 impurities[^1] 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 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.

#### 

#### 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.

### 

###  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 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:

  -------------------------- --------------------------------------------
  DL =                       3.3 σ

                             S
  -------------------------- --------------------------------------------

> where σ = 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 σ 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
> y-intercepts 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

> 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 σ

                               S
  ---------------------------- ------------------------------------------

> where σ = 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 σ 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
> y-intercepts 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.
>
> 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.

[^1]:
    > see chapters AReporting Impurity Content of Batches@ of the
    > corresponding VICH-Guidelines: AImpurities in New Drug Substances@
    > and AImpurities in New Drug Products@