Q2(R2) Validation of 
Analytical Procedures 
Guidance for Industry 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Center for Biologics Evaluation and Research (CBER) 
 
March 2024 
ICH-Quality 
Revision 2 
   
Q2(R2) Validation of 
Analytical Procedures 
Guidance for Industry 
 
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U.S. Department of Health and Human Services 
Food and Drug Administration 
Center for Drug Evaluation and Research (CDER) 
Center for Biologics Evaluation and Research (CBER) 
 
March 2024 
ICH-Quality 
Revision 2 
  Contains Nonbinding Recommendations 
FOREWORD 
 
The International Council for Harmonisation of Technical Requirements for Pharmaceuticals 
for Human Use (ICH) has the mission of achieving greater regulatory harmonization 
worldwide to ensure that safe, effective, and high-quality medicines are developed, 
registered, and maintained in the most resource-efficient manner.  By harmonizing the 
regulatory expectations in regions around the world, ICH guidelines have substantially 
reduced duplicative clinical studies, prevented unnecessary animal studies, standardized 
safety reporting and marketing application submissions, and contributed to many other 
improvements in the quality of global drug development and manufacturing and the products 
available to patients.  
 
ICH is a consensus-driven process that involves technical experts from regulatory authorities 
and industry parties in detailed technical and science-based harmonization work that results 
in the development of ICH guidelines.  The commitment to consistent adoption of these 
consensus-based guidelines by regulators around the globe is critical to realizing the benefits 
of safe, effective, and high-quality medicines for patients as well as for industry.  As a 
Founding Regulatory Member of ICH, the Food and Drug Administration (FDA) plays a 
major role in the development of each of the ICH guidelines, which FDA then adopts and 
issues as guidance to industry. 
  Contains Nonbinding Recommendations 
TABLE OF CONTENTS 
 
I.  INTRODUCTION (1) .................................................................................................. 1 
A.  Objective (1.1) .......................................................................................................................... 1 
B.  Scope (1.2) ................................................................................................................................. 1 
II.  GENERAL CONSIDERATIONS FOR ANALYTICAL PROCEDURE 
VALIDATION (2) ........................................................................................................ 2 
A.  Analytical Procedure Validation Study (2.1) ......................................................................... 3 
B.  Validation During the Life Cycle of an Analytical Procedure (2.2) .................................... 5 
C.  Reportable Range (2.3) ............................................................................................................ 6 
D.  Demonstration of Stability-Indicating Properties (2.4) ........................................................ 6 
E.  Considerations for Multivariate Analytical Procedures (2.5) .............................................. 6 
III.  VALIDATION TESTS, METHODOLOGY, AND EVALUATION (3) ................ 8 
A.  Specificity/Selectivity (3.1) ...................................................................................................... 8 
1. General Considerations (3.1.1) ................................................................................................. 8 
a.  Absence of interference (3.1.1.1) ........................................................................................ 8 
b.  Orthogonal procedure comparison (3.1.1.2) ....................................................................... 8 
c.  Technology-inherent justification (3.1.13) .......................................................................... 8 
2. Recommended Data (3.1.2) ........................................................................................................ 9 
a.  Identification (3.1.2.1) ......................................................................................................... 9 
b.  Assay, purity, and impurity test(s) (3.1.2.2) ....................................................................... 9 
B.  Range (3.2) .............................................................................................................................. 10 
1. General Considerations (3.2.1) ............................................................................................... 10 
2. Response (3.2.2) ....................................................................................................................... 10 
a.  Linear response (3.2.2.1) ................................................................................................... 10 
b.  Nonlinear response (3.2.2.2) ............................................................................................. 11 
c.  Multivariate calibration (3.2.2.3) ...................................................................................... 11 
3. Validation of Lower Range Limits (3.2.3)................................................................................ 12 
a.  Based on visual evaluation (3.2.3.1) ................................................................................. 12 
b.  Based on signal-to-noise (3.2.3.2) .................................................................................... 12 
c.  Based on the standard deviation of a linear response and a slope (3.2.3.3) ...................... 12 
d.  Based on accuracy and precision at lower range limits (3.2.3.4) ...................................... 13 
e.  Recommended data (3.2.3.5) ............................................................................................ 13 
C.  Accuracy and Precision (3.3) ................................................................................................ 13 
1. Accuracy (3.3.1) ....................................................................................................................... 13 
a.  Reference material comparison (3.3.1.1) .......................................................................... 14 
b.  Spiking study (3.3.1.2) ...................................................................................................... 14 
c.  Orthogonal procedure comparison (3.3.1.3) ..................................................................... 14 
d.  Recommended data (3.3.1.4) ............................................................................................ 14 
2. Precision (3.3.2) ...................................................................................................................... 14 
a.  Repeatability (3.3.2.1) ....................................................................................................... 15 
b.  Intermediate precision (3.3.2.2) ........................................................................................ 15 
c.  Reproducibility (3.3.2.3) ................................................................................................... 15 
d.  Recommended data (3.3.2.4) ............................................................................................ 15 
3. Combined Approaches for Accuracy and Precision (3.3.3) .................................................... 15 
a.  Recommended data (3.3.3.1) ............................................................................................ 16 
D.  Robustness (3.4) ..................................................................................................................... 16 
i  Contains Nonbinding Recommendations 
GLOSSARY (4) ...................................................................................................................... 17 
REFERENCES (5) ................................................................................................................. 22 
APPENDIX A: SELECTION OF VALIDATION TESTS (6. ANNEX 1) ....................... 23 
APPENDIX B: ILLUSTRATIVE EXAMPLES FOR ANALYTICAL TECHNIQUES  
(7. ANNEX 2) .......................................................................................................................... 24 
 
 
ii 
  Contains Nonbinding Recommendations 
Q2(R2) Validation of Analytical Procedures 
Guidance for Industry1 
 
 
 
This guidance represents the current thinking of the Food and Drug Administration (FDA or Agency) 
on this topic.  It does not establish any rights for any person and is not binding on FDA or the public.  
You can use an alternative approach if it satisfies the requirements of the applicable statutes and 
regulations.  To discuss an alternative approach, contact the FDA office responsible for this guidance 
as listed on the title page.   
 
 
 
I.  INTRODUCTION (1)2 
 
A.  Objective (1.1) 
 
This guidance presents elements for consideration during the validation of analytical 
procedures included as part of registration applications. Analytical procedure validation 
forms a part of the analytical procedure life cycle, as described within the International 
Council for Harmonisation (ICH) guidance for industry Q14 Analytical Procedure 
Development (March 2024) (ICH Q14).3 This ICH guidance for industry, Q2(R2) Validation 
of Analytical Procedures (ICH Q2), provides guidance on selection and evaluation of the 
various validation tests for analytical procedures. This guidance includes a collection of 
terms and their definitions, which are meant to bridge the differences that often exist between 
various compendia and documents of the ICH member regulatory authorities. 
 
The objective of validation of an analytical procedure is to demonstrate that the analytical 
procedure is fit for the intended purpose. Further general guidance is provided on validation 
studies for analytical procedures.  
 
B.  Scope (1.2) 
 
This guidance applies to analytical procedures used for release and stability testing of 
commercial drug substances and products, hereafter referred to as products. The guidance can 
also be applied to other analytical procedures used as part of the control strategy (ICH 
guidance for industry Q10 Pharmaceutical Quality System (April 2009)) following a risk-
based approach. The scientific principles described in this guidance can be applied in a 
phase-appropriate manner to analytical procedures used during clinical development.  
 
 
1 This guidance was developed within the Expert Working Group (Quality) of the International Council for 
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 Assembly at Step 4 of the ICH process, November 2023.  At Step 4 of the process, the 
final draft is recommended for adoption to the regulatory bodies of the ICH regions.  
2 The numbers in parentheses reflect the organizational breakdown of the document endorsed by the ICH 
Assembly at Step 4 of the ICH process, November 2023. 
3 We update guidances periodically.  To make sure you have the most recent version of a guidance, check the 
FDA guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents. 
1  Contains Nonbinding Recommendations 
The guidance is directed to common uses of analytical procedures, such as assay, potency, 
purity, impurity (quantitative or limit test), identity, or other quantitative or qualitative 
measurements.  
 
In general, FDAs guidance documents do not establish legally enforceable responsibilities.  
Instead, guidances describe the Agencys current thinking on a topic and should be viewed 
only as recommendations, unless specific regulatory or statutory requirements are cited.  The 
use of the word should in Agency guidances means that something is suggested or 
recommended, but not required.  
 
 
II.  GENERAL CONSIDERATIONS FOR ANALYTICAL PROCEDURE 
VALIDATION (2) 
 
This guidance indicates the data that should be presented in a regulatory submission. 
Analytical procedure validation data should be submitted in the corresponding sections of the 
application (ICH guideline M4Q(R1) The Common Technical Document for the Registration 
of Pharmaceuticals for Human Use: Quality)4. Relevant data collected during validation (and 
any methodology used for calculating validation results) should be submitted to demonstrate 
the suitability of the procedure for the intended purpose. Suitable data derived from 
development studies (see ICH Q14) can be used as part of validation data. When an 
established platform analytical procedure is used for a new purpose, validation testing can be 
abbreviated, if scientifically justified. 
 
Approaches other than those set forth in this guidance may be applicable and acceptable with 
appropriate  science-based  justification.  The  applicant  is  responsible  for  designing  the 
validation studies and protocol most suitable for their product.  
 
Reference materials, or other suitably characterized materials, with documented identity, 
purity, or any other characteristics as necessary should be used in the validation study.  
 
In practice, the experimental work can be designed so that the appropriate performance 
characteristics are considered simultaneously to provide sound, overall knowledge of the 
performance of the analytical procedure, for instance: specificity/selectivity, accuracy, and 
precision over the reportable range.  
 
As described in ICH Q14, the system suitability test is an integral part of analytical 
procedures and is generally established during development as a regular check of 
performance. Robustness is typically evaluated as part of development prior to the execution 
of the analytical procedure validation study (ICH Q14). Finally, the analytical procedure 
validation strategy is developed based on knowledge of the analytical procedure and the 
intended purpose. This includes the required analytical procedure performance to ensure the 
quality of the measured result (ICH Q14). If successfully executed, the analytical procedure 
validation strategy will demonstrate that the analytical procedure is fit for the intended 
purpose.  
 
 
4 Available at https://database.ich.org/sites/default/files/M4Q_R1_Guideline.pdf.  
2  Contains Nonbinding Recommendations 
A.  Analytical Procedure Validation Study (2.1) 
 
A validation study is designed to provide sufficient evidence that the analytical procedure 
meets its objectives. These objectives are described with a suitable set of performance 
characteristics and related performance criteria, which can vary depending on the intended 
purpose of the analytical procedure and the specific technology selected. Section III (3), 
Validation Tests, Methodology, and Evaluation, summarizes the typical methodologies and 
validation tests that can be used (see also Figure 2 in Appendix A (6. Annex 1) on selection 
of validation tests). Specific nonbinding examples for common techniques are given in 
Appendix B (7. Annex 2).  Table 1 (below) provides the measured quality attributes, typical 
performance characteristics and related validation tests, which are further illustrated in 
Appendix A (6. Annex 1). 
 
The validation study should be documented. Prior to the validation study, a validation 
protocol should be generated. The protocol should contain information about the intended 
purpose of the analytical procedure, the performance characteristics to be validated, and the 
associated criteria. In cases where prior knowledge is used (e.g., from development or from 
previous studies), appropriate justification should be provided. The results of the validation 
study should be summarized in a validation report. 
 
The experimental design of the validation study should reflect the number of replicates used 
in routine analysis to generate a reportable result. If justified, it may be acceptable to perform 
some validation tests using a different number of replicates or to adjust the number of 
replicates in the analytical procedure based on data generated during validation. 
 
Figure 1 (below) shows the interrelationship between ICH Q2 and ICH Q14 and how 
knowledge generated during analytical procedure development as described in ICH Q14 aids 
the design of a validation study. 
 
3  Contains Nonbinding Recommendations 
Table 1:  Typical Performance Characteristics and Related Validation Tests for 
Measured Quality Attributes 
 
   Measured Quality   IDENTITY  IMPURITY (PURITY)  ASSAY 
Attribute  Other Quantitative  Content or 
  Measurements (1)  Potency 
   
Analytical  Other 
Quantitative  Limit 
Procedure   Quantitative 
Test  Test 
Performance  Measurements (1) 
Characteristics to be 
Demonstrated (2) 
Specificity (3)         
  Specificity Test  +  +  +  + 
 
Range         
 Response  -  +  -  + 
(Calibration Model) 
 
  Lower Range Limit  -  QL  DL  - 
   
Accuracy (4)         
  Accuracy Test  -  +  -  + 
 
Precision (4)          
  Repeatability Test  -  +  -  + 
         
  Intermediate  -  + (5)  -  + (5) 
Precision Test 
- signifies that this test is not normally conducted. 
+ signifies that this test is normally conducted. 
 In some complex cases DL may also be evaluated. 
QL = quantitation limit; DL = detection limit. 
(1) Other quantitative measurements can follow the scheme for impurity, if the range limit is close to the 
DL/QL; other quantitative measurements can follow the scheme for assay (content or potency), if the range limit 
is not close to the DL/QL.  
(2) Some performance characteristics can be substituted with technology-inherent justification in the case of 
certain analytical procedures for physicochemical properties. 
(3) Lack of specificity of one analytical procedure should be compensated by one or more other supporting 
analytical procedures, unless appropriately justified.  
(4) Alternatively, a combined approach can be used to evaluate accuracy and precision.  
(5) Where reproducibility has been performed and intermediate precision can be derived from the 
reproducibility data set, an independent study for intermediate precision is not required.  
 
4  Contains Nonbinding Recommendations 
Figure 1: Validation Study Design and Evaluation 
 
 
ICH Q14 = International Council for Harmonisation (ICH) guidance for industry Q14 Analytical Procedure 
Development (March 2024). 
ICH Q2 = ICH guidance for industry Q2(R2) Validation of Analytical Procedures. 
 
B.  Validation During the Life Cycle of an Analytical Procedure (2.2) 
 
Changes may be required during the life cycle of a validated analytical procedure. In such 
cases, partial or full revalidation may be required. Science and risk-based principles can be 
used to justify whether or not a given performance characteristic needs revalidation. The 
extent of revalidation depends on the performance characteristics impacted by the change. 
 
Transfer of a validated analytical procedure should be considered in the context of analytical 
life cycle changes in line with ICH Q14. When transferring analytical procedures to a 
different laboratory, a partial or full revalidation of the analytical procedure performance 
characteristics and/or comparative analysis of representative samples should be performed. 
Justification for not performing additional transfer experiments should be provided if 
appropriate.  
 
Covalidation can be used to demonstrate that the analytical procedure meets predefined 
performance criteria by using data generated at multiple sites and could also satisfy the 
requirements of analytical procedure transfer at the participating sites. 
 
5  Contains Nonbinding Recommendations 
C.  Reportable Range (2.3) 
 
The required reportable range is typically derived from the specification and depends on the 
intended use of the procedure. The reportable range is confirmed by demonstrating that the 
analytical procedure provides results with acceptable response, accuracy, and precision. The 
reportable range should be inclusive of the upper and lower specification or reporting limits, 
as applicable.  
 
Table 2 (below) exemplifies recommended reportable ranges for common uses of analytical 
procedures; other ranges may be acceptable if justified. In some cases, (e.g., at low amounts) 
wider upper ranges may be more practical. 
 
D.  Demonstration of Stability-Indicating Properties (2.4) 
 
A validated quantitative analytical procedure that can detect changes in relevant quality 
attributes of a product during storage is considered to be stability indicating. To demonstrate 
specificity/selectivity of a stability-indicating test, samples containing relevant degradation 
products should be included in the study. These can include samples spiked with target 
analytes and known interferences; samples that have been exposed to various physical and 
chemical stress conditions; and actual product samples that are either aged or have been 
stored under stressed conditions.   
 
E.  Considerations for Multivariate Analytical Procedures (2.5) 
 
For multivariate analytical procedures, results are determined through a multivariate 
calibration model utilizing more than one input variable (e.g., a spectrum with many 
wavelength variables). The multivariate calibration model relates the input data to a value for 
the property of interest (i.e., the model output).  
 
Successful validation of a multivariate procedure should consider calibration, internal testing, 
and validation. 
 
Typically, development and validation are performed in two phases.  
 
  In the first phase, model development consists of calibration and internal testing. 
Calibration data are used to create the calibration model. Test data are used for 
internal testing and optimization of the model. The test data could be a separate set of 
data or part of the calibration set used in a rotational manner. This internal test step is 
used to obtain an estimate of the model performance and to fine-tune an algorithms 
parameters (e.g., the number of latent variables for partial least squares) to select the 
most suitable model within a given set of data. For more details, see ICH Q14. 
 
  In the second phase, model validation, a validation set with independent samples is 
used for validation of the model. For identification libraries, validation involves 
analyzing samples (i.e., challenge samples) not represented in the library to 
demonstrate the discriminative ability of the library model. 
 
6  Contains Nonbinding Recommendations 
Table 2: Examples of Reportable Ranges for Common Uses of Analytical Procedures 
 
Use of Analytical  Low End of Reportable  High End of Reportable 
Procedure  Range  Range 
Assay of a product (1)  80% of declared content or  120% of declared content or 
80% of lower specification  120% of the upper 
acceptance criterion   specification acceptance 
criterion  
Potency  Lowest specification  Highest specification 
acceptance criterion -20%  acceptance criterion +20% 
Content uniformity  70% of declared content   130% of declared content  
Dissolution:    
Immediate release   
  one point  Q -45% of the lowest 
specification  strength  
   
  multiple point  Lower limit of reportable  130% of declared content of 
specification  range (as justified by the  the highest strength  
specification) or QL, as 
  appropriate. 
Modified release  Lower limit of reportable 
range (as justified by the 
specification) or QL, as 
appropriate. 
Impurity (1)  Reporting threshold   120% of specification 
acceptance criterion 
Purity (as area %)  80% of lower specification  Upper specification 
acceptance criterion   acceptance criterion or 100%  
(1) Where assay and impurity are performed as a single test and only one standard is used, linearity should be 
demonstrated for both the reporting level of the impurities and up to 120% of the specification acceptance criterion 
for assay. 
QL = quantitation limit. 
 
Samples used for the validation of quantitative or qualitative multivariate procedures require 
values or categories assigned to each sample, typically obtained by a reference analytical 
procedure (i.e., a validated or pharmacopoeial procedure).  
 
When a reference analytical procedure is used, its performance should equal or exceed the 
expected performance of the multivariate analytical procedure. Analysis by the reference 
7  Contains Nonbinding Recommendations 
analytical procedure and multivariate data collection should be performed on the same 
samples (whenever possible) within a reasonable period of time to assure sample and 
measurement stability. In some cases, a correlation or conversion may be needed to provide 
the same unit of measure. Any assumptions or calculations should be described.   
 
 
III.  VALIDATION TESTS, METHODOLOGY, AND EVALUATION (3) 
 
In the following sections, experimental methodologies to evaluate the performance of an 
analytical procedure are described. These methodologies are grouped according to main 
performance characteristics dictated by the analytical procedure design. It is acknowledged 
that information about multiple performance characteristics may be derived from the same 
dataset. Different approaches may be used to demonstrate that the analytical procedure meets 
the objectives and related performance criteria, if justified. 
 
A.  Specificity/Selectivity (3.1) 
 
1.  General Considerations (3.1.1) 
 
The specificity or selectivity of an analytical procedure can be demonstrated through absence 
of interference or comparison of results to an orthogonal procedure. In some cases, 
specificity/selectivity may be inherently given by the underlying scientific principles of the 
analytical procedure. Some experiments can be combined with accuracy studies. 
 
Selectivity could be demonstrated when the analytical procedure is not specific. However, the 
test for an analyte to be identified or quantitated in the presence of potential interference 
should minimize that interference and demonstrate that the analytical procedure is fit for the 
intended purpose.  
 
Where one analytical procedure does not provide sufficient discrimination, a combination of 
two or more procedures is recommended to achieve the necessary specificity/selectivity.  
 
a.  Absence of interference (3.1.1.1) 
 
Specificity/selectivity can be shown by demonstrating that the identification and/or 
quantitation of an analyte is not impacted by the presence of other substances (e.g., 
impurities, degradation products, related substances, matrices, or other components likely to 
be present).  
 
b.  Orthogonal procedure comparison (3.1.1.2) 
 
Specificity/selectivity can be verified by demonstrating that the measured result of an analyte 
is comparable to the measured result of a second, well-characterized analytical procedure that 
ideally applies a different measurement principle.  
 
c.  Technology-inherent justification (3.1.13) 
 
In some cases where the specificity of the analytical technology can be ensured and predicted 
by technical parameters (e.g., resolution of isotopes in mass spectrometry, chemical shifts in 
8  Contains Nonbinding Recommendations 
nuclear magnetic resonance spectroscopy), additional experimental studies may not be 
required, if justified. 
 
2.  Recommended Data (3.1.2) 
 
a.  Identification (3.1.2.1) 
 
For identification tests, a critical aspect is to demonstrate the capability to identify the analyte 
of interest based on unique aspects of its molecular structure and/or other specific properties. 
The capability of an analytical procedure to identify an analyte can be confirmed by obtaining 
positive results comparable to a reference material using samples containing the analyte, 
along with negative results from samples, which do not contain the analyte. In addition, the 
identification test should be applied to materials structurally similar to or closely related to 
the analyte to confirm that a positive result is not obtained. The choice of such potentially 
interfering materials should be based on scientific judgement with a consideration of 
interferences that could occur.  
 
b.  Assay, purity, and impurity test(s) (3.1.2.2) 
 
The specificity/selectivity of an analytical procedure should be demonstrated to fulfill the 
accuracy requirements for the content or potency of an analyte in the sample.  
 
Representative data (e.g., chromatograms, electropherograms, spectra, biological response) 
should be used to demonstrate specificity and relevant components should be labeled, if 
appropriate.  
 
For separation techniques, suitable discrimination should be investigated at an appropriate 
level (e.g., for critical separations in chromatography, specificity can be demonstrated by the 
resolution of the two components, which elute closest to each other). Alternatively, spectra of 
different components could be compared to assess the possibility of interference. 
 
For nonseparation techniques (e.g., bioassay, enzyme-linked immunosorbent assay, 
quantitative polymerase chain reaction), specificity can be demonstrated through the use of 
reference materials or other suitably characterized materials to confirm the absence of 
interference in relation to the analyte. In cases where the analyte is a process-related impurity, 
specificity (noninterference) must also be confirmed against the product. 
 
In case a single procedure is not considered specific or sufficiently selective, an additional 
procedure should be used to ensure adequate discrimination. For example, where a titration is 
used to assay a drug substance for release, the combination of the assay and a suitable test for 
impurities may be used. 
 
Impurities or related substances are available or can be intentionally created: 
 
For assay or potency, discrimination of the analyte in the presence of impurities and/or 
excipients should be demonstrated. Practically, this can be performed by spiking product with 
appropriate amounts of impurities and consequently demonstrating that the assay result is 
unaffected by the presence of these materials (e.g., by comparison with the assay result 
obtained on unmanipulated samples). Alternatively, samples containing appropriate amounts 
of impurities could be generated through deliberate stressing of product materials. 
9  Contains Nonbinding Recommendations 
 
For a purity or impurity test, discrimination can be established by stressing or spiking product 
to achieve appropriate levels of impurities or related substances and demonstrating the 
absence of interference. 
 
Impurities or related substances are not available: 
 
If impurities, related substances, or degradation products cannot be prepared or isolated, 
specificity can be demonstrated by comparing the test results of samples containing typical 
impurities, related substances, or degradation products with an orthogonal procedure. The 
approach taken should be justified. 
 
B.  Range (3.2) 
 
1.  General Considerations (3.2.1) 
 
The range of an analytical procedure is the interval between the lowest and the highest results 
in which the analytical procedure has a suitable level of response, accuracy, and precision. 
The range can be validated through the direct assessment of reportable results (to generate a 
reportable range) using an appropriate calibration model (i.e., linear, nonlinear, multivariate). 
In some cases, the reportable range can be determined using one or more appropriate working 
ranges, depending on the sample preparation (e.g., dilutions) and the analytical procedure 
selected. 
 
Typically, a working range corresponds to the lowest and the highest sample concentrations 
or purity levels presented to the analytical instrument for which the analytical procedure 
provides reliable results. Mathematical calculations are typically required to generate 
reportable results. Reportable range and working range could be identical.  
 
In cases where materials of sufficient purity (or containing sufficient amounts of impurities) 
to validate the full range (e.g., 100 percent purity) cannot be generated, extrapolation of the 
reportable range may be appropriate and should be justified. 
 
2.  Response (3.2.2) 
 
a.  Linear response (3.2.2.1) 
 
A linear relationship between analyte concentration and response should be evaluated across 
the range of the analytical procedure to confirm the suitability of the procedure for the 
intended purpose. The response can be demonstrated directly on the product or suitable 
reference materials, separate weighings of analyte, or predefined mixtures of the components 
(e.g., by dilution of a solution of known content), using the proposed procedure.  
 
Linearity can be evaluated with a plot of signals as a function of analyte concentration or 
content and should demonstrate the analytical procedure capability across a given range to 
obtain values that are proportional to the true (known or theoretical) sample values. Test 
results should be evaluated by an appropriate statistical method (e.g., by calculation of a 
regression line by the method of least squares). 
 
10  Contains Nonbinding Recommendations 
Data derived from the regression line may help to provide mathematical estimates of the 
linearity. A plot of the data, the correlation coefficient or coefficient of determination, y-
intercept, and slope of the regression line should be provided. An analysis of the deviation of 
the actual data points from the regression line is helpful for evaluating linearity (e.g., for a 
linear response, the impact of any nonrandom pattern in the residuals plot from the regression 
analysis should be assessed).  
 
To assess linearity during validation, a minimum of five concentrations appropriately 
distributed across the range is recommended.  
 
The measured data can be mathematically transformed if necessary (e.g., through the use of a 
log function).  
 
Other approaches to the assessment of linearity should be justified. 
 
b.  Nonlinear response (3.2.2.2) 
 
Some analytical procedures may show nonlinear responses. In these cases, a model or 
function which can describe the relationship between the activity/concentration present and 
the response of the analytical procedure is necessary. The suitability of the model should be 
assessed by means of nonlinear regression analysis (e.g., coefficient of determination). 
 
For example, immunoassays or cell-based assays may show an S-shaped response. S-shaped 
test curves occur when the range of concentrations is wide enough that responses are 
constrained by upper and lower asymptotes. Common models used in this case are four- or 
five-parameter logistic functions, though other acceptable models exist.  
 
For these analytical procedures, the evaluation of linearity is separate from consideration of 
the shape of the concentration-response curve. Thus, linearity of the concentration-response 
relationship is not required. Instead, analytical procedure performance should be evaluated 
across a given range to obtain values that are proportional to the true (known or theoretical) 
sample values.  
 
c.  Multivariate calibration (3.2.2.3) 
 
Algorithms used for construction of multivariate calibration models can be linear or 
nonlinear, as long as the model is appropriate for establishing the relationship between the 
signal and the quality attribute of interest. The accuracy of a multivariate procedure is 
dependent on multiple factors, such as the distribution of calibration samples across the 
calibration range and the reference analytical procedure error.  
 
In multivariate analysis, the measured data are commonly pretreated through derivatives or 
normalization. 
 
Linearity assessment, apart from comparison of reference and predicted results, should 
include information on how the analytical procedure error (residuals) changes across the 
calibration range. Graphical plots can be used to assess the residuals of the model prediction 
across the working range. 
 
11  Contains Nonbinding Recommendations 
3.  Validation of Lower Range Limits (3.2.3) 
 
If the quality attribute to be measured requires the range of an analytical procedure to be 
close to the lower range limits of the procedure, detection limit (DL) and quantitation limit 
(QL), can be estimated using the following approaches.  
 
a.  Based on visual evaluation (3.2.3.1) 
 
Visual evaluation can be used for both noninstrumental and instrumental procedures. 
 
The limit is determined by the analysis of samples with known concentrations and by 
establishing the minimum level at which the analyte can be reliably resolved and detected or 
quantitated. 
 
b.  Based on signal-to-noise (3.2.3.2) 
 
This approach is relevant for 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. 
Alternatively, signals in an appropriate baseline region can be used instead of blank samples. 
The DL or QL are the minimum concentrations at which the analyte can be reliably detected 
or quantitated, respectively. A signal-to-noise ratio of 3:1 is generally considered acceptable 
for estimating the DL. For QL, a ratio of at least 10:1 is considered acceptable. 
 
The signal-to-noise ratio should be determined within a defined region and, if possible, 
situated equally around the place where the peak of interest would be found. 
 
c.  Based on the standard deviation of a linear response and a slope 
(3.2.3.3) 
 
The DL can be expressed as: 
 
 
3.3
while the QL can be expressed as:  DDDD =
SS
 
 
10
where     = the standard deviation QQoDDf t=he response 
SS
 
    S = the slope of the calibration curve 
 
The slope S can be estimated from the regression line of the analyte. The estimate of  can be 
carried out in a variety of ways, for example:  
 
Based on the standard deviation of the blank: 
 
Measurement of the magnitude of background response is performed by analyzing an 
appropriate number of blank samples and calculating the standard deviation of the responses.  
12  Contains Nonbinding Recommendations 
 
Based on the calibration curve: 
 
A specific calibration curve should be evaluated using samples containing an analyte in the 
range of the DL and QL. The residual standard deviation of a regression line (i.e., root mean 
square error/deviation) or the standard deviation of y-intercepts of the regression lines can be 
used as the standard deviation.  
 
d.  Based on accuracy and precision at lower range limits (3.2.3.4) 
 
Instead of using estimated values as described in the previous approaches, the QL can be 
directly validated by accuracy and precision measurements. 
 
e.  Recommended data (3.2.3.5) 
 
The DL and the approach used for its determination should be presented. If the DL is 
determined based on visual evaluation or based on signal-to-noise ratio, the presentation of 
the relevant data is considered an acceptable justification. 
 
In cases where an estimated value for the DL is obtained by calculation or extrapolation, this 
estimate can subsequently be validated by the independent analysis of a suitable number of 
samples known to be near or prepared at the DL.  
 
The QL and the approach used for its determination should also be presented. 
 
If the QL was estimated, the limit should be subsequently validated by the analysis of a 
suitable number of samples known to be near or at the QL. In cases where the QL is well 
below (e.g., approximately 10 times lower than) the reporting limit, this confirmatory 
validation can be omitted with justification. 
 
For impurity tests, the QL for the analytical procedure should be equal to or below the 
reporting threshold. 
 
C.  Accuracy and Precision (3.3) 
 
Accuracy and precision can be evaluated independently, each with a predefined acceptance 
criterion. Alternatively, accuracy and precision can be evaluated in combination.  
 
1.  Accuracy (3.3.1) 
 
Accuracy should be established across the reportable range of an analytical procedure and is 
typically demonstrated through comparison of the measured results with expected values. 
Accuracy should be demonstrated under regular test conditions of the analytical procedure 
(e.g., in the presence of sample matrix and using described sample preparation steps).  
 
Accuracy is typically verified through one of the studies described below. In certain cases, 
accuracy can be inferred once precision, response within the range, and specificity have been 
established.  
 
13  Contains Nonbinding Recommendations 
a.  Reference material comparison (3.3.1.1) 
 
The analytical procedure is applied to an analyte of known purity (e.g., a reference material, a 
well-characterized impurity, a related substance) and the measured versus theoretically 
expected results are evaluated.  
 
b.  Spiking study (3.3.1.2) 
 
The analytical procedure is applied to a matrix of all components except the analyte where a 
known amount of the analyte of interest has been added. In cases where all the expected 
components are impossible to reproduce, the analyte can be added to or enriched in the test 
sample. The results from measurements on unspiked and spiked/enriched samples are 
evaluated. 
 
c.  Orthogonal procedure comparison (3.3.1.3) 
 
The results of the proposed analytical procedure are compared with those of an orthogonal 
procedure. The accuracy of the orthogonal procedure should be reported. Orthogonal 
procedures can be used with quantitative impurity measurements to verify primary 
measurement values in cases where obtaining samples of all relevant components needed to 
mimic the matrix for spiking studies is not possible. 
 
d.  Recommended data (3.3.1.4) 
 
Accuracy should be assessed using an appropriate number of determinations and 
concentration levels covering the reportable range (e.g., three concentrations/three replicates 
each of the full analytical procedure). 
 
Accuracy should be reported as the mean percent recovery of a known added amount of 
analyte in the sample or as the difference between the mean and the accepted true value, 
together with an appropriate 100(1-) percent confidence interval (or justified alternative 
statistical interval). The observed interval should be compatible with the corresponding 
accuracy acceptance criteria, unless otherwise justified. 
 
For impurity tests, the approach for the determination of individual or total impurities should 
be described (e.g., weight/weight or area percent with respect to the major analyte). 
 
For quantitative applications of multivariate analytical procedures, appropriate metrics (e.g., 
root mean square error of prediction (RMSEP)) should be used. If RMSEP is found to be 
comparable to acceptable root mean square error of calibration, then this indicates that the 
model is sufficiently accurate when tested with an independent test set. Qualitative 
applications such as classification, misclassification rate, or positive prediction rate can be 
used to characterize accuracy.  
 
2.  Precision (3.3.2) 
 
Validation of tests for assay and for quantitative determination of impurity (purity) includes 
an investigation of precision. 
 
14  Contains Nonbinding Recommendations 
Precision should be investigated using authentic homogeneous samples or, if unavailable, 
artificially prepared samples (e.g., spiked matrix mixtures or samples enriched with relevant 
amounts of the analyte in question).  
 
a.  Repeatability (3.3.2.1) 
 
Repeatability should be assessed using: 
 
a) A minimum of nine determinations covering the reportable range for the procedure 
(e.g., three concentrations/three replicates each) 
 
or 
 
b) A minimum of six determinations at 100 percent of the test concentration. 
 
b.  Intermediate precision (3.3.2.2) 
 
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 different days, environmental conditions, analysts, and 
equipment, as relevant. Ideally, the variations tested should be based on and justified by using 
analytical procedure understanding from development and risk assessment (ICH Q14). 
Studying these effects individually is not necessary. The use of design of experiments studies 
is encouraged. 
 
c.  Reproducibility (3.3.2.3) 
 
Reproducibility is assessed by means of an interlaboratory trial. Investigation of 
reproducibility is usually not required for regulatory submission but should be considered in 
cases of standardization of an analytical procedure, for instance, for inclusion of procedures 
in pharmacopoeias and in cases where analytical procedures are conducted at multiple sites.   
 
d.  Recommended data (3.3.2.4) 
 
The standard deviation, relative standard deviation (coefficient of variation), and an 
appropriate 100(1-) percent confidence interval (or justified alternative statistical interval) 
should be reported. The observed interval should be compatible with the corresponding 
precision acceptance criteria, unless otherwise justified. 
 
Additionally, for multivariate analytical procedures, the routine metrics of RMSEP 
encompass accuracy and precision.  
 
3.  Combined Approaches for Accuracy and Precision (3.3.3) 
 
An alternative to separate evaluation of accuracy and precision is to consider their total 
impact by assessing against a combined performance criterion.  
 
Data generated during development may help determine the best approach and refine 
appropriate performance criteria to which combined accuracy and precision are compared. 
15  Contains Nonbinding Recommendations 
 
Combined accuracy and precision can be evaluated by use of a prediction interval, a tolerance 
interval, or a confidence interval. Other approaches may be acceptable if justified. 
 
a.  Recommended data (3.3.3.1) 
 
If a combined performance criterion is chosen, results should be reported as a combined 
value to provide appropriate overall knowledge of the suitability of the analytical procedure. 
If relevant to justify the suitability of the analytical procedure, the individual results for 
accuracy and precision should be provided as supplemental information. The approach used 
should be described. 
 
D.  Robustness (3.4) 
 
The evaluation of the analytical procedures suitability within the intended operational 
environment should be considered during the development phase and depends on the type of 
procedure under study. Robustness testing should show the reliability of an analytical 
procedure in response to deliberate variations in analytical procedure parameters as well as 
the stability of the sample preparations and reagents for the duration of the procedure, if 
appropriate. The robustness evaluation can be submitted as part of development data for an 
analytical procedure on a case-by-case basis or should be made available upon request.   
 
For further details, see ICH Q14. 
16  Contains Nonbinding Recommendations 
GLOSSARY (4) 
 
Accuracy 
 
The accuracy of an analytical procedure expresses the closeness of agreement between the 
value which is accepted either as a conventional true value or as an accepted reference value 
and the value or set of values measured. (International Council for Harmonisation guidance 
for industry Q2(R2) Validation of Analytical Procedures (ICH Q2))1 
 
Analytical procedure 
 
The analytical procedure refers to the way of performing the analysis. The analytical 
procedure should describe in sufficient detail the steps necessary to perform each analytical 
test. (ICH Q2) 
 
Analytical procedure parameter 
 
Any analytical factor (including reagent quality) or analytical procedure operational condition 
that can be varied continuously (e.g., flow rate) or specified at controllable, unique levels. 
(ICH guidance for industry Q14 Analytical Procedure Development (March 2024) (ICH 
Q14)) 
 
Analytical procedure validation strategy 
 
An analytical procedure validation strategy describes the selection of analytical procedure 
performance characteristics for validation. In the strategy, data gathered during development 
studies and system suitability tests can be applied to validation and an appropriate set of 
validation tests can be predefined. (ICH Q14) 
 
Calibration model 
 
A model based on analytical measurements of known samples that relates the input data to a 
value for the property of interest (i.e., the model output). (ICH Q2) 
 
Control strategy 
 
A planned set of controls, derived from current product and process understanding, that 
assures process performance and product quality. The controls can include parameters and 
attributes related to drug substance and drug product materials and components, facility and 
equipment operating conditions, in-process controls, finished product specifications, and the 
associated methods and frequency of monitoring and control. (ICH guidance for industry Q10 
Pharmaceutical Quality System (April 2009)) 
 
Covalidation 
 
Demonstration that the analytical procedure meets its predefined performance criteria when 
used at different laboratories for the same intended purpose. Covalidation can involve all (full 
 
1 We update guidances periodically. To make sure you have the most recent version of a guidance, check the 
FDA guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents.  
17  Contains Nonbinding Recommendations 
revalidation) or a subset (partial revalidation) of performance characteristics potentially 
impacted by the change in laboratories. (ICH Q2) 
 
Detection limit (DL) 
 
The detection limit is the lowest amount of an analyte in a sample, which can be detected but 
not necessarily quantitated as an exact value. (ICH Q2) 
 
Determination 
 
The reported value(s) from single or replicate measurements of a single sample preparation as 
per the validation protocol. (ICH Q2) 
 
Intermediate precision 
 
Intermediate precision expresses intralaboratory variations. Factors to be considered should 
include potential sources of variability, for example, different days, different environmental 
conditions, different analysts, and different equipment. (ICH Q2) 
 
Performance characteristic 
 
A technology independent description of a characteristic that ensures the quality of the 
measured result. Typically, accuracy, precision, specificity/selectivity, and range may be 
considered. Previous ICH Q2 guidance versions referred to this as validation characteristic. 
(ICH Q2) 
 
Performance criterion 
 
An acceptance criterion describing a numerical range, limit, or desired state to ensure the 
quality of the measured result for a given performance characteristic. (ICH Q14) 
 
Platform analytical procedure 
 
An analytical procedure that is suitable to test quality attributes of different products without 
significant change to its operational conditions, system suitability, and reporting structure. 
This type of analytical procedure can be used to analyze molecules that are sufficiently alike 
with respect to the attributes that the platform analytical procedure is intended to measure. 
(ICH Q2) 
 
Precision 
 
The precision of an analytical procedure expresses the closeness of agreement (degree of 
scatter) between a series of measurements obtained from multiple samplings of the same 
homogeneous sample under the prescribed conditions. Precision can be considered at three 
levels: repeatability, intermediate precision, and reproducibility. 
 
The precision of an analytical procedure is usually expressed as the variance, standard 
deviation, or coefficient of variation of a series of measurements. (ICH Q2) 
 
18  Contains Nonbinding Recommendations 
Quantitation limit (QL) 
 
The quantitation limit is the lowest amount of analyte in a sample which can be quantitatively 
determined with suitable precision and accuracy. The quantitation limit is a parameter used 
for quantitative assays for low levels of compounds in sample matrices and, particularly, is 
used for the determination of impurities and/or degradation products. (ICH Q2) 
 
Range 
 
The range of an analytical procedure is the interval between the lowest and the highest results 
in which the analytical procedure has a suitable level of precision, accuracy, and response. 
(ICH Q2) 
 
Reportable range 
 
The reportable range of an analytical procedure includes all values from the lowest to the 
highest reportable result for which there is a suitable level of precision and accuracy. 
Typically, the reportable range is given in the same unit as the specification acceptance 
criterion. (ICH Q2) 
 
Working range 
 
A working range corresponds to the lowest and the highest levels of the quality attribute 
to be measured (e.g., content, purity) as presented to the analytical instrument and for 
which the analytical procedure provides reliable results. (ICH Q2) 
 
Reference material 
 
A suitably characterized material, sufficiently homogeneous and stable with regard to one or 
more defined attributes, which has been established to be fit for the intended purpose. 
Reference materials may include national/international reference standards, pharmacopoeial 
reference standards, or in-house primary/secondary reference materials. (ICH Q2) 
 
Repeatability 
 
Repeatability expresses the precision under the same operating conditions over a short 
interval of time. Repeatability is also termed intraassay precision. (ICH Q2) 
 
Reportable result 
 
The result as generated by the analytical procedure after calculation or processing and 
applying the described sample replication. (ICH Q2) 
 
Reproducibility 
 
Reproducibility expresses the precision between laboratories (e.g., interlaboratory studies, 
usually applied to standardization of methodology). (ICH Q2) 
 
19  Contains Nonbinding Recommendations 
Response 
 
The response of an analytical procedure is its ability (within a given range) to obtain a signal 
which is effectively related to the concentration (amount) or activity of analyte in the sample 
by some known mathematical function. (ICH Q2) 
 
Revalidation 
 
Demonstration that an analytical procedure is still fit for the intended purpose after a change 
to the product, process, or the analytical procedure itself. Revalidation can involve all (full 
revalidation) or a subset (partial revalidation) of performance characteristics. (ICH Q2) 
 
Robustness 
 
The robustness of an analytical procedure is a measure of its capacity to meet the expected 
performance criteria during normal use. Robustness is tested by deliberate variations of 
analytical procedure parameters. (ICH Q14) 
 
Specificity/Selectivity 
 
Specificity and selectivity are both terms to describe the extent to which other substances 
interfere with the determination of an analyte according to a given analytical procedure. 
Specificity is typically used to describe the ultimate state, measuring unequivocally a desired 
analyte. Selectivity is a relative term to describe the extent to which particular analytes in 
mixtures or matrices can be measured without interferences from other components with 
similar behavior. (ICH Q2) 
 
System suitability test (SST) 
 
System suitability tests are developed and used to verify that the measurement system and the 
analytical operations associated with the analytical procedure are fit for the intended purpose 
and increase the detectability of unacceptable performance. (ICH Q14) 
 
Validation study 
 
An evaluation of prior knowledge, data, or deliberate experiments (i.e., validation tests) to 
determine the suitability of an analytical procedure for the intended purpose. (ICH Q2) 
 
Validation test 
 
Validation tests are deliberate experiments designed to authenticate the suitability of an 
analytical procedure for the intended purpose. (ICH Q2) 
 
Multivariate Glossary 
 
Calibration set 
 
A set of data with matched known characteristics and measured analytical results. (ICH Q14) 
 
20  Contains Nonbinding Recommendations 
Independent sample 
 
Independent samples are samples not included in the calibration set of a multivariate model. 
Independent samples can come from the same batch from which calibration samples are 
selected. (ICH Q2) 
 
Internal testing 
 
Internal testing is a process of checking if unique samples processed by the model yield the 
correct predictions (qualitative or quantitative). 
 
Internal testing serves as means to establish the optimal number of latent variables, estimate 
the standard error, and detect potential outliers. (ICH Q2) 
 
Latent variables 
 
Mathematically derived variables that are directly related to measured variables and are used 
in further processing. (ICH Q2) 
 
Model validation 
 
The process of determining the suitability of a model by challenging it with independent test 
data and comparing the results against predetermined performance criteria. (ICH Q2) 
 
Multivariate analytical procedure 
 
An analytical procedure where a result is determined through a multivariate calibration model 
utilizing more than one input variable. (ICH Q2) 
 
Reference analytical procedure 
 
A separate analytical procedure used to obtain the reference values of the calibration and 
validation samples for a multivariate analytical procedure. (ICH Q2) 
 
Validation set 
 
A set of data used to give an independent assessment of the performance of the calibration 
model. (ICH Q2) 
21  Contains Nonbinding Recommendations 
REFERENCES (5) 
 
International Council for Harmonisation guidance for industry Q10 Pharmaceutical Quality 
System (April 2009)1 
 
International Council for Harmonisation guidance for industry Q14 Analytical Procedure 
Development (March 2024) 
 
International Council for Harmonisation guideline M4Q(R1) The Common Technical 
Document for the Registration of Pharmaceuticals for Human Use: Quality2 
 
1 We update guidances periodically.  To make sure you have the most recent version of a guidance, check the 
FDA guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents.  
2 Available at https://database.ich.org/sites/default/files/M4Q_R1_Guideline.pdf. 
22  Contains Nonbinding Recommendations 
APPENDIX A: SELECTION OF VALIDATION TESTS (6. ANNEX 1) 
 
Figure 2: Examples of Relevant Validation Tests Based on the Objective of the Analytical Procedure 
 
 
23  Contains Nonbinding Recommendations 
APPENDIX B: ILLUSTRATIVE EXAMPLES FOR ANALYTICAL TECHNIQUES  
(7. ANNEX 2) 
 
The tables presented in this appendix are examples of approaches to analytical procedure 
validation for a selection of technologies. The technologies and approaches presented have 
been constructed to illustrate potential applications of the principles contained within this 
guidance and are not exhaustive. The examples are not intended to be mandatory, and 
alternative approaches (fulfilling the intent of the guidance) may also be acceptable.  
 
Table 3: Examples for Quantitative Separation Techniques 
 
Technique  Separation Techniques (e.g.,  Separation Techniques With 
HPLC, GC, CE) for Impurities  Relative Area Quantitation (e.g., 
or Assay  Product-Related Substances Such 
as Charge Variants) 
Performance  Validation Study Methodology 
Characteristic 
Specificity/  Absence of relevant interference:  Absence of relevant interference: 
Selectivity  With product, buffer, or  With product, buffer, or appropriate 
appropriate matrix, and between  matrix, and between individual peaks 
individual peaks of interest   of interest  
   
Spiking with known impurities/  Demonstration of stability-indicating 
excipients  properties through appropriate forced 
  degradation samples if necessary   
or    
 
By comparison of impurity 
profiles by an orthogonal 
analytical procedure 
 
Demonstration of stability-
indicating properties through 
appropriate forced degradation 
samples, if necessary 
Precision  Repeatability: 
Replicate measurements with 3 times 3 levels across the reportable range 
or 6 times at 100% level, considering peak(s) of interest  
  
Intermediate precision:  
e.g., different days, environmental conditions, analysts, equipment 
24  Contains Nonbinding Recommendations 
Technique  Separation Techniques (e.g.,  Separation Techniques With 
HPLC, GC, CE) for Impurities  Relative Area Quantitation (e.g., 
or Assay  Product-Related Substances Such 
as Charge Variants) 
Performance  Validation Study Methodology 
Characteristic 
Accuracy   For Assay:   Comparison with an orthogonal 
Comparison with suitably  procedure and/or suitably 
characterized material (e.g.,  characterized material (e.g., reference 
reference material)  material) 
   
or 
or 
 
 
Comparison with an orthogonal 
Accuracy can be inferred once 
procedure 
precision, linearity, and specificity 
 
For impurities or related  have been established  
substances:    
  or 
Spiking studies with impurities 
 
 
Spiking studies with forced 
or 
degradation samples and/or suitably 
 
Comparison of impurity profiles  characterized material 
with an orthogonal procedure 
Reportable range  Validation of calibration model  Validation of calibration model 
across the range:   across the range:  
    
Linearity: Dilution of the  Linearity: Between measured 
analytes of interest over the  (observed) relative result versus 
expected procedure range, at  theoretically expected relative result 
least 5 points   across specification range(s) (e.g., by 
  spiking or degrading material)  
Validation of lower range limits   
(for purity only): QL, DL  Validation of lower range limits: QL 
through a selected methodology  (and DL) through a selected 
(e.g., signal-to-noise  methodology (e.g., signal-to-noise 
determination)    determination) 
25  Contains Nonbinding Recommendations 
Technique  Separation Techniques (e.g.,  Separation Techniques With 
HPLC, GC, CE) for Impurities  Relative Area Quantitation (e.g., 
or Assay  Product-Related Substances Such 
as Charge Variants) 
Performance  Validation Study Methodology 
Characteristic 
Robustness and  Deliberate variation of relevant parameters, e.g.,  
other   
considerations  Sample preparation: extraction volume, extraction time, temperature, 
(performed as part  dilution 
of analytical   
procedure  Separation parameters: column/capillary lot, mobile phase/buffer 
development as  composition and pH, column/capillary temperature, flow rate, detection 
per International  wavelength 
Council for   
Harmonisation  Stability of sample and reference material preparations 
guidance for   
industry Q14  Relative Response Factors 
Analytical   
Procedure  If the analyte has a different response from the reference material (e.g., a 
Development)*   different specific UV absorbance), relative response factors should be 
calculated using the appropriate ratio of responses. This evaluation may 
be performed during validation or development, and should use the 
finalized analytical procedure conditions and be appropriately 
documented  
 
If the relative response factor is outside the range 0.8-1.2, then a 
correction factor should be applied. If an impurity/degradation product is 
overestimated, it may be acceptable not to use a correction factor 
HPLC = high-performance liquid chromatography; GC = gas chromatography; CE = capillary electrophoresis; 
QL = quantitation limit; DL = detection limit; UV = ultraviolet. 
* We update guidances periodically.  To make sure you have the most recent version of a guidance, check the 
FDA guidance web page at https://www.fda.gov/regulatory-information/search-fda-guidance-documents.  
 
Table 4: Example for Elemental Impurities by ICP-OES or ICP-MS  
 
Technique  Elemental Impurities by ICP-OES or ICP-MS 
Performance  Validation Study Methodology 
Characteristic 
Specificity/  Spiking of elements into matrix and demonstration of sufficient 
Selectivity  noninterference and confirmation of accuracy with the presence of 
components (e.g., carrier gas, impurities, matrix)  
 
or  
 
Justification through technology/prior knowledge (e.g., specificity of 
technology for certain isotopes) 
  
26  Contains Nonbinding Recommendations 
Technique  Elemental Impurities by ICP-OES or ICP-MS 
Performance  Validation Study Methodology 
Characteristic 
Precision  Repeatability:  
Replicate measurements with 3 times 3 levels across the reportable range 
or 6 times at 100% level, considering signals of interest  
 
Intermediate precision:  
e.g., different days, environmental conditions, analysts, equipment 
Accuracy   Spiking studies with impurities  
 
or 
 
Comparison of impurity profiles with an orthogonal procedure 
Reportable range  Validation of working range:  
  
Linearity: Dilution of the analytes of interest over the expected working 
range, at least 5 points, can be combined with multilevel accuracy 
experiment  
  
Validation of lower range: QL, DL through a selected methodology   
Robustness and  Deliberate variation of parameters and stability of test conditions, e.g.,  
other   
considerations  Sample digestion technique and preparation, nebulizer and sheath flow 
(performed as  settings, plasma settings  
part of analytical 
procedure 
development as 
per International 
Council for 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development)  
ICP-OES = inductively coupled plasma optical emission spectroscopy; ICP-MS = inductively coupled plasma 
mass spectrometry; QL = quantitation limit; DL = detection limit. 
 
27  Contains Nonbinding Recommendations 
Table 5: Example for Dissolution With HPLC as Product Performance Test for an 
Immediate Release Dosage Form  
 
Technique  Dissolution With HPLC as Product Performance Test for an 
Immediate Release Dosage Form 
Performance  Demonstration of Performance  Validation Testing Methodology 
Characteristic  of Dissolution Step  Typically demonstrated with final 
Typically demonstrated with  procedure 
development data 
Specificity/  Discriminatory power:   Absence of interference:  
Selectivity   Demonstration of the  Demonstration of noninterference 
discriminatory power to  with excipients and dissolution media 
differentiate between batches  likely to impact the quantitation of 
manufactured with different critical  the main analyte  
process parameters and/or critical 
material attributes, which may 
have an impact on the 
bioavailability (performed as part 
of development of dissolution step) 
Precision   Repeatability and intermediate  Repeatability and intermediate 
precision:    precision:    
Understanding of variability by  Demonstration with a homogeneous 
performing, e.g., vessel-to-vessel  sample from one dissolved tablet, 
repeatability studies or  e.g., several samples drawn from the 
intermediate precision studies  same vessel, after analyte in sample 
(operators, equipment)  has been fully dissolved  
Note: The study provides a    
combined assessment of variability 
of product quality and product 
dissolution performance in 
addition to the variability of the 
q uantitative procedure 
Accuracy   (Not applicable for dissolution  Spiking study:  
step)   Add known amounts of the reference 
material to the dissolution vessel 
containing excipient mixture in 
dissolution media and calculate 
recovery within defined working 
range  
28  Contains Nonbinding Recommendations 
Technique  Dissolution With HPLC as Product Performance Test for an 
Immediate Release Dosage Form 
Performance  Demonstration of Performance  Validation Testing Methodology 
Characteristic  of Dissolution Step  Typically demonstrated with final 
Typically demonstrated with  procedure 
development data 
Reportable  (Not applicable for dissolution  Validation of calibration model 
range    step)   across the range  
  
Linearity:  
Demonstrate linearity from sample 
concentrations (as presented to 
quantitative measurement) in the 
range of Q - 45% of the lowest 
strength up to 130% of the highest 
strength, for one point specification, 
and in the range of QL up to 130% of 
the highest strength, for multiple 
point specification 
 
If lower concentration ranges are 
expected to be close to QL:  
  
Validation of lower range limits, see 
separation techniques  
Robustness and  Justification of the selection of the  Deliberate variation of parameters of 
other  dissolution procedure parameters,  the quantitative procedure, see 
considerations  e.g., medium buffer composition,  separation technique  
(performed as  surfactant concentration, use of    
part of  sinkers, pH, deaeration, volume, 
analytical  a gitation rate, sampling time 
procedure 
development as 
per 
International 
Council for 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development) 
HPLC = high-performance liquid chromatography; QL = quantitation limit. 
 
29  Contains Nonbinding Recommendations 
Table 6: Example for Quantitative 1H-NMR for the Assay of a Drug Substance   
 
Technique  Quantitative 1H-NMR (Internal Standard Method) for the Assay of a 
Drug Substance 
Performance  Validation Study Methodology 
Characteristic   
Specificity/  Absence of interference: 
Selectivity   Select a signal which is representative for the analyte and does not show 
interference with potential baseline artifacts, residual water or solvent 
signals, related structure impurities or other impurities, internal 
standards, nontarget major component, or potential isomers/forms 
Precision  Repeatability: 
Replicate measurements of at least 6 independent preparations at 100% 
level 
 
Intermediate Precision:  
Not necessary to be conducted on target analyte (justified by technology 
principle, as typically verified through instrument calibration with a 
standard sample) 
Accuracy   Reference material comparison: 
Confirm with sample of known purity 
 
Reportable range  Validation tests are typically not necessary because the integral areas are 
usually directly proportional to the amount (mole) of reference material 
and analyte (technology-inherent justification) 
 
Robustness and  Deliberate variation of parameters, e.g., 
other  Temperature, concentration, field (shim), tuning and matching of the 
considerations  NMR probe, solution stability 
(performed as   
part of analytical   
procedure   
development as 
per International 
Council for 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development) 
1H-NMR = hydrogen-1 nuclear magnetic resonance. 
 
30  Contains Nonbinding Recommendations 
Table 7: Example for Biological Assays 
 
Technique  Binding Assay (e.g., ELISA, SPR) or Cell-Based Assay for 
Determination of Potency Relative to a Reference 
Performance  Validation Study Methodology 
Characteristic   
Specificity/  Absence of interference: 
Selectivity   Dose-response curve fulfills the response criteria demonstrating the 
similarity of the analyte and reference material, as well as noninterfering 
signal from the matrix (for binding assay), or no dose response from the 
cell line alone (for cell-based assay) 
 
Demonstration of stability-indicating properties through appropriate 
forced degradation samples if necessary 
 
Precision  Repeatability: 
Repeated sample analysis on a single day or within a short interval of 
time covering the reportable range of the analytical procedure (at least 3 
replicates over at least 5 levels) 
 
Intermediate Precision: Different analysts, multiple independent 
preparations over multiple days at multiple potency levels through the 
analytical procedures reportable range, inclusive of normal laboratory 
variation 
 
Accuracy   Reference material comparison: 
Assess recovery versus theoretical activity for multiple (at least 3) 
independent preparations at multiple (at least 5) levels through the 
analytical procedures reportable range 
 
Reportable range  Validation of range, including lower and higher range limits: 
The lowest to highest relative potency levels that meet accuracy, 
precision, and response criteria, determined over at least 5 potency levels  
 
Robustness and  Deliberate variation of parameters, e.g., 
other  Plate type, buffer components, incubation times, incubation conditions, 
instruments, reaction times, reagent lots including controls 
considerations 
 
(performed as 
For binding assay procedures: coating proteins, capture/detection 
part of analytical 
antibody  
procedure 
 
development as 
For cell-based assay procedures: cell density, effector/target cell ratio, 
per International 
cell generation number 
Council for 
 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development)  
ELISA = enzyme-linked immunosorbent assay; SPR = surface plasmon resonance. 
31  Contains Nonbinding Recommendations 
 
Table 8: Example for Quantitative PCR 
 
Technique  Quantitative PCR (quantitative analysis of impurities in drug 
substances or products) 
Performance  Validation Stud y Methodology 
Characteristic 
Specificity/Selectivity   Orthogonal Procedure Comparison:   
Test reaction specificity by gel electrophoresis, melting profile, or 
DNA sequencing  
 
Absence of interference:  
Positive template, no-reverse transcription control for RT-qPCR 
and no template control. Test primer and probe target specificity 
against gene bank with sequence similarity search program (e.g., 
nucleotide BLAST). Evaluate the slope of standard curve for 
efficiency  
Precision  Repeatability:   
Independent preparations of 5 positive control levels evenly 
distributed along the standard curve and assayed in triplicate within 
a single assay assessment. The results can be compared using (CV)  
 
Intermediate precision:  
At least 3 replicates per run at each positive control level in at least 
6 runs over 2 or more days 
Accuracy   Spiking Study: 
Test (e.g., n=6) replicates at 3 to 5 template spike levels from the 
standard curve concentrations  
 
Efficiency/consistency of RNA/DNA extraction method should be 
accounted for  
Reportable range  Linearity: 
Working range should cover at least 5 to 6 log to the base 10 
concentration values. Correlation coefficients or standard 
deviations should be calculated through the entire dynamic range  
  
Validation of lower working range limits based on the calibration 
curve:  
  
DL defined by template spiking in samples or from standard curves. 
DL is lowest point meeting the response curve parameters 
  
QL demonstrated through showing sufficient recovery and 
acceptable CVs from the accuracy experiment   
32  Contains Nonbinding Recommendations 
Technique  Quantitative PCR (quantitative analysis of impurities in drug 
substances or products) 
Performance  Validation Stud y Methodology 
Characteristic 
Robustness and other  Deliberate variation of parameters, e.g., 
considerations  Equipment, master mix composition (concentrations of salts, 
(performed as part of  dNTPs, adjuvants), master mix lots, reaction volume, probe and 
analytical procedure  primer concentrations, thermal cycling parameters 
development as per 
International Council 
for Harmonisation 
guidance for industry 
Q14 Analytical 
Procedure 
Development)  
qPCR = quantitative polymerase chain reaction; RT-qPCR = reverse transcription qPCR; CV = coefficient of 
variation; DL = detection limit; QL = quantitation limit; dNTPs = deoxynucleotide triphosphate. 
 
Table 9: Example for Particle Size Measurement 
 
Technique  Particle Size Measurement 
(Dynamic Light Scattering; Laser Diffraction Measurement) as a 
Property Test 
Performance  Validation Stud y Methodology 
Characteristic 
Specificity/  Absence of interference: 
Selectivity    
Evaluate blank and sample to determine the appropriateness of the 
e quipment settings and sample preparation  
Precision  Repeatability:  
Test at least 6 replicates using established analytical procedure 
parameters at target range  
 
Intermediate precision:  
Analysis performed on different days, environmental conditions, 
analysts, equipment setup 
  
Accuracy   Technology-inherent justification:  
Confirmed by an appropriate instrument qualification 
 
or 
 
Orthogonal procedure comparison: 
Qualitative comparison using a different technique, like optical 
microscopy, to confirm results 
Reportable range  T  echnology specific justification, e.g., particle size range covered 
Robustness and  Deliberate variation of parameters, e.g., 
other  Evaluation of expected size ranges for the intended use of the analytical 
considerations  procedure 
33  Contains Nonbinding Recommendations 
(performed as part   
of analytical  Dispersion stability for liquid dispersions (stability over potential 
procedure  analysis time, stir rate, dispersion energy equilibration or stir time 
development as  before measurement) 
per International   
Council for  Dispersion stability for dry dispersions (sample amount, measurement 
Harmonisation  time, air pressure and feed rate) 
guidance for   
industry Q14  Obscuration range (establish optimum percentage of laser obscuration) 
Analytical  U  ltrasound time/percentage for sample, if applicable  
Procedure 
Development)  
 
Table 10: Example for NIR Analytical Procedure  
 
Technique  NIR Analytical Procedure for Core Tablet Assay 
Performance 
Validation Stud y Methodology 
Characteristic 
Specificity/  Absence of interference: 
Selectivity    
Comparison of drug substance spectrum and the loading plots of the 
model  
 
Rejection of outliers (e.g., excipient, analogues) not covered by the 
multivariate procedure  
Precision  Repeatability:  
Repeated analysis with removal of sample from the holder between 
m  easurements 
Accuracy   Comparison with an orthogonal procedure:  
Demonstration across the range through comparison of the predicted 
and reference values using an appropriate number of determinations 
and concentration levels (e.g., 5 concentrations, 3 replicates)  
 
Accuracy is typically reported as the standard error of prediction (SEP 
or RMSEP) 
Reportable range  Response:  
Demonstration of the relationship between predicted and reference 
values 
  
Error (accuracy) across the range:  
Information on how the analytical procedure error (accuracy) changes 
across the calibration range, e.g., by plotting the residuals of the model 
prediction versus the actual data 
Robustness and  Deliberate variation of parameters, e.g., 
other  Chemical and physical factors that can impact NIR spectrum and 
considerations  model prediction should be represented in data sets. Examples include 
(performed as part  various sources of drug substance and excipients, water content, tablet 
of analytical  hardness, and orientation in the holder  
34  Contains Nonbinding Recommendations 
Technique  NIR Analytical Procedure for Core Tablet Assay 
Performance 
Validation Stud y Methodology 
Characteristic 
procedure   
development as  Note: NIR measurements are sensitive to changes in tablet composition 
per International  and properties outside variation present in the calibration set 
Council for 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development)  
NIR = near infrared; SEP = square error of prediction; RMSEP = root mean square error of prediction. 
 
Table 11: Example for Quantitative LC/MS 
 
Technique  Quantitative LC/MS Analysis of Trace Impurities in Product 
Performance 
Validation Stud y Methodology 
Characteristic 
Specificity/  Technology-inherent justification:  
Selectivity   Inferred through use of specific and selective MS detection (e.g., MRM 
transition with specified quantitative to qualitative ion ratio, accurate 
m/z value) in combination with retention time, consider potential for 
isotopes  
 
or  
 
Absence of interference from other components in sample matrix  
  
or 
 
Comparison of impurity profiles determined by an orthogonal analytical 
p rocedure  
Precision  Repeatability  
Measurement of a minimum of 3 replicates at each of at least 3 spiking 
levels or a minimum of 6 replicates at 100% 
  
Intermediate precision  
Comparison of measurements of the same samples performed in the 
same laboratory but under varying conditions (e.g., different LC/MS 
s ystems, different analysts, different days)   
Accuracy   Spiking study:  
Acceptable recovery of spiked impurity standards in sample matrix at 
multiple spiking levels  
  
or  
  
Comparison of the results to the true values obtained from an orthogonal 
p rocedure  
35  Contains Nonbinding Recommendations 
Technique  Quantitative LC/MS Analysis of Trace Impurities in Product 
Performance 
Validation Stud y Methodology 
Characteristic 
Reportable range  Validation of calibration model across the range:  
  
Linearity:  Experimental demonstration of the linear relationship 
between analyte concentrations and peak responses (or the ratio of peak 
response if an internal standard was used) with reference materials at 5 
or more concentration levels  
  
Validation of lower range limits:  
 
DL: Use the CV of responses at the spiking level (with 6 or more 
repeated injections) as a measure of signal-to-noise. The CV obtained 
must be less than or equal to a predefined acceptable value 
 
QL: The lowest spiking level with acceptable accuracy and precision   
  
The range extends from and is inclusive of the QL to the highest spiking 
l evel with acceptable accuracy, precision, and response  
Robustness and  Deliberate variation of parameters, e.g., 
other  LC flow rate, LC injection volume, MS drying/desolvation temperature, 
considerations  MS gas flow, mass accuracy, MS collision energy, stability of test 
(performed as part  conditions   
of analytical    
procedure    
development as 
per International 
Council for 
Harmonisation 
guidance for 
industry Q14 
Analytical 
Procedure 
Development)  
LC/MS = liquid chromatography/mass spectrometry; MRM = multiple reaction monitoring; CV = coefficient of 
variation. 
36