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The CHROMacademy Essential Guide to Chromatographic Method Validation

In this session, Dr. Mike Swartz (Ariad Pharmaceutical, Cambridge, MA) and Scott Fletcher (Technical Business Development Manager, Crawford Scientific), present an Introduction to Chromatographic Validation.  The session will consider topics such as why validate a chromatographic method?,  regulatory guidelines, eight steps of analytical method validation and a review of how and when to use statistical tests.  A must see for everyone working in a regulated environment requiring validated methods or those wishing to benefit from the increased confidence that method validation brings. The material in the tutorial reflects two excellent previous Validation Viewpoint articles from Mike and Ira Krull which can be found at the links below:
Analytical Method Validation: Back to Basics, Part I
Analytical Method Validation: Back to Basics, Part II


Scott Fletcher
Crawford Scientific
Dr. Mike Swartz
Ariad Pharmaceuticals

Topics include:

  • The Method Validation process
  • Guidelines on Implementing Analytical Method Validation (AMV)
  • Analytical performance characteristics - Accuracy, Limit of Detection, Limit of Quantification, Specificity / Selectivity, Linearity, Range, Robustness
  • Statistical tests used in AMV

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  Key Learning Objectives:

  • Understand why analytical method validation is required and how this fits into the overall validation process
  • Review the various government and other agencies who issue guidelines on method validation
  • Define the analytical performance characteristics investigated during method validation
  • Understand the applicability of validation tests to chromatographic methods
  • Introduce the statistical tests often employed during method validation and a review of the rigour they provide

The CHROMacademy Essential Guide to Chromatographic Method Validation
June 2011

Dr. Mike Swartz (Ariad Pharmaceutical, Cambridge, MA) and Scott Fletcher (Technical Business Development Manager, Crawford Scientific), present an Introduction to Chromatographic Validation. The material in the tutorial reflects two excellent previous Validation Viewpoint articles from Mike and Ira Krull which can be found at the links below:

Analytical Method Validation: Back to Basics, Part I

Analytical Method Validation: Back to Basics, Part II

In any regulated environment, analytical method validation (AMV) is a critical part of the overall process of validation. AMV is a part of the validation process that establishes, through laboratory studies, that the performance characteristics of the method meet the requirements for the intended analytical application and provides an assurance of reliability during normal use. Regulated laboratories must perform AMV to be in compliance with government or other regulators, in addition to being good science.

A well-defined and documented validation process can provide evidence not only that the system and method is suitable for its intended use, but can aid in transferring the method and satisfy regulatory compliance requirements.

"The process of providing documented evidence that something does what it is intended to do."

Validation is also the foundation of quality in the chromatographic laboratory, and AMV is just one part of a regulatory quality system that incorporates both quality control and quality assurance (1,2).

United States Food and Drug Administration, Guideline for submitting samples and analytical data for methods validation, February 1997. US Government Printing Office: 1990-281-794:20818

Since the late 1980s, government and other agencies (for example, FDA, International Conference on Harmonization-ICH) have issued guidelines on validating methods. In 1987, the FDA designated the specifications in the current edition of the United States Pharmacopeia (USP) as those legally recognized when determining compliance with the Federal Food, Drug, and Cosmetic Act (3,4). More recently, new information has been published, updating the previous guidelines and providing more detail and harmonization with International Conference on Harmonization (ICH) guidelines (5,6).

Presenters: Scott Fletcher
Crawford Scientific
Dr. Mike Swartz
Ariad Pharmaceuticals


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Critical FDA / ICH Analytical Method Validation Documents Guideline for Industry, Text on Validation of Analytical ProceduresICH-Q2(R1) November 2005

United States Food and Drug Administration, Guidance for Industry, Analytical Procedures and Methods Validation, Chemistry, Manufacturing, and Controls Documentation, August 2000

All International Conference on Harmonisation (ICH) – Quality guidance


When looking at the guidelines, one observes that AMV is just one part of the overall validation process that encompasses at least four distinct steps:

Figure 1: The Analytical Validation Process

The overall validation process begins with validated software and a validated (qualified) system; then a method is developed and validated using the qualified system. Finally, the whole process is wrapped together using system suitability. Each step is critical to the overall success of the process.

Software Validation

The overall validation process begins with validated software and a validated (qualified) system; then a method is developed and validated using the qualified system. Finally, the whole process is wrapped together using system suitability. Each step is critical to the overall success of the process.


Critical Documentation on Analytical Instrument Software Validation


FDA regulations 21 CFR part 11 outlines requirements for software validation, audit trails, record retention, and record copying.


Before undertaking the task of method validation, it is necessary to invest some time and energy up-front to ensure that the analytical system itself is validated, or qualified. Qualification is a subset of the validation process that verifies proper module and system performance before the instrument being placed on-line in a regulated environment. In March, 2003, the American Association of Pharmaceutical Chemists (AAPS), the International Pharmaceutical Federation (FIP), and the International Society for Pharmaceutical Engineering (ISPE) cosponsored a workshop entitled "A Scientific Approach to Analytical Instrument Validation" (10). Among other objectives, the various parties (the event drew a cross-section of attendees; users, quality assurance specialists, regulatory scientists, consultants, and vendors) agreed that processes are "validated" and instruments are "qualified," finally reserving the term validation for processes that include analytical methods–procedures and software development.

The proceedings of the AAPS et al. committee have now become the basis for a new general USP chapter, number 1058, on Analytical Instrument Qualification (AIQ) that originally appeared in the USP's Pharmacopeial Forum (11-13). The chapter details the AIQ process, data quality, roles and responsibilities, software validation, documentation, and instrument categories.


AAPS PharmSciTech 2004; 5 (1) Article 22, Qualification of Analytical Instruments for Use in the Pharmaceutical Industry: A Scientific Approach


Instruments are qualified according to a stepwise process grouped into four, not always distinct, phases:
figure 2
Figure 2: The Instrument Qualification Process

The DQ phase usually is performed at the vendor's site, where the instrument is developed, designed, and produced in a validated environment according to good laboratory practices (GLP), current good manufacturing practices (cGMP), and ISO 9000 standards. Whilst there appears little laboratory input into the DQ phase, it is worthwhile ensuring the instrument vendor can advise / aid in installation, training, servicing and on-going support during the lifetime of the instrument.

During the IQ phase, all of the activities associated with properly installing the instrument (new, pre-owned, or existing) at the users' site are documented. After the IQ phase is completed, testing is done to verify that the instrument and instrument modules operate as intended in an OQ phase. First, fixed parameters, for example, length, weight, height, voltage inputs, pressures, and so forth are either verified or measured against vendor-supplied specifications. Because these parameters do not change over the lifetime of the instrument, they usually are measured just once. Next, secure data handling is verified. Finally, instrument function tests are undertaken to verify that the instrument (or instrument modules) meets vendor and user specifications.

Instrument function tests should measure important instrument parameters according to the instruments' intended use and environment. For LC, the following types of tests might be included:

  • pump flow rate
  • detector wavelength accuracy
  • gradient linearity
  • injector precision, linearity, and accuracy
  • detector linearity
  • column oven temperature

Relevant OQ tests should be repeated whenever the instrument undergoes major repairs or modifications.
A timeline approach to Instrument Qualification is shown in Table 1

Timing and applicability
Before Purchase of a new instrument At installation of each instrument (new, old or existing unqualified) After installation or major repair of each instrument Periodically at specified intervals for each instrument
Assurance of vendors DQ System description* Fixed parameters* Preventative maintenance and repairs
Assurance of adequate support from manufacturer Instrument delivery   SOP for operation, calibration, maintenance and change control
Instrument fitness for use in laboratory Utilities, facility, environment    
  Network data and storage * Secure data storage, backup and archive*  
  Assembly and installation    
  Installation verification* Instrument function tests Performance tests*
Activities under each phase are usually performed as given in the table. However, in some cases, it may be appropriate to perform or combine a given activity with another phase, Activities spanning more than one phase are indicated (*)
Table 1: A timeline approach to Analytical Instrument Qualification (AIQ)

After an IQ and an OQ have been performed, PQ testing is conducted. PQ testing should be performed under the actual running conditions across the anticipated working range. In practice, a known method with known, predetermined specifications is used to verify that all of the modules are performing together to achieve their intended purpose. OQ and PQ frequently blend together in a holistic approach, particularly for injector linearity and precision (repeatability) tests, which can be conducted more easily at the system level. For HPLC, the PQ test should use a method with a well-characterized analyte mixture, column, and mobile phase.

PQ testing should be repeated at regular intervals; the frequency depends upon such things as the ruggedness of the instrument, and the criticality and frequency of use. PQ testing at periodic intervals also can be used to compile an instrument performance history.

Figure 3 shows an example of a "vendor" PQ test method that incorporates the essence of a holistic OQ and PQ test. PQ tests should incorporate the essence of the system suitability section of the general chromatography chapter 621 in the USP (15) to show suitability under conditions of actual use.

figure 3  

Figure 3: Example of a vendor PQ test.  Column: 75mm x 4.6mm, 3.5mm Symmetry C18 (Waters, Milford, Massachusetts); temperature: 30oC; mobile phase: 40:60 (v/v) water-methanol;  flow rate: 1.0 mL/min; injection volume: 20L; detection: UV absorbance at 254 nm. Peaks: 1 - acetone (t0), 2 - acetophenone, 3 - propiophenone, 4 - butyrophenone (0.01 mg/mL each in water)


According to the USP, system suitability tests are an integral part of chromatographic methods (14). These tests are used to verify that the resolution and reproducibility of, for example, a chromatographic system, are adequate for the analysis to be performed. System suitability tests are based upon the concept that the equipment, electronics, analytical operations, and samples constitute an integral system that can be evaluated as a whole.

System suitability is the checking of a system to ensure system performance before or during the analysis of unknowns. Parameters such as plate count, tailing factors, resolution, and reproducibility (%RSD [%Coefficient of variation] retention time and area or height for repetitive injections) are determined and compared against the specifications set for the method. However, samples consisting of only a single peak (for example, a drug substance assay in which only the API is present) can be used, provided that a column plate number specification is included in the method. Unless otherwise specified by the method, data from five replicate injections of the analyte are used to calculate the relative standard deviation if the method requires RSD > 2%; data from six replicate injections are used if the specification is RSD ≤ 2%. These parameters are measured during the analysis of a system suitability "sample" that is a mixture of main components and expected byproducts. Table 2 lists the terms to be measured and their recommended limits obtained from the analysis of the system suitability sample (15).

Parameter Recommendation
Retention factor (k) The peak should be well resolved from other peaks and the void volume generally k>2.0
Repeatability RSD ≤ 1% for n ≥ 5 is desirable
Relative retention Not essential provided resolution is stated
Resolution (Rs) Rs > 2 between the peak of interest and the closest eluting potential interferent (impurity, excipient, degradation product, internal standard etc.)
Tailing factor (T) T ≤ 2
Theoretical plate (N) In general N > 20,000
Table 2: System suitability parameters and recommendations

System suitability tests must be carried out before the analysis of any samples in a regulated environment. Following blank injections of mobile phase, water, or sample diluent, replicate system suitability injections are made, and the results compared against method specifications. If specifications are met, subsequent analyses can continue. If the method's system suitability requirements are not met, any problems with the system or method must be identified and remedied (perhaps as part of a formal out-of-specification (OOS) investigation), and passing system-suitability results must be obtained before sample analysis is resumed.

To provide confidence that the method runs properly, it is also recommended that additional system suitability samples (quality control samples or check standards) are run at regular intervals (interspersed throughout the sample batch); %-difference specifications should be included for these interspersed samples, to make sure the system still performs adequately over the course of the entire sample run.

As previously mentioned, USP compendial methods are considered to be validated, however, adjustments to USP methods are allowed to meet system-suitability requirements. In 1998, Furman and colleagues proposed a way to classify allowable adjustments (16). But it was not until 2005 that guidance appeared on the topic (17–19). Although USP guidance on this topic recently was included into USP Chapter 621 on chromatography (14), the FDA Office of Regulatory Affairs (ORA) has had guidance in place for a number of years.

FDA ORA Laboratory Procedure, #ORA-LAB.5.4.5, USFDA ( 09/09/2005)

Table 3 summarizes the adjustments allowed for various HPLC parameters taken from both the USP and ORA documents. Adjustments outside of the ranges listed in Table 3 constitute modifications, or changes, which are subject to additional validation.


Parameter Maximum specification Comments
pH + 0.2 units  
Buffer salt concentration + 10% Providing the pH variation is met
Ratio of components in the mobile phase Components specified at 50% or less: + 30% or + 2% absolute, whichever is larger; maximum change of + 10% absolute; no component can be reduced to zero  
UV detector wavelength No deviations A validated procedure must be used to very wavelength error is £ 3nm
Column length + 70%  
Column internal diameter + 50% (ORA)
Can be adjusted such that the linear velocity is kept constant (USP)
For linear velocity equation, see equation below
Flow rate Additionally, the flow rate can be adjusted by ±50%
Injection volume Reduced as far as consistent with accepted precision and detection limits  
Particle size Reduced by as much as 50%  
Column temperature + 20% (ORA)
+ 10% (USP)
Column thermostating is recommended to improve control and reproducibility of retention time
Table 3: Maximum specifications for adjustments to HPLC operating conditions

Several parameters, generally referred to as analytical performance characteristics, may be investigated during any method validation protocol depending upon the type of method and its intended use. These analytical performance characteristics, which we have over the years affectionately referred to as "The Eight Steps of Analytical Method Validation," are illustrated in Figure 4.

figure 4
FIgure 4: Analytical method validation performance characteristics.

Although most of these terms are familiar and are used daily in any regulated chromatographic laboratory, they sometimes mean different things to different people. To avoid any confusion, it is necessary to have a complete understanding of the terms, definitions, and methodology as discussed in the following sections. Typical acceptance criteria are listed in Table 4, these are for reference only as individual acceptance criteria will be dictated by the matrix, concentration and method type.

Parameter Acceptable Criteria
System suitability Resolution between API and nearest impurity ≥2.5
  Retention Time 5 + 1 min
  Overall standard precision (five injections) Area, tr RSD ≤2%
  Tailing factor ≤2.5
  Plate count >5000
Specificity All peaks are resolved from one another in the chromatogram and diluent blank
Linearity r2 ≥0.99 for a range of 0.05 – 0.15 μg/mL (target concentration of 0.1 μg/mL)
Accuracy Average recover at 0.05 μg/mL and 0.1 μg/mL 98 – 102%
Precision (repeatability) RSD ≤2%
Precision (intermediate) RSD ≤2% on individual basis 2%
  RSD ≤5% overall
LOD S/N ≥3
LOQ Target S/N ≥10, RSD ≤20%
Robustness Meet system suitability Rs and %RSD requirements for all experiments and samples
≤20% difference from original method conditions
Stability (stock standard) ≤10% difference from assay value at time 0
Solution stability (samples) ≤10% difference from assay value at time 0
Table 4: Example method validation protocol acceptance criteria

Accuracy ‘The closeness of test results obtained by the method to the true value’

Accuracy is the measure of exactness of an analytical method or the closeness of agreement between an accepted reference value and the value found in a sample. Established across the range of the method, accuracy is measured as the percent of analyte recovered by the assay. For drug substances, accuracy measurements are obtained by comparison of the results to the analysis of a standard reference material, or by comparison to a second, well-characterized method. For the assay of the drug product, accuracy is evaluated by the analysis of synthetic mixtures (containing all excipient materials in the correct proportions) spiked with known quantities of components. For the quantification of impurities, accuracy is determined by the analysis of samples (drug substance or drug product) spiked with known amounts of impurities (if impurities are not available, see specificity).

Accuracy is often determined concurrently with precision, linearity and specificity, often through analysis of test samples under conditions defined within the analytical method.

figure 5
FIgure 5: Relationship between Accuracy and Precision in Analytical Method Validation. Only methods which are both precise and accurate are acceptable.

To document accuracy, the guidelines recommend that data be collected from a minimum of nine determinations over a minimum of three concentration levels covering the specified range (that is, three concentrations, three replicates each). The data should be reported as the percent recovery of the known, added amount, or as the difference between the mean and true value with confidence intervals (for example, ± 1 SD).

Acceptability criteria are defined by the end user but rarely would one want accuracy which falls outside the range 97 – 103% of the nominal (label claim) value. Statistical rigour can be applied by use of a one sample t-test.


Precision ‘The measure of the degree of agreement among test results when the method is applied repeatedly to multiple samplings of a homogeneous sample‘

Precision is commonly performed as three measurements: repeatability, intermediate precision, and reproducibility.

Repeatability - refers to the ability of the method to generate the same results over a short time interval under identical conditions (intra-assay precision). To document repeatability, the guidelines suggest analyzing a minimum of nine determinations covering the specified range of the procedure (that is, three levels or concentrations, three repetitions each) or a minimum of six determinations at 100% of the test or target concentration. Repeatability results are typically reported as % RSD. This is not to be confused with injector / instrument precision which forms part of the system suitability tests with relation to the instrument qualification.

Intermediate precision - refers to the agreement between the results from within-laboratory variations due to random events that might occur when using the method, such as different days, analysts, or equipment. To determine intermediate precision, an experimental design should be used (Plackett Burman, Anova etc. ) so that the effects (if any) of the individual variables can be monitored. Intermediate precision results are typically generated by two analysts who prepare and analyze replicate sample preparations. Each analyst would prepare his or her own standards and solutions, and might use a different HPLC system for the analysis. The %-difference in the mean values between the two analysts' results are subjected to statistical testing (for example, a Student's t-test) to examine if there is a difference in the mean values obtained.

Reproducibility - refers to the results of collaborative studies among different laboratories. Documentation in support of reproducibility studies should include the standard deviation, the relative standard deviation (or coefficient of variation), and the confidence interval. To generate data to demonstrate reproducibility, a typical experimental design might include analysts from two laboratories (possibly different from the analysts involved in the intermediate precision) preparing and analyzing replicate sample preparations Again, each analyst would prepare his or her own standards and solutions and use a different HPLC system for analysis. Results are reported as % RSD, and the %-difference in the mean values between the two analysts must be within specifications. Statistical calculations could also be carried out to determine if there is any difference in the mean values obtained.

Acceptance Criteria -

  • Less than 2% relative standard deviation is often recommended
  • Less than 5% RSD can be acceptable for minor components
  • Up to 10% RSD may be acceptable near the limit of quantitation
Past USP guidelines included the term ruggedness, defined as the degree of reproducibility of test results obtained by the analysis of the same samples under a variety of conditions, such as different laboratories, analysts, instruments, reagent lots, elapsed assay times, assay temperature, or days. Ruggedness is a measure of the reproducibility of test results under the variation in conditions normally expected from laboratory to laboratory and from analyst to analyst. The use of the term ruggedness, however, is falling out of favour and is not used by the ICH, but is instead addressed in guideline Q2 (R1) (Q2A and Q2B) under the discussion of intermediate precision.


Specificity ‘The ability to measure accurately and specifically the analyte of interest in the presence of other components that may be expected to be present in the sample‘

Specificity takes into account the degree of interference from:
  • other active ingredients
  • excipients
  • impurities
  • degradation products
  • placebo ingredients
  • matrices

Specificity in a method ensures that a peak's response is due to a single component (no peak coelutions). Specificity for a given analyte is commonly measured and documented by resolution, plate number (efficiency), and tailing factor.

For identification purposes, specificity is demonstrated by the ability to discriminate between other compounds in the sample or by comparison to known reference materials. For assay and impurity tests, specificity can be shown by the resolution of the two most closely eluted compounds. These compounds usually are the major component or active ingredient and a closely eluted impurity.

  • If impurities are available, it must be demonstrated that the assay is unaffected by the presence of spiked materials (impurities or excipients).
  • If the impurities are not available, the test results are compared to a second well-characterized procedure. For assay, the two results are compared. Additionally samples can be suitably ‘stressed’ in order to induce likely degradation products.21
  • For impurity tests, the impurity profiles are compared. Comparison of test results will vary with the particular method, but it may include visual comparison as well as retention times, peak areas (or heights), and peak shape.

Starting with the publication of USP 24, and as a direct result of the ICH process, it is now recommended that a peak-purity test based upon photodiode-array (PDA) detection or mass spectrometry (MS) be used to demonstrate specificity in chromatographic analyses by comparison to a known reference material. Modern PDA technology is a powerful tool to evaluate specificity. PDA detectors can collect spectra across a range of wavelengths at each data point collected across a peak, and through software processes, each spectrum can be compared to determine peak purity. Used in this manner, PDA detectors can distinguish minute spectral and chromatographic differences not readily observed by simple overlay comparisons.

However, PDA detectors can be limited on occasion in the evaluation of peak purity by a lack of UV response, as well as by the noise of the system and the relative concentrations of interfering substances. Also, the more similar the spectra are, and the lower the relative absorbances, the more difficult it is to distinguish coeluted compounds. MS detection overcomes many of the limitations of a PDA, and in many laboratories it has become the detection method of choice for method validation. MS can provide unequivocal peak purity information, exact mass, and structural and quantitative information. The combination of both PDA and MS on a single HPLC instrument can provide valuable orthogonal information to help ensure that interferences are not overlooked during method validation.


The limit of detection (LOD) is defined as the lowest concentration of an analyte in a sample that can be detected, but not necessarily quantitated. It is a limit test that specifies whether or not an analyte is above or below a certain value.

The limit of quantitation (LOQ) is defined as the lowest concentration of an analyte in a sample that can be quantitated with acceptable precision and accuracy under the stated operational conditions of the method.

In a chromatography laboratory, the most common way of determining both the LOD and the LOQ is using signal-to-noise ratios (S/N), commonly:

  • 3:1 for LOD
  • 10:1 for LOQ

Another method that is gaining popularity is a means of calculating the limits based upon the following formula: LOD or LOQ = K(SD/S)

where K is a constant (3 for LOD, 10 for LOQ), SD is the standard deviation of response, and S is the slope of the calibration curve.
It should be noted that determination of these limits is a two-step process. Regardless of the method used to determine the limit, an appropriate number of samples needs to be analyzed at the limit, once calculated, to fully validate the method performance at the limit.


Linearity is the ability of the method to provide test results that are directßly proportional to analyte concentration within a given range.

Range is the interval between the upper and lower concentrations of an analyte (inclusive) that have been demonstrated to be determined with acceptable precision, accuracy, and linearity using the method as written.

The range is normally expressed in the same units as the test results obtained by the method (for example, ng/mL). Guidelines specify that a minimum of five concentration levels be used to determine the range and linearity, along with certain minimum specified ranges depending upon the type of method. Table 5 summarizes typical minimum ranges specified by the guidelines. Data to be reported generally include the equation for the calibration curve line, the coefficient of determination (r2 ), residuals, and the curve itself.

Type of method Recommended minimum range
Assay 80 – 120% of the target concentration
Impurities From the reporting level of each impurity, to 120% of the specification
Content Uniformity 70 – 130% of the test concentration
Dissolution + 20% over the specified range of the dissolution test
Note that for toxic or more potent impurities, the range should be commensurate with the controlled level
Table 5: Example minimum recommended ranges

Robustness: A measure of its capacity to obtain comparable and acceptable results when perturbed by small but deliberate variations in procedural parameters listed in the documentation.

Robustness provides an indication of the method's suitability and reliability during normal use. During a robustness study, method parameters are intentionally varied to study the effects on analytical results. The key word in the definition is deliberate. Examples of HPLC variations are illustrated in Tables 6 and 7 for isocratic and gradient methods, respectively. Variations should be chosen symmetrically around a nominal value, or about the value specified in the method, to form an interval that slightly exceeds the variations that can be expected when the method is implemented or transferred. For instrument settings, manufacturers' specifications are sometimes used to determine variability.

The range evaluated during the robustness study should not be selected to be so wide that the robustness test will purposely fail, but rather to represent the type of variability routinely encountered in the laboratory. Challenging the method to the point of failure is not necessary. After robustness is demonstrated over a given range of a parameter, the value of that parameter can be adjusted within that range to meet system suitability without a requirement to revalidate the method. This premise is also the underpinning strategy behind the Quality by Design (QbD) approach to method robustness determination, which defines the ‘control space’, the set of variable ranges under which the method can operate whilst still producing fit for purpose results.

Factor Limit range
Organic solvent concentration +  2 – 3%
Buffer concentration +  1 – 2%
Buffer pH (if applicable) +  0.1 – 0.2 pH units
Temperature + 3oC
Flow rate +  0.1 – 0.2 mL/min.
Detector wavelength +  2-3 nm for 5-nm bandwidth
Injection volume Depends on injection type and size
Column lots 2 – 3 different lots
Table 6: Example isocratic separation robustness variations
Factor Limit range
Initial gradient hold time +  10 – 20 % of hold time
Slope and time The slope is determined by the gradient range and time.  It is recommended to adjust the gradient time
by + 10 – 20% and allow the slope to vary
Final hold time Adjusted to allow last-eluted compound to appear in chromatogram
Table 7: Example isocratic separation robustness variations

Robustness should be tested late in the development of a method, and if not, is typically one of the first parameters investigated during method validation. Throughout the method development process, however, attention should be paid to the identification of which chromatographic parameters are most sensitive to small changes so that when robustness tests are undertaken the appropriate variables can be tested. Robustness studies are also used to establish system suitability parameters to make sure the validity of the entire system (including both the instrument and the method) is maintained throughout method implementation and use. In addition, if the results of a method or other measurements are susceptible to variations in method parameters, these parameters should be adequately controlled and a precautionary statement included in the method documentation. Common HPLC parameters used to measure and document robustness include (for information about how to calculate, see reference 20)

  • critical peak pair resolution Rs
  • column plate number N (or peak width in gradient elution)
  • retention time tR
  • tailing factor TF
  • peak area (and height) and concentration

Replicate injections will improve the estimates (for example, %RSD) of the effect of a parameter change. In many cases, multiple peaks are monitored, particularly when some combination of acidic, neutral, or basic compounds are present in the sample.

Very often experimental design is used to produce a set of experiments in which multiple parameters are altered. Analysis of variance (ANOVA) is then typically used to decipher the results and calculate the most important variables within the experiment and the ranges over which these can be altered before the results are considered to be Out of Specification (OOS).

A common question that arises during the development of analytical method validation protocols is defining robustness parameters versus intermediate precision or reproducibility parameters. A simple rule of thumb:

If it is internal or written into the method (for example, temperature and flow rate) it is a robustness parameter; if it is external to the method (for example, the analyst, instrument number, or day) it is an intermediate precision (formerly ruggedness) parameter.

In other words, you would write a method to reflect flow rate, temperature, wavelength, buffer composition, and pH, but you would never write into a method: "Jim runs the method on Tuesdays on Column Lot # 42587 on System Six" — those are all intermediate precision parameters.


Solution (Autosampler) Stability

While not formally listed in the guidelines, it is also quite common to investigate sample and standard stability during validation. The stability of both the samples and the stock reference standard solution is evaluated at different time intervals (for example, at time 0, 3, and 7 days), in both flasks and vials, in amber and colourless glassware, following storage at both room temperature and refrigeration. This information is used to determine how often standards need to be prepared, how they (and the samples) should be stored, and how quickly the samples must be analyzed following preparation. In order to apply statistical rigour a paired t-test can be employed.


Several types of methods are used to measure the active pharmaceutical ingredient (API) and impurities, related substances, and excipients and the USP recognizes that is it not always necessary to evaluate every analytical performance parameter for every method. The type of method and its intended use dictate which performance characteristics need to be investigated, as summarized in Table 8. Both the USP and ICH divide analytical methods into four separate categories:

  • Category 1: Assays for the quantification of major components or active ingredients
  • Category 2: Determination of impurities or degrad ation products
  • Category 3: Determination of performance characteristics
  • Category 4: Identification tests
Category 1:
Category 2: Impurities Category 3:
Specific Tests
Category 4:
Quantitative Limit Tests
Accuracy Yes Yes * * No
Precision Yes Yes No Yes No
Specificity Yes Yes Yes * Yes
LOD No No Yes * No
LOQ No Yes No * No
Linearity Yes Yes No * No
Range Yes Yes No * No
Robustness Yes Yes No Yes No
*May be required, depending upon type of test.  For example, although dissolution testing falls into Category 3, as a quantitative test, measurements typical of Category 1 are used (with some exception)
Table 8: Measured analytical performance characteristics vs’ method type

Category 1 Methods
Category 1 tests target the analysis of major components and include methods such as content-uniformity and potency-assay analyses. The latter methods, while quantitative, are not usually concerned with low concentrations of analyte, but only with the amount of the API in the drug product. Because of the simplicity of the separation (the API must be resolved from all interferences, but any other peaks in the chromatogram do not need to be resolved from each other), emphasis is on speed over resolution. For assays in Category 1, LOD and LOQ evaluations are not necessary because the major component or active ingredient to be measured is normally present at high concentrations. However, because quantitative information is desired, all of the remaining analytical performance parameters are pertinent and may be investigated.

Category 2 Methods
Category 2 tests target the analysis of impurities or degradation products (among other applications). These assays usually look at much lower analyte concentrations than Category 1 methods, and are divided into two subcategories: quantitative and limit tests. If quantitative information is desired, a determination of LOD is not necessary, but the remaining parameters are required. Methods used in support of stability studies (referred to as stability-indicating methods) are an example of a quantitative Category 2 test. The situation reverses itself for a limit test. Because quantitation is not required, it is sufficient to measure the LOD and demonstrate specificity and robustness. For a Category 2 limit test, it is only necessary to show that a compound of interest is either present or not — that is, above or below a certain concentration. Methods in support of cleaning validation and environmental EPA methods often fit into this category. Although, as seen in Table 8, it is never necessary to measure both LOD and LOQ for any given Category 2 method, but it is common during validation to evaluate both characteristics.

Category 3 Methods
The parameters that must be documented for methods in USP-assay Category 3 (specific tests or methods for performance characteristics) are dependent upon the nature of the test. Dissolution testing is an example of a Category 3 method. Because it is a quantitative test optimized for the determination of the API in a drug product, the validation parameters evaluated are similar to a Category 1 test for a formulation designed for immediate release. However, for an extended-release formulation, where it might be necessary to confirm that none of the active ingredient has been released from the formulation until after a certain time point, the parameters to be investigated would be more like a quantitative Category 2 test that includes LOQ. Because the analytical goals may differ, the Category 3 evaluation parameters are dependent upon the actual method, as indicated in Table 8.

Category 4 Methods
Category 4 identification tests are qualitative in nature, so only specificity is required. For example, identification can be performed by comparing the retention time or a spectrum to that of a known reference standard. Freedom from interferences is all that is necessary in terms of chromatographic separation.



  1. United States Food and Drug Administration, Guideline for submitting samples and analytical data for methods validation, February 1997. US Government Printing Office: 1990-281-794:20818
  2. Current Good Manufacturing Practice in Manufacturing, Processing, Packing, or Holding Of Drugs, 21 CFR Part 210
  3. Current Good Manufacturing Practice for Finished Pharmaceuticals, 21 CFR Part 211
  4. USP 32-NF 27, August 2009, Chapter 1225.
  5. Analytical Procedures and Method Validation. Fed. Reg. 65(169), 52,776-52,777, 30 August 2000.
  6. International Conference on Harmonization, Harmonized Tripartite Guideline, Validation of Analytical Procedures, Text and Methodology, Q2(R1), November 2005
  7. Guidance for Industry Computerized Systems Used in Clinical Investigations, FDA May 2007.
  8. FDA, 21 CFR Part 11, "Electronic Records; Electronic Signatures; Final Rule." Federal Register Vol. 62, No. 54, 13429, March 20, 1997.
  9. FDA, Part 11, Electronic Records; Electronic Signatures — Scope and Application, 2003.
  10. Qualification of Analytical Instruments for Use in the Pharmaceutical Industry: A Scientific Approach, AAPS PharmSciTech, 2004, 5(1) Article 22
  11. Pharmacopeial Forum , 31(5), 1453–1463 (Sept-Oct 2005).
  12. USP 32-NF 27, August 2009, Chapter 1058
  13. M.E. Swartz, Analytical Instrument Qualification, Pharmaceutical Regulatory Guidance Book (Advanstar Communications, July 2006), pp. 12–16.
  14. USP 32-NF 27, August 2009, Chapter 621
  15. Center for Drug Evaluation and Research (CDER), Reviewer Guidance: Validation of Chromatographic Methods, US Government Printing Office, 1994 - 615-023 - 1302/02757.
  16. W.B. Furman, J.G. Dorsey, and L.R. Snyder, Pharm. Technol. 22(6), 58–64 (1998).
  17. FDA ORA Laboratory Procedure, #ORA-LAB.5.4.5, USFDA ( 09/09/2005).
  18. Pharmacopeial Forum, 31(3), 825 (May-June 2005).
  19. Pharmacopeial Forum, 31(6) 1681 (Nov.-Dec. 2005).
  20. USP 32-NF 27, August 2009, Chapter 621.
  21. International Conference on Harmonization, Harmonized Tripartite Guideline, Stability Testing of New Drug Substances and Products, Q1A (R2), February 2003
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