Validation of Analytical Methods and Procedures
Frequent speaker and chair person at FDA, ISPE, PDA, USP. IVT,
and GAMP conferences and workshops
||Here Ludwig Huber
(right) in the Q&A Discussion Session on Laboratory
Compliance at a ISPE/FDA Beijing University Conference with
Nick Buhay, Acting Director in FDA/CDER's Division of
Manufacturing and Product Quality
For Dr. Huber's connection with the FDA,
Validation of Analytical Methods according to the New FDA
Understanding FDA's New Lifecycle
Approach for Method Validation
Recorded, available with all reference material at any time
Review of Analytical Methods as
Alternative to regular Revalidation
Understand how to remain in
compliance at much lower costs and at higher effectiveness
September 30, 2014
A large portion of this tutorial comes from the book: Validation
and qualification in Analytical Laboratories, published by Informa
in 2007. Copyright resides with the publisher. For contents and
Method validation is the process used to confirm that the
analytical procedure employed for a specific test is suitable for
its intended use. Results from method validation can be used to
judge the quality, reliability and consistency of analytical
results; it is an integral part of any good analytical practice.
Analytical methods need to be validated or revalidated
- before their introduction into routine use;
- whenever the conditions change for which the method has been
validated (e.g., an instrument with different characteristics or
samples with a different matrix); and
- whenever the method is changed and the change is outside the
original scope of the method.
Method validation has received considerable attention in the
literature and from industrial committees and regulatory agencies.
- The U.S. FDA CGMP (1) request in section 211.165 (e) methods
to be validated: The accuracy, sensitivity, specificity, and
reproducibility of test methods employed by the firm shall be
established and documented. Such validation and documentation
may be accomplished in accordance with Sec. 211.194(a). These
requirements include a statement of each method used in testing
the sample to meet proper standards of accuracy and reliability,
as applied to the tested product. The U.S. FDA has also proposed
an industry guidance for Analytical Procedures and Methods
- ISO/IEC 17025 includes a chapter on the validation of
methods (3) with a list of nine validation parameters. The ICH
(4) has developed a consensus text on the validation of
analytical procedures. The document includes definitions for
eight validation characteristics. ICH also developed a guidance
with detailed methodology (5).
- The U.S. EPA prepared a guidance for method’s development
and validation for the Resource Conservation and Recovery Act
(RCRA) (6). The AOAC, the EPA and other scientific organizations
provide methods that are validated through multi-laboratory
The USP has published specific guidelines for method validation
for compound evaluation (7). USP defines eight steps for validation:
- Limit of detection
- Limit of quantitation
- Linearity and range
The FDA has also published a guidance for the validation of
bioanalytical methods (8). The most comprehensive document is the
conference report of the 1990 Washington conference: Analytical
Methods Validation: Bioavailability, Bioequivalence and
Pharmacokinetic Studies, which was sponsored by, among others, the
American Association of Pharmaceutical Scientists (AAPS), the AOAC
and the U.S. FDA (70). The report presents guiding principles for
validating studies of both human and animal subjects. The report has
also been used as a basis for the FDA industry guidance document
Representatives of the pharmaceutical and chemical industry have
published papers on the validation of analytical methods. Hokanson
(9,10) applied the life cycle approach, developed for computerized
systems, to the validation and revalidation of methods. Green (11)
gave a practical guide for analytical method validation, with a
description of a set of minimum requirements for a method. Renger
and his colleagues (12) described the validation of a specific
analytical procedure for the analysis of theophylline in a tablet
using high-performance thin layer chromatography (HPTLC). The
validation procedure in this particular article is based on
requirements for EU multistate registration.
Wegscheider (13) has published procedures for method validation
with a special focus on calibration, recovery experiments, method
comparison and investigation of ruggedness. Seno et al. (14) have
described how analytical methods are validated in a Japanese QC
laboratory. The AOAC (15) has developed a Peer-Verified Methods
validation program with detailed guidelines on exactly which
parameters should be validated. Winslow and Meyer (16) recommend the
definition and application of a master plan for validating
analytical methods. J.Breaux and colleagues have published a study
on analytical methods development and validation (17). The key point
is to develop methods for easy validation and revalidation. O.
Krause published a guide for analytical method transfer,
comparability, maintenance and acceptance criteria for the testing
of biopharmaceuticals (18).
This primer gives a review and a strategy for the validation of
analytical methods for both methods developed in-house as well as
standard methods, and a recommendation on the documentation that
should be produced during, and on completion of, method validation.
It also describes what is important when transferring a method.
Strategy for the Validation of Methods
The validity of a specific method should be demonstrated in
laboratory experiments using samples or standards that are similar
to unknown samples analyzed routinely. The preparation and execution
should follow a validation protocol, preferably written in a
step-by-step instruction format. Possible steps for a complete
method validation are listed in Table 1. This proposed procedure
assumes that the instrument has been selected and the method has
been developed. It meets criteria such as ease of use; ability to be
automated and to be controlled by computer systems; costs per
analysis; sample throughput; turnaround time; and environmental,
health and safety requirements.
- Develop a validation protocol, an operating procedure or a
validation master plan for the validation
- For a specific validation project define owners and
- Develop a validation project plan
- Define the application, purpose and scope of the method
- Define the performance parameters and acceptance criteria
- Define validation experiments
- Verify relevant performance characteristics of equipment
- Qualify materials, e.g. standards and reagents for purity,
accurate amounts and sufficient stability
- Perform pre-validation experiments
- Adjust method parameters or/and acceptance criteria if
- Perform full internal (and external) validation experiments
- Develop SOPs for executing the method in the routine
- Define criteria for revalidation
- Define type and frequency of system suitability tests
and/or analytical quality control (AQC) checks for the routine
- Document validation experiments and results in the
Table 1. Steps in Method Validation
Successful acceptance of the validation parameters and
performance criteria, by all parties involved, requires the
cooperative efforts of several departments, including analytical
development, QC, regulatory affairs and the individuals requiring
the analytical data. The operating procedure or the Validation
Master Plan (VMP) should clearly define the roles and
responsibilities of each department involved in the validation of
The scope of the method and its validation criteria should be
defined early in the process. These include the following questions:
- What analytes should be detected?
- What are the expected concentration levels?
- What are the sample matrices?
- Are there interfering substances expected, and, if so,
should they be detected and quantified?
- Are there any specific legislative or regulatory
- Should information be qualitative or quantitative?
- What are the required detection and quantitation limits?
- What is the expected concentration range?
- What precision and accuracy is expected?
- How robust should the method be?
- Which type of equipment should be used? Is the method for
one specific instrument, or should it be used by all instruments
of the same type?
- Will the method be used in one specific laboratory or should
it be applicable in all laboratories at one side or around the
- What skills do the anticipated users of the method have?
The method’s performance characteristics should be based on the
intended use of the method. It is not always necessary to validate
all analytical parameters that are available for a specific
technique. For example, if the method is to be used for qualitative
trace level analysis, there is no need to test and validate the
method’s limit of quantitation, or the linearity, over the full
dynamic range of the equipment. Initial parameters should be chosen
according to the analyst’s experience and best judgment. Final
parameters should be agreed between the lab or analytical chemist
performing the validation and the lab or individual applying the
method and users of the data to be generated by the method. Table 2
gives examples of which parameters might be tested for a particular
The scope of the method should also include the different types
of equipment and the locations where the method will be run. For
example, if the method is to be run on a specific instrument in a
specific laboratory, there is no need to use instruments from other
vendors or to include other laboratories in the validation
experiments. In this way, the experiments can be limited to what is
|limit of detection
Table 2. Validation parameters for specific
The validation experiments should be carried out by an
experienced analyst to avoid errors due to inexperience. The analyst
should be very well versed in the technique and operation of the
instrument. Before an instrument is used to validate a method, its
performance specifications should be verified using generic chemical
standards. Satisfactory results for a method can be obtained only
with equipment that is performing well. Special attention should be
paid to those equipment characteristics that are critical for the
method. For example, if detection limit is critical for a specific
method, the instrument’s specification for baseline noise and, for
certain detectors, the response to specified compounds should be
Any chemicals used to determine critical validation parameters,
such as reagents and reference standards, should be
- available in sufficient quantities,
- accurately identified,
- sufficiently stable and
- checked for exact composition and purity.
Any other materials and consumables, for example, chromatographic
columns, should be new and be qualified to meet the column’s
performance criteria . This ensures that one set of consumables can
be used for most experiments and avoids unpleasant surprises during
Operators should be sufficiently familiar with the technique and
equipment. This will allow them to identify and diagnose unforeseen
problems more easily and to run the entire process more efficiently.
If there is little or no information on the method’s performance
characteristics, it is recommended to prove the suitability of the
method for its intended use in initial experiments. These studies
should include the approximate precision, working range and
detection limits. If the preliminary validation data appear to be
inappropriate, the method itself, the equipment, the analysis
technique or the acceptance limits should be changed. Method
development and validation are, therefore, an iterative process. For
example, in liquid chromatography, selectivity is achieved through
the selection of mobile phase composition. For quantitative
measurements, the resolution factor between two peaks should be 2.5
or higher. If this value is not achieved, the mobile phase
composition needs further optimization. The influence of operating
parameters on the performance of the method should be assessed at
this stage if this was not done during development and optimization
of the method.
There are no official guidelines on the correct sequence of
validation experiments, and the optimal sequence may depend on the
method itself. Based on the author’s experience, for a liquid
chromatographic method, the following sequence has proven to be
- Selectivity of standards (optimizing separation and
detection of standard mixtures if selectivity is insufficient)
- Linearity, limit of quantitation, limit of detection, range
- Repeatability (short-term precision) of retention times and
- Intermediate precision
- Selectivity with real samples
- Trueness/accuracy at different concentrations
- Ruggedness (interlaboratory studies)
The more time-consuming experiments, such as accuracy and
ruggedness, are included toward the end. Some of the parameters, as
listed under (2) to (6), can be measured in combined experiments.
For example, when the precision of peak areas is measured over the
full concentration range, the data can be used to validate the
During method validation, the parameters, acceptance limits and
frequency of ongoing system suitability tests or QC checks should be
defined. Criteria should be defined to indicate when the method and
system are beyond statistical control. The aim is to optimize these
experiments so that, with a minimum number of control analyses, the
method and the complete analytical system will provide long-term
results to meet the objectives defined in the scope of the method.
Once the method has been developed and validated, a validation
report should be prepared that includes the following:
- Objective and scope of the method (applicability, type).
- Summary of methodology.
- Type of compounds and matrix.
- All chemicals, reagents, reference standards, QC samples
with purity, grade, their source or detailed instructions on
- Procedures for quality checks of standards and chemicals
- Safety precautions.
- A plan and procedure for method implementation from the
method development lab to routine analysis.
- Method parameters.
- Critical parameters taken from robustness testing.
- Listing of equipment and its functional and performance
requirements, e.g., cell dimensions, baseline noise and column
temperature range. For complex equipment, a picture or schematic
diagram may be useful.
- Detailed conditions on how the experiments were conducted,
including sample preparation. The report must be detailed enough
to ensure that it can be reproduced by a competent technician
with comparable equipment.
- Statistical procedures and representative calculations.
- Procedures for QC in routine analyses, e.g., system
- Representative plots, e.g., chromatograms, spectra and
- Method acceptance limit performance data.
- The expected uncertainty of measurement results.
- Criteria for revalidation.
- The person(s) who developed and validated the method.
- References (if any).
- Summary and conclusions.
- Approval with names, titles, date and signature of those
responsible for the review and approval of the analytical test
<1226> for Verification of Compendial Methods
In Oct 2009 USP had
published a Stimuli article “Transfer of Analytical Procedures".
Based on comments received, USP now proposes a new general
information chapter <1224>. The procedure-transfer process focuses
on qualifying the receiving laboratory to perform an analytical
procedure that was developed and validated in another laboratory
within the same or in a different organization. One of the major
differences to the stimuli paper chapter is that <1224> suggests a
risk based approach for type and extent of transfer activities,
e.g., for comparative testing.
To learn everything about the new
"Transfer of Analytical Procedures According to the New USP <1224"
and receive SOPs, templates and examples for easy implementation.
Verification of Standard Methods
A laboratory applying a specific method should have documented
evidence that the method has been appropriately validated. This
holds for methods developed in-house, as well as for standard
methods, for example, those developed by organizations such as the
EPA, American Society for Testing and Materials (ASTM), ISO or the
A number of questions usually arises about the validation of
standard methods: Firstly, should these methods be revalidated in
the user’s laboratory and, if so, should method revalidation cover
all experiments, as performed during initial validation? Secondly,
which documentation should be available or developed in-house for
standard methods? Official guidelines and regulations are not
explicit about validating standard methods. Only CITAC/EURACHEM
guide (19) includes a short paragraph that reads as follows:
The validation of standard or collaboratively
tested methods should not be taken for granted, no matter how
impeccable the method’s pedigree - the laboratory should satisfy
itself that the degree of validation of a particular method is
adequate for the required purpose, and that the laboratory is itself
able to match any stated performance data.
There are two important requirements in this excerpt:
- The standard’s method validation data are adequate and
sufficient to meet the laboratory’s method requirements.
- The laboratory must be able to match the performance data as
described in the standard.
Further advice comes from FDA’s 21 CFR 194 section(a)2: “If the
method employed is in the current revision of the United States
Pharmacopeia, National Formulary, Association of Official Analytical
Chemists, or in other recognized standard references, or is detailed
in an approved new drug application and the referenced method is not
modified, a statement indicating the method and reference will
suffice. The suitability of all testing methods used shall be
verified under actual conditions of use.” The spirit of this text is
in line with the two requirements listed above.
This section elaborates on what these statements mean in
practice, and it gives a strategy for validating standard methods.
Like the validation of methods developed in-house, the evaluation
and verification of standard methods should also follow a documented
process that is usually the validation plan. Results should be
documented in the validation protocol. Both documents will be the
major source for the validation report.
Figure 1. Workflow for evaluation and
validation of standard methods
An example of a step-by-step plan for the evaluation and
validation of standard methods is shown as a flow diagram in Figure
1. As a first step, the scope of the method, as applied in the
user’s laboratory, should be defined. This should be done
independently of what is written in the standard method and should
include information such as
- the type of compounds to be analyzed,
- the type of information required (qualitative or
- detection and quantitation limits,
- precision and accuracy as specified by the client of the
analytical data and
- the type of equipment—its location and environmental
As a second step, the method’s performance requirements should be
defined in considerable detail, again irrespective of what has been
validated in the standard method. General guidelines on validation
criteria for different measurement objectives and procedures for
their evaluation are discussed later in this chapter.
The results of these steps lead to the experiments that are required
for adequate method validation and to the minimal acceptance
criteria necessary to prove that the method is suitable for its
intended use. Third, required experiments and expected results
should be compared with what is written in the standard method.
In particular, the standard method should be checked for the
- Have the reported validation results been obtained from the
complete procedure or from just a part of it? Sometimes the
validation data from the published method have been obtained
from the chromatographic analysis but have not included sample
preparation steps. The diagram in Figure 2 can be used for this
check. A complete validation of the analytical procedure should
include the entire process from sampling, sample preparation,
analysis, calibration and data evaluation to reporting.
- Has the same matrix been used?
- Did the validation experiments cover the complete
concentration range as intended for the method in the user’s
laboratory? If so, has the method’s performance been checked at
the different concentration ranges?
- Has the same equipment (brand, model) been used as available
in the user’s laboratory, and, if not, was the scope of standard
method regarding this item broad enough to include the user’s
equipment? This question is very important for a gradient HPLC
analysis, where the HPLC’s delay volume can significantly
influence the method’s selectivity.
- Have performance characteristics, e.g., the limit of
quantitation, been checked in compliance with the most recent
guidelines, as required for the user’s laboratory (e.g., the ICH
guideline (5) for pharmaceutical laboratories)? If not, does the
test procedure have equivalency to the guideline?
Figure 2. Steps for validating complete
analytical procedures. Standard methods should be checked if all
steps are included in the validation data.
If either the scope, the validation parameters or the validation
results do not meet the user’s requirements, adequate validation
experiments should be defined, developed and carried out. The extent
of these experiments depends on the overlap of the user requirements
with the scope and results, as described in the standard method. If
there is no overlap, a complete validation should be carried out. In
the case of a complete overlap, validation experiments may not be
If method validation experiments are unnecessary, the user should
prove the suitability of the method in his or her laboratory. This
evidence should confirm that the user’s equipment, the people, the
reagents and the environment are qualified to perform the analysis.
The experiments may be an extract of the full method validation and
should focus on the critical items of the method. Guidelines for
these tests should have been developed during method development. If
not, they should be developed and carried out at this stage. Typical
experiments may include precision of amounts and limits of
quantitation. The validation report should include a reference to
the standard method.
Validation of Non-routine Methods
Frequently, a specific method is used for only a few sample
analyses. The question should be raised as to whether this method
also needs to be validated using the same criteria as recommended
for routine analysis. In this case, the validation may take much
more time than the sample analysis and may be considered
inefficient, because the cost per sample will increase
significantly. The answer is quite simple: Any analysis is
worthwhile only if the data are sufficiently accurate; otherwise,
sample analysis is pointless. The suitability of an analysis method
for its intended use is a prerequisite to obtaining accurate data;
therefore, only validated methods should be used to acquire
meaningful data. However, depending on the situation, the validation
efforts can be reduced for non-routine methods. The CITAG/ EURACHEM
guide (19) includes a chapter on how to treat non-routine methods.
The recommendation is to reduce the validation cost by using generic
methods, for example, methods that are broadly applicable. A generic
method could, for example, be based on capillary gas chromatography
or on reversed phase gradient HPLC. With little or no modification,
the method can be applied to a large number of samples. The
performance parameters should have been validated on typical samples
characterized by sample matrix, compound types and concentration
If, for example, a new compound with a similar structure in the
same matrix is to be analyzed, the validation will require only a
few key experiments. The documentation of such generic methods
should be designed to easily accommodate small changes relating to
individual steps, such as sample preparation, sample analysis or
The method’s operating procedure should define the checks that
need to be carried out for a novel analyte in order to establish
that the analysis is valid. Detailed documentation of all
experimental parameters is important to ensure that the work can be
repeated in precisely the same manner at any later date.
Quality Control Plan and
Implementation for Routine
For any method that will be used for routine analysis, a QC plan
should be developed. This plan should ensure that the method,
together with the equipment, delivers consistently accurate results.
The plan may include recommendations for the following:
- Selection, handling and testing of QC standards
- Type and frequency of equipment checks and calibrations (for
example, should the wavelength accuracy and the baseline noise
of an HPLC UV detector be checked after each sample analysis, or
on a daily or weekly basis?)
- Type and frequency of system suitability testing (for
example, at which point during the sequence system should
suitability standards be analyzed?)
- Type and frequency of QC samples (for example, should a QC
sample be analyzed after 1, 5, 20 or 50 unknown samples, and
should there be single or duplicate QC sample analysis, or
should this be run at one or several concentrations?)
- Acceptance criteria for equipment checks, system suitability
tests and QC sample analysis
- Action plan in case criteria 2, 3 and/or 4 are not met.
In many cases, methods are developed and validated in service
laboratories that are specialized in this task. When the method is
transferred to the routine analytical laboratory, care should be
taken that the method and its critical parameters are well
understood by the workers in the departments who apply the method. A
detailed validation protocol, a documented procedure for method
implementation and good communication between the development and
operation departments are equally important. If the method is used
by a number of departments, it is recommended to verify method
validation parameters and to test the applicability and usability of
the method in a couple of these departments before it is distributed
to other departments. In this way, problems can be identified and
corrected before the method is distributed to a larger audience. If
the method is intended to be used by just one or two departments, an
analyst from the development department should assist the users of
the method during initial operation. Users of the method should be
encouraged to give constant feedback on the applicability and
usability of the method to the development department. The latter
should correct problems if any arise.
Transferring Validated Routine Methods
Validated routine methods are transferred between laboratories at
the same or different sites when contract laboratories offer
services for routine analysis in different areas or when products
are manufactured in different areas. When validated routine methods
are transferred between laboratories and sites, their validated
state should be maintained to ensure the same reliable results in
the receiving laboratory. This means the competence of the receiving
laboratory to use the method should be demonstrated through tests,
for example, repeat critical method validation experiments and run
samples in parallel in the transferring and receiving laboratories.
The transfer should be controlled by a procedure, The recommended
- Designate a project owner
- Develop a transfer plan
- Define transfer tests and acceptance
criteria (validation experiments, sample
analysis: sample type, #replicates)
- Describe rational for tests
- Train receiving lab operators in transferring lab on
equipment, method, critical parameters and troubleshooting
- Repeat 2 critical method validation tests in routine lab
- Analyze at least three samples in transferring and
- Document transfer results
Most likely some method parameters have to be changed or adjusted
during the life of the method if the method performance criteria
fall outside their acceptance criteria. The question is whether such
change requires revalidation. In order to clarify this question
upfront, operating ranges should be defined for each method, either
based on experience with similar methods or else investigated during
method development. These ranges should be verified during method
validation in robustness studies and should be part of the method
characteristics. Availability of such operating ranges makes it
easier to decide when a method should be revalidated. A revalidation
is necessary whenever a method is changed, and the new parameter
lies outside the operating range. If, for example, the operating
range of the column temperature has been specified to be between 30
and 40°C, the method should be revalidated if, for whatever reason,
the new operating parameter is 41°C.
Revalidation is also required if the scope of the method has been
changed or extended, for example, if the sample matrix changes or if
operating conditions change. Furthermore, revalidation is necessary
if the intention is to use instruments with different
characteristics, and these new characteristics have not been covered
by the initial validation. For example, an HPLC method may have been
developed and validated on a pump with a delay volume of 5 mL, but
the new pump has a delay volume of only 0.5 mL.
Figure 3. Flow diagram for revalidation
Part or full revalidation may also be considered if system
suitability tests, or the results of QC sample analysis, lie outside
preset acceptance criteria and where the source of the error cannot
be traced back to the instruments or any other cause.
Whenever there is a change that may require part or full
revalidation, the change should follow a documented change control
system. A flow diagram of such a process is documented in Figure 3.
The change should be defined, authorized for implementation and
documented. Possible changes may include
- new samples with new compounds or new matrices,
- new analysts with different skills,
- new instruments with different characteristics,
- new location with different environmental conditions,
- new chemicals and/or reference standards and
- modification of analytical parameters.
An evaluation should determine whether the change is within the
scope of the method. If so, no revalidation is required. If the
change lies outside the scope, the parameters for revalidation
should be defined. After the validation experiments, the system
suitability test parameters should be investigated and redefined, if
Parameters for Method Validation
The parameters for method validation have been defined in
different working groups of national and international committees
and are described in the literature. Unfortunately, some of the
definitions vary between the different organizations. An attempt at
harmonization was made for pharmaceutical applications through the
ICH (4,5), where representatives from the industry and regulatory
agencies from the United States, Europe and Japan defined
parameters, requirements and, to some extent, methodology for
analytical methods validation. The parameters, as defined by the ICH
and by other organizations and authors, are summarized in Table 3
and are described in brief in the following paragraphs.
- Specificity (1,2)
- Precision (1,2)
- repeatability (1)
- intermediate precision (1)
- reproducibility (3)
- Accuracy (1,2)
- Linearity (1,2)
- Range (1,2)
- Limit of detection (1,2)
- Limit of quantitation (1,2)
- Robustness (2,3)
- Ruggedness (2)
Table 3. Possible analytical parameters for
(1) Included in ICH publications, (2) Included in USP
(3) Terminology included in ICH publication but not part of
The terms selectivity and specificity are often used
interchangeably. A detailed discussion of this term, as defined by
different organizations, has been presented by Vessmann (20). He
particularly pointed out the difference between the definitions of
specificity given by IUPAC/WELAC and the ICH.
Although it is not consistent with the ICH, the term specific
generally refers to a method that produces a response for a single
analyte only, while the term selective refers to a method that
provides responses for a number of chemical entities that may or may
not be distinguished from each other. If the response is
distinguished from all other responses, the method is said to be
selective. Since there are very few methods that respond to only one
analyte, the term selectivity is usually more appropriate. The USP
monograph (7) defines the selectivity of an analytical method as its
ability to measure accurately an analyte in the presence of
interference, such as synthetic precursors, excipients, enantiomers
and known (or likely) degradation products that may be expected to
be present in the sample matrix. Selectivity in liquid
chromatography is obtained by choosing optimal columns and setting
chromatographic conditions, such as mobile phase composition, column
temperature and detector wavelength. Besides chromatographic
separation, the sample preparation step can also be optimized for
It is a difficult task in chromatography to ascertain whether the
peaks within a sample chromatogram are pure or consist of more than
one compound. Therefore, the analyst should know how many compounds
are in the sample or whether procedures for detecting impure peaks
should be used.
While in the past chromatographic parameters such as mobile phase
composition or the column were modified, now the application of
spectroscopic detectors coupled on-line to the chromatograph is
being used. UV/visible diode-array detectors and mass spectrometers
acquire spectra on-line throughout the entire chromatogram. The
spectra acquired during the elution of a peak are normalized and
overlaid for graphical presentation. If the normalized spectra are
different, the peak consists of at least two compounds.
The principles of diode-array detection in HPLC and their
application and limitations with regard to peak purity are described
in the literature (21). Examples of pure and impure HPLC peaks are
shown in Figure 4. While the chromatographic signal indicates no
impurities in either peak, the spectral evaluation identifies the
peak on the left as impure. The level of impurities that can be
detected with this method depends on the spectral difference, on the
detector’s performance and on the software algorithm. Under ideal
conditions, peak impurities of 0.05 to 0.1 percent can be detected.
Selectivity studies should also assess interferences that may be
caused by the matrix, e.g., urine, blood, soil, water or food.
Optimized sample preparation can eliminate most of the matrix
components. The absence of matrix interferences for a quantitative
method should be demonstrated by the analysis of at least five
independent sources of control matrix.
Figure 4. Examples of pure and impure HPLC
peaks. The chromatographic signal does not indicate any impurity in
either peak. Spectral evaluation, however, identifies the peak on
the left as impure.
Precision and Reproducibility
The precision of a method (Table 4) is the extent to which the
individual test results of multiple injections of a series of
standards agree. The measured standard deviation can be subdivided
into 3 categories: repeatability, intermediate precision and
reproducibility (4, 5). Repeatability is obtained when the analysis
is carried out in a laboratory by an operator using a piece of
equipment over a relatively short time span. At least 6
determinations of 3 different matrices at 2 or 3 different
concentrations should be performed, and the RSD calculated.
The ICH (4) requires precision from at least 6 replications to be
measured at 100 percent of the test target concentration or from at
least 9 replications covering the complete specified range. For
example, the results can be obtained at 3 concentrations with 3
injections at each concentration.
The acceptance criteria for precision depend very much on the
type of analysis. Pharmaceutical QC precision of greater than 1
percent RSD is easily achieved for compound analysis, but the
precision for biological samples is more like 15 percent at the
concentration limits and 10 percent at other concentration levels.
For environmental and food samples, precision is largely dependent
on the sample matrix, the concentration of the analyte, the
performance of the equipment and the analysis technique. It can vary
between 2 percent and more than 20 percent.
The AOAC manual for the Peer-Verified Methods program (15)
includes a table with estimated precision data as a function of
analyte concentration (Table 4).
Intermediate precision is a term that has been defined by ICH (4)
as the long-term variability of the measurement process. It is
determined by comparing the results of a method run within a single
laboratory over a number of weeks. A method’s intermediate precision
may reflect discrepancies in results obtained
- from different operators,
- from inconsistent working practice (thoroughness) of the
- from different instruments,
- with standards and reagents from different suppliers,
- with columns from different batches or
- a combination of these.
Table 4. Analyte concentration versus precision
The objective of intermediate precision validation is to verify
that in the same laboratory the method will provide the same results
once the development phase is over.
Reproducibility (Table 5), as defined by the ICH (4), represents
the precision obtained between different laboratories. The objective
is to verify that the method will provide the same results in
different laboratories. The reproducibility of an analytical method
is determined by analyzing aliquots from homogeneous lots in
different laboratories with different analysts, and by using
operational and environmental conditions that may differ from, but
are still within, the specified parameters of the method (interlaboratory
tests). Validation of reproducibility is important if the method is
to be used in different laboratories.
- Differences in room temperature and humidity
- Operators with different experience and thoroughness
- Equipment with different characteristics, e.g. delay volume
of an HPLC system
- Variations in material and instrument conditions, e.g. in
HPLC, mobile phases composition, pH, flow rate of mobile phase
- Variation in experimental details not specified by the
- Equipment and consumables of different ages
- Columns from different suppliers or different batches
- Solvents, reagents and other material with varying quality
Table 5. Typical variations affecting a
Table 6 summarizes factors that should be the same, or different,
for precision, intermediate precision and reproducibility.
accessories e.g. chrom. columns
Batches of material, e.g., reagents
conditions, e.g., temperature
Table 6. Variables for measurements of
precision, intermediate precision and reproducibility
Accuracy and Recovery
The accuracy of an analytical method is the extent to which test
results generated by the method and the true value agree. Accuracy
can also be described as the closeness of agreement between the
value that is adopted, either as a conventional, true or accepted
reference value, and the value found.
The true value for accuracy assessment can be obtained in several
ways. One alternative is to compare the results of the method with
results from an established reference method. This approach assumes
that the uncertainty of the reference method is known. Secondly,
accuracy can be assessed by analyzing a sample with known
concentrations (e.g., a control sample or certified reference
material) and comparing the measured value with the true value as
supplied with the material. If certified reference materials or
control samples are not available, a blank sample matrix of interest
can be spiked with a known concentration by weight or volume. After
extraction of the analyte from the matrix and injection into the
analytical instrument, its recovery can be determined by comparing
the response of the extract with the response of the reference
material dissolved in a pure solvent. Because this accuracy
assessment measures the effectiveness of sample preparation, care
should be taken to mimic the actual sample preparation as closely as
possible. If validated correctly, the recovery factor determined for
different concentrations can be used to correct the final results.
The concentration should cover the range of concern and should
include concentrations close to the quantitation limit, one in the
middle of the range and one at the high end of the calibration
curve. Another approach is to use the critical decision value as the
concentration point that must be the point of greatest accuracy.
Table 7. Analyte recovery at different
concentrations (Ref 9)
The expected recovery (Table 7) depends on the sample matrix, the
sample processing procedure and the analyte concentration. The AOAC
manual for the Peer-Verified Methods program (15) includes a table
with estimated recovery data as a function analyte concentration.
The ICH document on validation methodology recommends accuracy to
be assessed using a minimum of nine determinations over a minimum of
three concentration levels covering the specified range (e.g., three
concentrations/three replicates each). Accuracy should be reported
as percent recovery by the assay of known added amount of analyte in
the sample or as the difference between the mean and the accepted
true value, together with the confidence intervals.
Linearity and Calibration Curve
The linearity of an analytical method is its ability to elicit
test results that are directly proportional to the concentration of
analytes in samples within a given range or proportional by means of
well-defined mathematical transformations. Linearity may be
demonstrated directly on the test substance (by dilution of a
standard stock solution) and/or by using separate weighings of
synthetic mixtures of the test product components, using the
Linearity is determined by a series of 3 to 6 injections of 5 or
more standards whose concentrations span 80–120 percent of the
expected concentration range. The response should be directly
proportional to the concentrations of the analytes or proportional
by means of a well-defined mathematical calculation. A linear
regression equation applied to the results should have an intercept
not significantly different from 0. If a significant nonzero
intercept is obtained, it should be demonstrated that this has no
effect on the accuracy of the method.
Frequently, the linearity is evaluated graphically, in addition
to or as an alternative to mathematical evaluation. The evaluation
is made by visually inspecting a plot of signal height or peak area
as a function of analyte concentration. Because deviations from
linearity are sometimes difficult to detect, two additional
graphical procedures can be used. The first is to plot the
deviations from the regression line versus the concentration or
versus the logarithm of the concentration, if the concentration
range covers several decades. For linear ranges, the deviations
should be equally distributed between positive and negative values.
Another approach is to divide signal data by their respective
concentrations, yielding the relative responses. A graph is plotted
with the relative responses on the y-axis and the corresponding
concentrations on the x-axis, on a log scale. The obtained line
should be horizontal over the full linear range. At higher
concentrations, there will typically be a negative deviation from
linearity. Parallel horizontal lines are drawn on the graph
corresponding to, for example, 95 percent and 105 percent of the
horizontal line. The method is linear up to the point where the
plotted relative response line intersects the 95 percent line.
Figure 5 shows a comparison of the two graphical evaluations on a
sample of caffeine using HPLC.
The ICH recommends, for accuracy reporting, the linearity curve’s
correlation coefficient, y-intercept, slope of the regression line
and residual sum of squares. A plot of the data should be included
in the report. In addition, an analysis of the deviation of the
actual data points from the regression line may also be helpful for
evaluating linearity. Some analytical procedures, such as
immunoassays, do not demonstrate linearity after any transformation.
In this case, the analytical response should be described by an
appropriate function of the concentration (amount) of an analyte in
a sample. In order to establish linearity, a minimum of five
concentrations is recommended. Other approaches should be justified.
Figure 5. Graphical presentations of linearity
plot of a caffeine sample using HPLC.
Plotting the sensitivity (response/amount) gives clear indication
of the linear range. Plotting the amount on a logarithmic scale has
a significant advantage for wide linear ranges. Rc = Line of
The range of an analytical method is the interval between the
upper and lower levels (including these levels) that have been
demonstrated to be determined with precision, accuracy and linearity
using the method as written. The range is normally expressed in the
same units as the test results (e.g., percentage, parts per million)
obtained by the analytical method.
For assay tests, the ICH (5) requires the minimum specified range
to be 80 to 120 percent of the test concentration, and for the
determination of an impurity, the range to extend from the limit of
quantitation, or from 50 percent of the specification of each
impurity, whichever is greater, to 120 percent of the specification.
Figure 6. Definitions for linearity, range,
Limit of Detection
The limit of detection is the point at which a measured value is
larger than the uncertainty associated with it. It is the lowest
concentration of analyte in a sample that can be detected but not
necessarily quantified. The limit of detection is frequently
confused with the sensitivity of the method. The sensitivity of an
analytical method is the capability of the method to discriminate
small differences in concentration or mass of the test analyte. In
practical terms, sensitivity is the slope of the calibration curve
that is obtained by plotting the response against the analyte
concentration or mass.
In chromatography, the detection limit is the injected amount
that results in a peak with a height at least two or three times as
high as the baseline noise level. Besides this signal/noise method,
the ICH (4) describes three more methods:
- Visual inspection: The detection limit is determined by the
analysis of samples with known concentrations of analyte and by
establishing the minimum level at which the analyte can be
- Standard deviation of the response based on the standard
deviation of the blank: Measurement of the magnitude of
analytical background response is performed by analyzing an
appropriate number of blank samples and calculating the standard
deviation of these responses.
- Standard deviation of the response based on the slope of the
calibration curve: A specific calibration curve is studied using
samples containing an analyte in the range of the limit of
detection. The residual standard deviation of a regression line,
or the standard deviation of y-intercepts of regression lines,
may be used as the standard deviation.
Figure 7. Limit of detection and limit of
quantitation via signal to noise
Limit of Quantitation
The limit of quantitation is the minimum injected amount that
produces quantitative measurements in the target matrix with
acceptable precision in chromatography, typically requiring peak
heights 10 to 20 times higher than the baseline noise.
If the required precision of the method at the limit of
quantitation has been specified, the EURACHEM (22) (Figure 8)
approach can be used. A number of samples with decreasing amounts of
the analyte are injected six times. The calculated RSD percent of
the precision is plotted against the analyte amount. The amount that
corresponds to the previously defined required precision is equal to
the limit of quantitation. It is important to use not only pure
standards for this test but also spiked matrices that closely
represent the unknown samples.
For the limit of detection, the ICH (5) recommends, in addition
to the procedures as described above, the visual inspection and the
standard deviation of the response and the slope of the calibration
Figure 11. Limit of quantitation with the
EURACHEM (80) method.
Any results of limits of detection and quantitation measurements
must be verified by experimental tests with samples containing the
analytes at levels across the two regions. It is equally important
to assess other method validation parameters, such as precision,
reproducibility and accuracy, close to the limits of detection and
quantitation. Figure 6 illustrates the limit of quantitation (along
with the limit of detection, range and linearity). Figure 7
illustrates both the limit of detection and the limit of
Ruggedness is not addressed in the ICH documents (4,5) Its
definition has been replaced by reproducibility, which has the same
meaning as ruggedness, defined by the USP as the degree of
reproducibility of results obtained under a variety of conditions,
such as different laboratories, analysts, instruments, environmental
conditions, operators and materials. Ruggedness is a measure of
reproducibility of test results under normal, expected operational
conditions from laboratory to laboratory and from analyst to
analyst. Ruggedness is determined by the analysis of aliquots from
homogeneous lots in different laboratories.
Robustness tests examine the effect that operational parameters
have on the analysis results. For the determination of a method’s
robustness, a number of method parameters, for example, pH, flow
rate, column temperature, injection volume, detection wavelength or
mobile phase composition, are varied within a realistic range, and
the quantitative influence of the variables is determined. If the
influence of the parameter is within a previously specified
tolerance, the parameter is said to be within the method’s
Obtaining data on these effects helps to assess whether a method
needs to be revalidated when one or more parameters are changed, for
example, to compensate for column performance over time. In the ICH
document (5), it is recommended to consider the evaluation of a
method’s robustness during the development phase, and any results
that are critical for the method should be documented. This is not,
however, required as part of a registration.
Many solutes readily decompose prior to chromatographic
investigations, for example, during the preparation of the sample
solutions, extraction, cleanup, phase transfer or storage of
prepared vials (in refrigerators or in an automatic sampler). Under
these circumstances, method development should investigate the
stability of the analytes and standards.
The term system stability has been defined as the stability of
the samples being analyzed in a sample solution. It is a measure of
the bias in assay results generated during a preselected time
interval, for example, every hour up to 46 hours, using a single
solution (Figure 9). System stability should be determined by
replicate analysis of the sample solution. System stability is
considered appropriate when the RSD, calculated on the assay results
obtained at different time intervals, does not exceed more than 20
percent of the corresponding value of the system precision. If, on
plotting the assay results as a function of time, the value is
higher, the maximum duration of the usability of the sample solution
can be calculated.
Figure 9. Schematics of stability testing
The effect of long-term storage and freeze-thaw cycles can be
investigated by analyzing a spiked sample immediately after
preparation and on subsequent days of the anticipated storage
period. A minimum of two cycles at two concentrations should be
studied in duplicate. If the integrity of the drug is affected by
freezing and thawing, spiked samples should be stored in individual
containers, and appropriate caution should be employed for the study
Which Parameters Should Be Included in Method Validation?
For an efficient validation process, it is of utmost importance
to specify the right validation parameters and acceptance criteria.
The more parameters, the more time it will take to validate. The
more stringent the specifications or acceptance limits, the more
often the equipment has to be recalibrated, and probably also
requalified, to meet the higher specifications at any one time. It
is not always essential to validate every analytical performance
parameter, but it is necessary to define which ones are required.
This decision should be based on business, regulatory and/or
- For contract analyses: What does the client request?
- For regulatory submission: What do the regulations or
- For laboratory accreditation: What do the standard and
relevant guidelines recommend?
- interim precision
|Limit of detection
Limit of quantitation
Table 8. ICH Characteristics
* may be required, depending on the nature of the specific test
Limit of detection
Table 9. USP Characteristics
* may be required, depending on the nature of the specific test
The validation parameters depend on the analytical task and the
scope of the method. For example, both the USP (26) and the ICH (4)
contain chapters on validation procedures for different analytical
tasks, both of which are included to provide some ideas on what type
of validations are required for different tasks (see Tables 8 and
9). For example, according to the ICH, accuracy, any type of
precision and limits of detection and quantitation are not required
if the analytical task is identification. For assays in USP category
1, the major component or active ingredient to be measured is
normally present at high concentrations; therefore, validation of
limits of detection and quantitation is not necessary.
Because the type of analysis and the information that should be
obtained from a sample have so much influence on the validation, the
objective and scope of the method should always be defined as the
first step of any method validation.
- Develop a validation master plan or an operating procedure
for method validation.
- For individual method validation projects, develop a
validation project plan
- Define intended use of the method and performance criteria.
- Check all equipment and material for performance and
- Perform validation experiments.
- For standard methods: check scope of the standard with your
- For non-routine methods: develop and use generic methods
and customize them for specific non-routine tasks.
- Develop an operating procedure for method transfer between
- U.S. FDA, Title 21 of the U.S. Code of Federal Regulations:
21 CFR 211—Current good manufacturing practice for finished
- U.S. FDA - Guidance for Industry (draft) Analytical
Procedures and Methods Validation: Chemistry, Manufacturing, and
Controls and Documentation, 2000
- ISO/IEC 17025, General requirements for the competence of
testing and calibration laboratories, 2005
- International Conference on Harmonization (ICH) of Technical
Requirements for the Registration of Pharmaceuticals for Human
Use, Validation of analytical procedures: definitions and
terminology, Geneva (1996)
- International Conference on Harmonization (ICH) of
Technical Requirements for the Registration of Pharmaceuticals
for Human Use, Validation of analytical procedures: Methodology,
adopted in 1996, Geneva
- U.S. EPA, Guidance for methods development and methods
validation for the Resource Conservation and Recovery Act (RCRA)
Program, Washington, D.C. (1995).,
- General Chapter 1225, Validation of compendial methods,
United States Pharmacopeia 30, National Formulary 25, Rockville,
Md., USA, The United States Pharmacopeial Convention, Inc.,
- U.S. FDA - Guidance for Industry, Bioanalytical Method
- G. C. Hokanson, A life cycle approach to the validation of
analytical methods during pharmaceutical product development,
Part I: The initial validation process, Pharm. Tech., Sept.
1994, pp. 118–130.
- G. C. Hokanson, A life cycle approach to the validation of
analytical methods during pharmaceutical product development,
Part II: Changes and the need for additional validation,
Pharm.Tech., Oct. 1994, pp. 92–100.
- J. M. Green, A practical guide to analytical method
validation, Anal. Chem. News & Features, 1 May 1996, pp.
- B. Renger, H. Jehle, M. Fischer and W. Funk, Validation of
analytical procedures in pharmaceutical analytical chemistry:
HPTLC assay of theophylline in an effervescent tablet, J. Planar
Chrom. 8:269–278 (July/August 1995).
- Wegscheider, Validation of analytical methods, in:
Accreditation and quality assurance in analytical chemistry,
edited by H. Guenzler, Springer Verlag, Berlin (1996).
- S. Seno, S. Ohtake and H. Kohno, Analytical validation in
practice at a quality control laboratory in the Japanese
pharmaceutical industry, Accred. Qual. Assur. 2:140–145 (1997).
- 9. AOAC Peer-Verified Methods Program, Manual on policies
and procedures, Arlington, Va., USA (1998).
- 16. P. A. Winslow and R. F. Meyer, Defining a master plan
for the validation of analytical methods, J. Validation
Technology, pp. 361–367 (1997).
- J.Breaux, K. Jones, and P. Boulas, Pharmaceutical
Technology, Analytical Technology and Testing, 6-13, 2003
- S.O. Krause, A Guide for testing biopharmaceuticals, Part
II: acceptance criteria and analytical method maintenance,
Pharm. Tech. Europe, Vol 18(6), 29/38, 2006
- 29. CITAC/EURACHEM, Working Group, International guide to
quality in analytical chemistry: An aid to accreditation, 2002.
- J. Vessman, Selectivity or specificity? Validation of
analytical methods from the perspective of an analytical chemist
in the pharmaceutical industry, J. Pharm & Biomed Analysis
- L. Huber and S. George, Diode-array detection in
high-performance liquid chromatography, New York, Marcel Dekker,
ISBN 0-8247-4 (1993).
- EURACHEM – The Fitness for Purpose of Analytical Methods A
Laboratory Guide to Method Validation and Related Topics, 1998
- AOAC Guidelines
for Standard Method Performance Requirements (link)
Links to Other Websites
Not available yet
A good relationship with industry and FDA has always been my
highest priority. Most issues between industry and FDA can
be resolved by having a good understanding of each others
position. Personal visits to FDA's centers in Rockville,
panel discussions at public conferences, joint industry/FDA
workshops and having FDA and industry guest speakers in the
Labcompliance audio seminars helped a lot to get a real good
understanding on both positions, and to get an insight on
The examples below show interactions with the FDA.
||Ludwig Huber and
Paul Lepore, FDA's 'Father of GLP' during a GLP Workshop in
Paul Lepore told the audience how they should prepare for a
GLP inspection and what inspectors will ask.
Ludwig Huber explained how to implement computer validation
in GLP environment.
||Nick Buhay, Acting
Director in FDA/CDER's Division of Manufacturing and Product
Quality, and Ludwig Huber in the Q&A Discussion Session on
||Ludwig Huber was
on conference program's Part 11 panel discussion with FDA's
the Joseph Famulare, Acting Director, Office of Compliance,
(right) , QA manager at the FDA Labs in Puerto Rico, and
author of FDA's Excel Bulletins spoke at Ludwig Huber's
seminar as guest speaker.
2005 and in 2009
||Ludwig Huber has
been asked to review FDA's internal SOP and Lab Information
Bulletin on Spreadsheet Validation.
FDA acknowledged Ludwig Huber's contribution in the LIB
||Thomas S. Savage,
Senior Coordinator at FDA's Office of Regulatory Affairs,
told the audience that he took quite a lot of material from
Ludwig Huber's Labcompliance website. He also said that he
regularly visits this website when he wants to learn about
news on FDA inspections.
||Ludwig Huber in an
joint industry/FDA panel discussion at the IVT Part11
conference in Washington DC: From right to left: Martin
Browning, fEduQuest Inc, Paul Motise, US FDA, Kathryn
Davidson. Baxter Healthcare, INC, and Ludwig Huber fAgilent,
(middle) with FDA's Paul Motise (second from left) and the
speaker panel at an IVT conference in Washington (2002).
Other speakers, from right to left: Chris Reid, Rebecca
Fuller Heyde, and Jeff Beck
|Video Clips with
FDA Management are on the Lab Compliance Website
FDA management explained FDA's 21st Century Drug cGMP
initiative and the impact on Part 11
Mark B. McClellan, MD., PhD; Commissioner of Food and Drugs,
Janet Woodcock, MD. ; CDER Director David Horowitz, Director
of CDER's Office of Compliance, Joseph Famulare, Director,
Div. of Manufacturing & Product Quality Office of
(right) and John Murray, FDA, (left), speaking at the IVT
Computer System Validation Conference
FDA's national Part11 expert, at a panel discussion with
Ludwig Huber during an IVT conference 2005
Smith and Huber discussed and answered questions about
computer system validation and e-records.
(right) in a panel discussion with FDA inspectors and
Dr. Robert C. Horan, B Erik Henrikson,Joseph Famulare, and
Nicholas Buhay, Acting Director in FDA/CDERs Division of
Manufacturing and Product Quality.
Ludwig Huber (right) with Dr. Robert C. Horan, FDA,
Nicholas Buhay, and Joseph Famulare, in the joint
SINO-SFDA-US FDA cGMP /workshop
Ludwig Huber has been invited by FDA’s CDER to give a
seminar for FDA Quality Professionals
The idea was to share Ludwig’s expertise in the area of
laboratory controls, computer validation and integrity of
In 2007 Dr. Ludwig Huber has been invited by FDA's Eric
Hendrikson to give a post conference tutorial at the annual
GMP conference organized by FDA professionals.
Two FDA professionals attended Ludwig's tutorial.
Dr. Brenda Uratani, Assistant Country
Director US FDA China Offices, and Accociate Prof. Mr. Wang
Yamin, Center for Drug Evaluation, SFDA attended Dr. Huber's
GMP compliance workshop at the Bejing University.
Here Dr. Ludwig Huber (left) at lunch with Dr. Brenda
Uratani, , and with Accociate Prof. Mr. Wang Yamin,