describes the analytical method validation and its parameters

1. Analytical Method Validation
P. Raja Abhilash, M.pharm
(Ph.D.)
Assistant professor
S.R. college of pharmacy.

2. Introduction
 Method validation is the process of documenting /
proving that an analytical method provides analytical
data acceptable for the intended use.
 A pharmaceutical drug product must meet all its
specifications through out its entire shelf-life.
 The performance of product characteristics through
out the shelf-life must be tested by analytical method
for the product’s chemical, physiochemical,
microbiological and biological characteristics.
 The method of analysis used must be validated. This
is required to ensure the product’s safety and efficacy
through out all phases of its shelf-life.

3. Objective
 The main objective of analytical validation
is to ensure that a selected analytical
procedure will give reproducible and
reliable results that are adequate for the
intended purpose.
 This is applicable to all the procedure either
pharmacopoeial or non pharmacopoeial.

4. Steps of method development &
validation
 The steps of method development & validation
depends upon the type of method being developed,
however the following steps are common to most
types of projects:
 Method development plan definition
 Back ground information gathering
 Laboratory method development
 Generation of test procedure
 Methods validation protocol definition
 Laboratory method validation
 Validated test method generation
 Validation report

5. Types of Analytical Procedures
to be Validated
 The required validation parameters also termed
“analytical performance characteristics”, depends
upon the type of analytical method.
 Pharmaceutical analytical methods are
characterized into 5 general types
 Identification tests
 Potency assays
 Limit tests for the control of impurities
 Impurity tests- quantitative
 Specific tests.

6. Prerequisites for analytical method validation
Man
Man Machine
Machine Methods
Methods
qualified
qualified calibrated
calibrated characterised
characterised
robust
robust documented
documented
skilled
skilled qualified
qualified suitable
suitable
Quality
Quality
Reference
Reference Vibrations
Vibrations Time
Time
analy
analy
standards
standards Analysts´
Irradi-
Irradi- Analysts´
support
meth
meth
Tempe-
Tempe- ations
ations support
Quality rature
Quality rature Humidity
Humidity Supplies
Supplies
terial
terial Milieu Management
Milieu Management
Six “M”s



7. Validation parameter ICH USP
Accuracy O O
Repeatibility O O
Precision Interm. precision O -
Reproducibility O -
Specificity or Selectivity O O
Detection limit O O
Quantitation limit O O
Linearity O O
Range O O
Robustness O O
Ruggedness - O

8. Table

9. Specificity / selectivity
Is this analytical Suppose we alter
procedure specific test conditions
for the drug under test? slightly?

10. Specificity (1)
 Specificity is the ability to assess
unequivocally the analyte in the presence of
components which may be expected to be
present.
 Typically these might include impurities,
degradants, matrix, etc.
 Lack of specificity of an individual
analytical procedure may be compensated
by other supporting analytical procedure(s).

11. Specificity (2)
 An investigation of specificity should be conducted
during the validation of identification tests, the
determination of impurities and the assay.
 The procedures used to demonstrate specificity will
depend on the intended objective of the analytical
procedure.
 It is not always possible to demonstrate that an
analytical procedure is specific for a particular
analyte (complete discrimination).
 In this case a combination of two or more analytical
procedures is recommended to achieve the necessary
level of discrimination.

12. Identification
 Suitable identification tests should be able to
discriminate between compounds of closely related
structures which are likely to be present.
 The discrimination of a procedure may be confirmed by
obtaining positive results (perhaps by comparison with
a known reference material) from samples containing
the analyte, coupled with negative results from samples
which do not contain the analyte.
 In addition, the identification test may be applied to
materials structurally similar to or closely related to the
analyte to confirm that a positive response is not
obtained.

13. Assay and Impurity Test(s)
 For chromatographic procedures, representative
chromatograms should be used to demonstrate specificity
and individual components should be appropriately
labelled.
 Critical separations in chromatography should be
investigated at an appropriate level.
 For critical separations, specificity can be demonstrated by the
resolution of the two components which elute closest to each other.
 In cases where a non-specific assay is used, other
supporting analytical procedures should be used to
demonstrate overall specificity.
 For example, where a titration is adopted to assay the drug
substance for release, the combination of the assay and a suitable
test for impurities can be used.

14. Impurities are available
 For the assay , this should involve demonstration
of the discrimination of the analyte in the presence
of impurities and/or excipients;
 practically, this can be done by spiking pure
substances (drug substance or drug product) with
appropriate levels of impurities and/or excipients
and demonstrating that the assay result is
unaffected by the presence of these materials

15. Impurities are not available
 specificity may be demonstrated by comparing the
test results of samples containing impurities or
degradation products to a second well-
characterized procedure e.g.: spharmacopoeial
method or other validated analytical procedure
(independent procedure).
 As appropriate, this should include samples stored
under relevant stress conditions:
 light, heat, humidity, acid/base hydrolysis and
oxidation.

16. Linearity and Range
‘Know that it’s a straight line’
vs
‘For what concentrations is it a
straight line’

17. Linearity and Range
Concentration
mg/mL
Response
 ‘Know that it’s a straight line’ versus ‘For what
concentrations is it a straight line’
 Is it a straight line between 0.4 & 0.6 mg/mL?
 Over what range is it a straight line?
 Answer: approx 0.25-0.70 mg/mL

18. LINEARITY (1)
 A linear relationship should be evaluated
across the range of the analytical
procedure.
 It may be demonstrated directly on the
drug substance by:
 dilution of a standard stock solution and/or
 separate weighing of synthetic mixtures of the
drug product components using the proposed
procedure.

19. LINEARITY (2)
 Linearity should be evaluated by visual inspection of a plot of
signals as a function of analyte concentration or content.
 If there is a linear relationship, test results should be
evaluated by appropriate statistical methods, for example, by
calculation of a regression line by the method of least squares.
 In some cases, to obtain linearity between assays and sample
concentrations, the test data may need to be subjected to a
mathematical transformation prior to the regression analysis.
Data from the regression line itself may be helpful to provide
mathematical estimates of the degree of linearity.
 For the establishment of linearity, a minimum of 5
concentrations is recommended.

20. Example
 Seven solutions containing different
concentrations (0.280 – 0.520) mg/ml of
ketotifen fumarate in tablets were assayed
using HPLC
 The results were evaluated statistically and
the results shown on the following slide

21. Example (continued)
Concentration of ketotifen fumarate Area detected Acceptance
mg/ml % criteria
0.280 70 1473566
0.320 80 1677013
0.360 90 1904848
0.400 100 2091215
0.440 110 2293647
0.480 120 2518976
0.520 130 2670144
Regression: y = ax + b 0.998 – 1.002
a = 5055766.964
b = 67608.786
r2 = 0.9984

22. RANGE
 The specified range is normally derived from
linearity studies and depends on the intended
application of the procedure.
 It is established by confirming that the analytical
procedure provides an acceptable degree of
linearity, accuracy and precision when applied to
samples containing amounts of analyte within or
at the extremes of the specified range of the
analytical procedure.

23. Minimum Specified Ranges
 for the assay of a drug substance or a finished
(drug) product: normally from 80 - 120 % of the test
concentration
 for content uniformity, covering a minimum of
70 - 130 % of the test concentration
 for dissolution testing: +/-20 % over the
specified range;
 e.g., if the specifications for a controlled released
product cover a region from 20%, after 1 hour, up to
90%, after 24 hours, the validated range would be 0-
110% of the label claim

24. Accuracy vs precision
What you
would
like
to see!

25. Accuracy vs precision
 Poor accuracy
 Good precision

26. Accuracy vs precision
 Poor precision
 Good accuracy

27. Accuracy vs precision
What would you
call this?
 Totally hopeless!
 Poor precision
 Poor accuracy

28. So what definitions do these
concepts lead us to in the
context of assay validation?

29. ACCURACY (1)
 The accuracy of an analytical procedure
expresses the closeness of agreement
between the value which is accepted either
as a conventional true value or an accepted
reference value and the value found. This is
sometimes termed trueness.

30. ACCURACY (2)
Assay of Drug Product:
a) Application of the analytical procedure to synthetic
mixtures of the drug product components to which known
quantities of the drug substance to be analysed have been
added (standard addition method);
b) In cases where it is impossible to obtain samples of all drug
product components, it may be acceptable either to:
 add known quantities of the analyte to the drug product or
 to compare the results obtained from a second, well characterized
procedure, the accuracy of which is stated and/or defined
(independent procedure)
c) Accuracy may be inferred once precision, linearity and
specificity have been established.

31. ACCURACY (3)
Impurities (Quantitation):
 Accuracy should be assessed on samples (drug
substance/drug product) spiked with known amounts of
impurities.
 In cases where it is impossible to obtain samples of certain
impurities and/or degradation products, it is considered
acceptable to compare results obtained by an independent
procedure. The response factor of the drug substance can
be used.
 It should be clear how the individual or total impurities
are to be determined e.g., weight/weight or area percent, in
all cases with respect to the major analyte.

32. Recommended Data
 Accuracy should be assessed using a min. of
9 determinations over a min. of 3
concentration levels covering the specified
range (e.g. 3 concentrations/3 replicates each of
the total analytical procedure).
 Accuracy should be reported as:
 % 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

33. Example:
 Nine solutions containing different
concentrations of ketotifen fumarate
reference standard added to ketotifen tablet
were assayed

34. Example (continued):
Conc. of ketotifen fumarate Area Recovery Acceptance
mg/ml % detected (%) Criteria
0.280 70 1473566 99.32
0.320 80 1677013 99.48
0.360 90 1904848 100.94
0.380 95 1905862 100.51
0.400 100 2091215 100.06
0.420 105 2180374 100.03
0.440 110 2293647 100.07
0.480 120 2518976 101.01
0.520 130 2670144 98.99
Mean (recovery) : 100.04 98.0–102.0 %
Standard deviation : 0.699
Relative standard deviation (RSD) : 0.699 % <2%

35. PRECISION
 The precision of an analytical procedure expresses the
closeness of agreement (degree of scatter) between a series
of measurements obtained from multiple sampling of the
same homogeneous sample under the prescribed
conditions.
 Precision may be considered at three levels:
 repeatability,
 intermediate precision and
 reproducibility.
 Precision should be investigated using homogeneous,
authentic samples. However, if it is not possible to obtain a
homogeneous sample it may be investigated using
artificially prepared samples or a sample solution.
 The precision of an analytical procedure is usually
expressed as the variance, standard deviation or
coefficient of variation of a series of measurements.

36. Repeatability (1)
 Repeatability expresses the precision under
the same operating conditions over a short
interval of time.
 Repeatability is also termed intra-assay
precision.

37. Repeatability (2)
 Repeatability should be assessed using:
a) a minimum of 9 determinations
covering the specified range for the
procedure (e.g. 3 concentrations/3
replicates each) or
b) a minimum of 6 determinations at
100% of the test concentration.

38. Intermediate precision
 Intermediate precision expresses within-laboratories
variations: different days, different analysts,
different equipment, etc.
 The extent to which intermediate precision should be
established depends on the circumstances under which the
procedure is intended to be used.
 The applicant should establish the effects of random events
on the precision of the analytical procedure.
 Typical variations to be studied include days, analysts,
equipment, etc. It is not considered necessary to study
these effects individually. The use of an experimental
design (matrix) is encouraged.

39. Reproducibility
 Reproducibility is assessed by means of an
inter-laboratory trial.
 Reproducibility should be considered in
case of the standardization of an analytical
procedure, for instance, for inclusion of
procedures in pharmacopoeias.
 These data are not part of the marketing
authorization dossier.

40. Recommended Data
 The standard deviation, relative
standard deviation (coefficient of
variation) and confidence interval should be
reported for each type of precision
investigated.

41. Example
 The active ingredient, ketotifen fumarate,
in tablets was assayed seven times using
HPLC and the reference standard

42. Example (continued)
Sample no. Concentration (mg/ml) Area detected
1 0.4 1902803
2 0.4 1928083
3 0.4 1911457
4 0.4 1915897
5 0.4 1913312
6 0.4 1897702
7 0.4 1907019
Mean : 1910896
Standard deviation : 9841.78
Relative standard deviation (RSD) : 0.515 %
Acceptance criteria:
Relative standard deviation (RSD): not more than 2 %

43. Detection limit vs
Quantitation limit
‘Know that it’s there’
vs
‘Know how much is there’

44. Detection limit
(means)
Is any of it present?
Is it there?

45. Quantitation limit
How much of it is present???
How much of it is there?

46. DETECTION LIMIT
 The detection limit of an individual
analytical procedure is the lowest amount of
analyte in a sample which can be detected
but not necessarily quantitated as an exact
value
 Several approaches for determining the
detection limit are possible, depending on
whether the procedure is a non-
instrumental or instrumental.

47. Based on Visual Evaluation
 Visual evaluation may be used for non-
instrumental methods but may also be used
with instrumental methods.
 The detection limit is determined by the
analysis of samples with known
concentrations of analyte and by
establishing the minimum level at which the
analyte can be reliably detected .

48. Based on Signal-to-Noise
 This approach can only be applied to analytical
procedures which exhibit baseline noise.
 Determination of the signal-to-noise ratio is
performed by comparing measured signals from
samples with known low concentrations of analyte
with those of blank samples and establishing the
minimum concentration at which the analyte can
be reliably detected.
 A signal-to-noise ratio between 3:1 or 2:1 is
generally considered acceptable for estimating the
detection limit.

49. Based on the Standard Deviation of
the Response and the Slope
The detection limit (DL) may be expressed
as:
DL = 3.3 σ /S
where σ = the standard deviation of the
response
S = the slope of the calibration curve
The slope S may be estimated from the
calibration curve of the analyte.

50. Estimate of σ
 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
 Based on the Calibration Curve
 A specific calibration curve should be studied using
samples containing an analyte in the range of DL.
 The residual standard deviation of a regression line or
the standard deviation of y-intercepts of regression lines
may be used as the standard deviation.

51. Recommended Data
 The detection limit and the method used for
determining the detection limit should be
presented.
 If DL is determined based on visual evaluation or
based on signal to noise ratio, the presentation of
the relevant chromatograms is considered
acceptable for justification.
 In cases where an estimated value for the detection
limit is obtained by calculation or extrapolation,
this estimate may subsequently be validated by the
independent analysis of a suitable number of
samples known to be near or prepared at the
detection limit

52. QUANTITATION LIMIT
 The quantitation limit of an individual analytical
procedure is the lowest amount of analyte in a
sample which can be quantitatively determined
with suitable precision and accuracy.
 The quantitation limit is a parameter of
quantitative assays for low levels of compounds in
sample matrices, and is used particularly for the
determination of impurities and/or degradation
products.
 Several approaches for determining the
quantitation limit are possible, depending on
whether the procedure is a non-instrumental or
instrumental.

53. Based on Visual Evaluation
 Visual evaluation may be used for non-
instrumental methods but may also be used
with instrumental methods.
 The quantitation limit is generally
determined by the analysis of samples with
known concentrations of analyte and by
establishing the minimum level at which the
analyte can be quantified with acceptable
accuracy and precision.

54. Based on
Signal-to-Noise Approach
 This approach can only be applied to analytical
procedures that exhibit baseline noise.
 Determination of the signal-to-noise ratio is
performed by comparing measured signals from
samples with known low concentrations of analyte
with those of blank samples and by establishing
the minimum concentration at which the analyte
can be reliably quantified.
 A typical signal-to-noise ratio is 10:1.

55. Based on the Standard Deviation of
the Response and the Slope
 The quantitation limit (QL) may be
expressed as:
QL = 10 σ /S
where σ = the standard deviation of the
response
S = the slope of the calibration curve
 The slope S may be estimated from the
calibration curve of the analyte.

56. Estimate of σ
 Based on Standard Deviation of the Blank
 Measurement of the magnitude of analytical
background response is performed by analyzing an
appropriate number of blank samples and calculating
the standard deviation of these responses.
 Based on the Calibration Curve
 A specific calibration curve should be studied using
samples, containing an analyte in the range of QL.
 The residual standard deviation of a regression line or
the standard deviation of y-intercepts of regression lines
may be used as the standard deviation.

57. Recommended Data
 The quantitation limit and the method used
for determining the quantitation limit
should be presented.
 The limit should be subsequently validated
by the analysis of a suitable number of
samples known to be near or prepared at
the quantitation limit.

58. Robustness
Small changes do not affect
the parameters of the
assay

59. ROBUSTNESS
 The robustness of an analytical procedure is a measure of
its capacity to remain unaffected by small, but deliberate
variations in method parameters and provides an
indication of its reliability during normal usage.
 The evaluation of robustness should be considered during
the development phase and depends on the type of
procedure under study.
 If measurements are susceptible to variations in analytical
conditions, the analytical conditions should be suitably
controlled or a precautionary statement should be included
in the procedure.
 One consequence of the evaluation of robustness should be
that a series of system suitability parameters (e.g.,
resolution test) is established to ensure that the validity of
the analytical procedure is maintained whenever used.

60. Typical Variations
 stability of analytical solutions,
 extraction time
Liquid chromatography:
 influence of variations of pH in a mobile phase,
 influence of variations in mobile phase composition,
 different columns (different lots and/or suppliers),
 temperature,
 flow rate.
Gas chromatography:
 different columns (different lots and/or suppliers),
 temperature,
 flow rate.

61. SYSTEM SUITABILITY TESTING
 System suitability testing is an integral part of
many analytical procedures.
 The tests are based on the concept that the
equipment, electronics, analytical operations and
samples to be analyzed constitute an integral
system that can be evaluated as such.
 System suitability test parameters to be
established for a particular procedure depend on
the type of procedure being validated. They are
especially important in the case of
chromatographic methods.

62. System Suitability in
Chromatography
 To verify that the resolution and reproducibility of the
chromatographic system are adequate for the analysis to
be done
 The resolution, R, is specified to ensure that closely eluting
compounds are resolved from each other
 Replicate injections of a standard preparation are
compared to ascertain whether requirements for precision
are met
 The tailing factor, T, has to meet a certain requirement,
because as peak asymmetry increases, integration, and
hence precision, becomes less reliable

63. Evaluating validation data for an
HPLC procedure
 Here are some suggestions………
 But please note!
- The slides that follow do not represent requirements; they
are suggestions.
- There is more than one way to do this!
- Use judgement.
 If you are unsure, consult with experienced analysts!!

64. Specificity
(selectivity)
Use some or all of these procedures:
- Add a synthetic mixture of excipients to the sample &
check whether the assay result for the drug is the same
- Add some known impurities to the test sample & check
whether they are resolved (separated from) the drug
- Forcably degrade the active & test whether degradants are
separated from the intact drug
- Assess peak purity by diode array

65. Linearity
- Minimum of 5 concentrations
- r2 >0.99 if possible
- Intercept NMT ±2% of response of 100% the
working concentration
- Confirm accuracy & precision over the
required range

66. Accuracy
- Generally within +2%
- Recoveries after spiking, or
- Comparison with ‘well-established’ methods & by
inference
- Arguably can be up to +10% for
related substances
- What is known about the reference
standard?

67. Precision
- repeatability
 System repeatability %CV (of detector
response) <2.0% for 6
injections
 Method repeatability %CV <2.0%
and accuracy
should be within 2%

68. Precision - intermediate
[= ruggedness USP]
- Use same complete analytical procedure for
comparisons
- Compare results across different analysts, days,
equipment
- Means preferably within 2%
- Compare %CV with that for method repeatability

69. Precision
- reproducibility
- This is not normally a component of a dossier for
an application to register, but if you do have to
evaluate these data then……
- For interlab comparisons
- Means should preferably be within 2%
- Compare the %CV with that for method
repeatability
- Can use an F test, normally with 95%
confidence

70. Limit of detection
- Use some or all of these procedures:
- - Visual evaluation: A clear & symmetrical peak is
visible
- Signal to noise ratio of 3:1 or 2:1
- Based on statistical information:
- Detection limit =
- 3.3 x (std dev at that concentration)
- slope

71. Limit of quantitation
- Use some or all of these procedures:
- ‘Visual’ evaluation: A clear & symmetrical peak is
visible
- Signal to noise ratio of 10:1
- Based on statistical information:
- Detection limit =
- 10 x (std dev at that concentration)
- slope

72. Robustness
- Use some or all of these procedures:
- Compare results after altering HPLC parameters,
eg mobile phase composition, buffer composition,
pH, column type, flow rate:
- NMT ± 2% difference in assay
- Compare results after storage of test solution, eg
for 24h at say 250C
- NMT ± 2% difference in assay

73. Evaluation of analytical validation data
The objective of the analytical procedure
The analytical technique
Item Data provided by applicant Acceptable or not? (add comments if
(very briefly) necessary, & reasons if unacceptable)
Is a chromatogram, spectrum or
similar provided?
S
Linearity
Range
Accuracy
Precision: Repeatability
Precision: Intermediate
Precision: Reproducibility
Detection limit
Quantitation limit
Robustness
System suitability (if necessary)
Are the data concerning analytical validation satisfactory? YES/NO
DataIfon therecommended questions to the applicant appear in
NO, reference standard
……………………………………………………………………
Other evaluator comments:
(eg page number below, or draft letter to the company on page……)

74. Thank you