What is Validation?
Validation is defined as establishing documented evidence
which provides a high degree of assurance that a specific process
will consistently produce a product
specifications and quality attributes.
Identification
meeting its pre-determined
Determination
Assay
of impurities
Analytical Method Validation 2
Why Validation?
• The objective of any analytical measurement is to obtain
consistent, reliable and accurate data. Validated analytical
methods play a major role in achieving this goal.
• Validation of analytical methods is also required by most
regulations.
Analytical Method Validation
3
Typical Analytical Procedures
Be Validated
To
• Four most common types of analytical procedures to
validated:
be
•
•
•
•
Identification tests
Quantitative tests for impurities content
Limit tests for the control of impurities
Quantitative tests of the active moiety
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Parameters
1. Linearity and Range
2. Specificity
3. Precision
4. Accuracy
5. Limit of Detection
6. Limit of Quantitation
7. Robustness
8. System Suitability
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-signifies that this characteristic is not normally evaluated
+ signifies that this characteristic is normally evaluated
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Characteristic Identification Impurities Testing Assay
Quantitative Limit
Accuracy _ + _ +
Precision
a. Repeatability _ + _ +
b. Intermediate precision _ + _ +
Specificity + + + +
LOD _ _ + _
LOQ _ + _ _
Linearity _ + _ +
Range _ + _ +
1. Linearity and Range
LINEARITY
Ability to obtain test results that are directly (or by a well-defined
mathematical transformation) proportional to the concentration
of analyte in samples within a given range. (y = mx + c)
•
•
The following parameters should be
correlation coefficient
y-intercept(c)
determined:
slope of the regression line(m)
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Determination of Linearity
• For establishment of linearity, minimum
recommended.
5 concentrations are
• Linearity results
methods.
should be established by appropriate statistical
= 0.9988
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R²
1
0.8
0.6
0.4 y = 0.0868x + 0.019
0.2
0
0 2 4 6 8 10 12
• Transformations are also acceptable and may include log, square
root, or reciprocal (other transformations are acceptable)
1.2
0.8
0 2 4 6-0.2
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y = 0.3671x - 0.4296
1.8
1.6
1.4
1 R² = 0.9515
0.6
0.4
0.2
0
Conc. Response
(µg/ml)
1 0.0625
2 0.25
3 0.562
4 0.922
5 1.562
0
1.2
0.4
• If linearity is not attainable, a nonlinear model may be used. The
goal is to have a model (whether linear or nonlinear) that
describes closely the concentration-response relationship.
• r2Acceptance criteria: Linear regression > 0.95
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1.4
1
0.8
0.6 y = 0.246x + 0.004
R² = 0.9982
0.2
0 2 4 6
Conc. √Response
(µg/ml)
1 0.25
2 0.5
3 0.75
4 0.96
5 1.25
RANGE
• The range of an analytical procedure is the interval between the
upper and lower levels of analyte(including these levels) that
have been demonstrated with a suitable level of precision,
accuracy, and linearity.
For assay tests, ICH requires the minimum specified range to be
80 to 120 percent of the test concentration.
•
Analytical Method Validation 12
•
•
Acceptable range having linearity, accuracy, precision.
For Drug Substance & Drug product Assay
– 80 to 120% of test Concentration
For Content Uniformity Assay
– 70 to 130% of test Concentration
For Dissolution Test Method
– +/- 20% over entire Specification Range
For Impurity Assays
•
•
•
– From Reporting Level to 120% of Impurity
Impurity Assays
– From Reporting Level to 120% of Assay Specification for
Impurity/Assay Methods
Specification for
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2. 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.
• Sample prepared in six replicates
as per the method.
on the same day and analysed
• The precision is reportedin terms of %RSD
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Less Variation
High Precision
More Variation
Low Precision
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Concentration Absorbance
10 µg/ml
Mean
0.22
0.35
0.39
0.53
0.36
Concentration Absorbance
10 µg/ml
Mean
0.28
0.31
0.29
0.30
0.29
• Precision maybe considered at three levels:
Precision
Intermediate
Precision
Repeatability Reproducibility
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1.
•
Repeatability
Repeatability expresses the precision under the same
operating conditions over a short interval of time.
Repeatability should be assessed using a minimum of
9 determinations covering the specified range.
•
2.
•
Intermediate Precision
Intermediate precision expresses variations within
laboratories, such as different days, different analysts,
different equipment, and so forth.
3.
•
Reproducibility
Reproducibility
laboratories. It
laboratory trial.
17025)
expresses the precision between
an inter-
USP, ISO
is assessed by means of
(Defined as ruggedness in
Analytical Method Validation 17
0.
• Following parameters should be reported:
a.
b.
Standard deviation
Relative standard deviation (coefficient of variation)
1
0
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12
20
1.2
8
8
0.8 8
0.6
12
4 12
0.2 20
20
4 8 12 16 20 24
Concentration Absorbance SD & % RSD
µg/ml
8
0.337 0.00041,
1.223%0.348
0.341
12
0.575 0.0106,
1.815%0.583
0.596
20
0.967
0.0091,
0.933%
0.985
0.978
3. Accuracy
Closeness of agreement between the conventional true• value /
an accepted reference value and the value found.
High Accuracy Less Accuracy
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Determination of Accuracy
1. Assay
Drug Substance Drug Product
a)application of the analyticala) application
procedure
Material.
of
to
analytical
reference procedure to synthetica
mixtures
quantities
to which
of the
known
drug
addedsubstance have been
b) to compare the results. b) to compare the results
c) accuracy may be concluded
once precision, linearity and
specificity have been
established.
c) accuracy may be concluded
once precision, linearity
and specificity have been
established.
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2. Impurities (Quantitation)
Assessed on samples (drug substance/drug product) spiked with
known amounts of impurities.
Accuracy should be assessed using a minimum of 9 determinations
over a minimum of 3 concentration levels covering the specified
range (e.g., 3 concentrations/3 replicates each of the total
analytical procedure).
Accuracy should be reported as percent recovery by the assay of
known added amount of analyte in the sample or as the difference
between the mean and the accepted true value.
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4. Limit of Detection &
Quantitation
Limit of Detection:
It is the lowest amount of analyte in a sample
detected but not necessarily quantitated.
Limit of
•
• which can be
•
•
Limit of Quantitation:
It is the lowest amount of analyte in a sample which can be
quantitatively determined with suitable precision and accuracy.
Analytical Method Validation 23
4. Limit of Detection & Limit of
Quantitation
LOQLOD
Lowest amount of analyte
in a sample that can be
Lowest amount of analyte in a
sample that can be detected
but not necessarily quantified with suitable
quantitated. accuracy and precision.
Estimated by Signal to
Noise Ratio of 10:1.
Estimated by Signal to Noise
Ratio of 3:1.
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Signal to noise ratio 10:1 Signal to noise ratio 2:1 or 3:1
Determination of LOD & LOQ
Limit of Detection
Method
Limit of Quantitation
Method
Based on visual evaluation Based on visual evaluation
Based on standard deviation
of response and slope
Based on standard deviation
of response and slope
LOD = 3.3 σ / Slope LOD = 10 σ / Slope
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6. Specificity
• The ability to detect the analyte of interest in the presence of
interfering substances (typically impurities, degradants, ).
1. Identification
• Suitable identification tests should be able to discriminate
between compounds of closely related structures which are
likely to be present.
• The discrimination of a procedure may be confirmed by
obtaining positive results from samples containing the analyte,
coupled with negative results from samples which do not
contain the analyte.
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.
•
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2. Assay and impurity test:
a.
•
Impurities are available
For the assay , this
discrimination of the
and/or excipients.
should involve demonstration of the
analyte in the presence of impurities
• This can be done by spiking pure substances with
appropriate levels of impurities and/or excipients and
demonstrating that the assay result is unaffected by the
presence of these materials.
• For the impurity test, the discrimination may be established
by spiking drug substance or drug product with appropriate
levels of impurities and demonstrating
these impurities individually and/or from
in the sample matrix.
the separation of
other components
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7. 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.
•
• If measurements are susceptible to variations in analytical
conditions, the analytical conditions should
should
be suitably
controlled or a precautionary statement
the procedure, such as:
Use solution within 24 hours
be included in
•
• Maintain temperature below 25 degrees
Analytical Method Validation 29
• In the case of liquid chromatography, examples of typical
variations are:
influence of variations of pH in a mobile phase
influence of variations in mobile phase composition
different columns (different lots and/or suppliers)
temperature
flow rate
• In the case of gas-chromatography, examples of typical variations
are:
different columns (different lots and/or suppliers)
temperature
flow rate
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8. System Suitability
• 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.
• Determination: repeatability, tailing factor (T), capacity factor
(k’), resolution (R), and theoretical Plates (N)
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System Suitability Requirements
Analytical Method Validation 32
Parameters Recommendations
K’ In general k’ ≥ 2.0
R >2, between the peak of interest and
R the closest potential interferent (degradant,
internal STD, impurity, excipient, etc…)
T T ≤ 2
N In general N > 2000
Repeatability RSD ≤ 2.0% (n ≥ 5)
Conclusion
When the method is properly validated consistent, reliable•
and accurate results are obtained. Also, Validation of
analytical methods is also required by regulations. Hence it
is very important to validate any analytical method that has
been developed.
Analytical Method Validation 33
correlation coefficient : statistical relationship between two variables
y-intercept is the point where a line crosses the y-axis.
The slope of regression line (b) represents the rate of change in y as x changes. Because y is dependent on x, the slope describes the predicted values of y given x.
In reproducibility : the same analysis is performed in different laboratory or place by same methods.