Validation of Pharmaceuticals

1. VALIDATION
Presented by – Arif Nadaf
M. Pharm (Pharmaceutics)
Jamia Hamdard University, New Delhi

2. • Validation means to Confirm,
Establish, Authenticate or Define the
Results Or Outcomes that are
obtained from the work which is done.
WHAT IS VALIDATION ?

3. • Action of proving, in accordance with the GMP , that
any Procedure, Process, Equipment, Material, Activity
Or System actually leads to the expected results .
VALIDATION AS PER WHO / PICS
VALIDATION AS PER 21 CFR
Validation means confirmation by examination and
provision by objective evidence that the particular
requirements for a specific intended use can be consistently
fulfilled .

4. • Process validation
• Equipment validation
• Facility validation
• HVAC system validation ( Heating, ventilation and
air conditioning)
• Cleaning validation
• Analytical method validation
• Computer system validation
TYPES OF VALIDATION

5. • Process validation is defined as the collection and
evaluation of data, from the process design stage
through commercial production, which establishes
scientific evidence that a process is capable of
consistently delivering quality product.
PROCESS VALIDATION :

6. WHY PROCESS VALIDATION IS REQUIRED

7. 1. Process design : The goal of this stage is to design a process suitable for
routine commercial manufacturing that can consistently deliver a product that meets
its quality attributes.
2. Process qualification : The process design is evaluated to determine if it is
capable of reproducible commercial manufacture:
The stage has two elements:
-design of facility and qualification of equipment and utilities.
-Process Performance Qualification (PPQ)
3. Continued process verification: The goal of this stage is continual
assurance that the process remain in state of control (validated state) during
commercial manufacturing. Evaluating the performance of process identifies
problems and determines weather actions must be taken to correct, anticipate and
prevent so that process remain in control.
STAGES OF PROCESS VALIDATION:

8. PROCESS VALIDATION:

9. TYPES OF PROCESS VALIDATION:
1. Prospective validation
2. Concurrent validation
3. Retrospective validation
4. Revalidation

10. • Prospective validation is done before the production
and during the development stage.
• In prospective validation one has to draw up the
plans and has to do the risk analysis.
• The primary aim is to establish the controlled
synergy.
1. PROSPECTIVE VALIDATION:

11. • To define commercial production process
• To define CQA (Critical Quality Attributes) and
CPP (Critical Process Parameter)
• Risk assessment – FMEA (Failure Mode And Effect
Analysis)
• Control to mitigate risk
OBJECTIVES OF PROSPECTIVE VALIDATION
:

12. • Concurrent validation is done to assure
and demonstrate that the process will
remain in state of control during
commercial manufacturing.
2. CONCURRENT VALIDATION :

13. • Qualification of process designed in stage-1
• Commercial scale production batches
• Close monitoring of all process parameters
• Insight on variability and our current controls
• Design of facility and qualification of equipment
CONCURRENT VALIDATION IS DONE
FOR:

14. • In this validation one has to collect and evaluate information
and data about :
-performance of the process.
-final control tests.
• How well the process parameters remain to the acceptable
range
• Data should be assessed periodically.
3. RETROSPECTIVE VALIDATION :

15. • In retrospective validation the evaluation parameters
includes :
1. Relevant Process Trends
2. Quality of incoming materials
3. In Process Material ,Etc.
• Data generated is statistically trended and reviewed by
trained person.
RETROSPECTIVE VALIDATION:

16. • Why revalidation is required ?
When any changes are made in the
process or its environment it is very essential
to ensure that it should not any adverse effect
on : - Product Quality or
- Process Characteristics
4. REVALIDATION:

17. • Changes in starting material
• Changes in packaging material
• Changes in process
• Changes in equipment
• Changes in support system or production
area
WHEN REVALIDATION IS
REQUIRED:

18. A. CHANGE IN STARTING
MATERIAL:

19. B. CHANGE IN PACKAGING MATERIAL:

20. C. CHANGES IN PROCESS :

21. D. CHANGE IN EQUIPMENT:

22. E. CHANGE IN SUPPORT SYSTEM OR
PRODUCTION AREA

23. Different Types of Validation Parameters :
Accuracy.
Precision.
Specificity.
Linearity. Range.
Limit of Detection.
Limit of Quantification.
Ruggedness.
Robustness.
5. VALIDATION PARAMETERS :

24. I. Accuracy :
Definition:
It is the closeness of agreement between the actual value
and measured value. Accuracy is calculated as the percentage
of recovery by the assay of the known added amount of the
analyte in the sample or the difference between the mean and
accepted true value together with confidence intervals.
The ICH guidance recommended to take a minimum of 3
concentration levels covering the specified range and 3
replicates of each concentration are analyzed (totally 3 * 3 = 9
determination)
5. VALIDATION PARAMETERS :

25. II. Precision:
Definition:
The closeness of agreement between a series of
measurements multiple samplings of the same
homogeneous sample under prescribed condition. The
precision of test method is usually expressed as the
standard deviation or relative standard deviation of a
series of measurements.
Precision may be considered at three levels:
Repeatability, Intermediate Precision and reproducibility.
5. VALIDATION PARAMETERS :

26. Method precision (Repeatability): Repeatability expresses
the precision under the same operating conditions over a
short interval of time. repeatability is also termed intra-
assay precision.
Intermediate Precision: It expresses with in laboratory
variations; different days, different analysts, different
equipment, etc.
Reproducibility: Precision between laboratories (mostly
performed during analytical method transfer).
5. VALIDATION PARAMETERS :

27. • Relative standard deviation:
This serves as a daily evaluation of the repeatability of the
system. Often, the relative standard deviation calculated as % RSD
for five or six replicate injections of a reference standard or working
standard is measured at the beginning of each set of analyses.
Standard deviation is calculated using the formula
Where,
s = standard deviation
x = each value in the sample
æ= mean of the values
N = the no. of values ( sample size)
5. VALIDATION PARAMETERS :

28. III. Specificity :
Definition
The ability to assess unequivocally the analyte in the presence of
components that may be expected to present, such as impurities,
degradation products and matrix components, etc.
Methodology:
Specificity shall be demonstrated by performing Placebo / blank
interference and forced degradation studies.
1. Blank interference:
Prepare blank solutions as per the test method and analyze them as
per the test method.
5. VALIDATION PARAMETERS :

29. 2. Placebo interference (In case of Drug products):
Prepare the placebo solution equivalent to the test
concentration (Subtract the weight of active ingredient) and
analyze it as per the test method.
3. Force Degradation studies :
Degrade the sample forcefully under the various stress
conditions like Light, heat, humidity, acid/base/water hydrolysis,
and oxidation and ensure the degradation and for peak purity.
Note: Based on the physicochemical properties and literature stress
conditions can be decided.
5. VALIDATION PARAMETERS :

30. IV. Linearity and Range :
Linearity:
The linearity of an analytical procedure is its ability (within
a given range) to obtain test results which are directly
proportional to the concentration (amount) of analyte in the
sample.
Range:
The range of analytical procedure is the interval between
the upper and lower concentrations of analyte in the analytical
procedure has a suitable level of precision, accuracy, and
linearity.
5. VALIDATION PARAMETERS :

31. Methodology:
At least 6 replicates per concentrations to be studied. Plot a
graph of concentration (on the x-axis) Vs mean response (on Y-axis).
Calculate the regression equation, Y – intercept and correlation
coefficient. Linearity shall be established across the range. If linearity
is not meeting the acceptance criteria, establish the range of
concentration in which it is linear.
5. VALIDATION PARAMETERS :

32. Correlation Co-efficient :
A measure of the strength of linear association between two variables. The
correlation will always between -1.0 and +1.0. If the correlation is positive, we have
a positive relationship. If it is negative, the relationship is negative.
Where,
N = Number of values or elements
X = First Score
Y = Second Score
Σxy = Sum of the product of first and Second Scores
Σx = Sum of First Scores
Σy = Sum of Second Scores
Σx 2 = Sum of square First Scores
Σy 2 = Sum of square Second Scores
5. VALIDATION PARAMETERS :

33. V. Limit of Detection :
Definition:
It is the lowest amount of analyte in a sample that can be
detected but not necessarily quantified under the stated experimental
conditions.
Methodology:
A. Visual Evaluation Method:
The 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.
5. VALIDATION PARAMETERS :

34. B. Based on Signal to Noise Ratio Method:
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 or 2:1 is generally considered acceptable for estimating the
detection limit.
C. Based on the standard Deviation of the Response and the Slope:
The detection limit (DL) may be expressed as:
The formula for calculating LOD is
LOD = 3.3 δ/S
Where δ = standard deviation of intercepts of calibration curves.
S = the slope of the linearity plot.
The slope shall be estimated from the calibration curve of the analyte.
5. VALIDATION PARAMETERS :

35. D. 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.
E. 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.
5. VALIDATION PARAMETERS :

36. VI. Limit of Quantification :
Definition:
It is lowest amount of analyte in a sample, which can be quantitatively
determined with acceptable accuracy and precision.
Methodology:
Following are different approaches:
A. Visual evaluation method:
The 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.
5. VALIDATION PARAMETERS :

37. B. Based on signal to noise ratio method:
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.
C. Based on the standard Deviation of the Response and the Slope:
The formula for calculating LOQ is
LOQ = 10 δ/S
Where
δ = standard deviation of response.
S = Mean of slopes of the calibration curves.
5. VALIDATION PARAMETERS :

38. D. 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.
E. 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.
5. VALIDATION PARAMETERS :

39. VII.Ruggedness
Definition:
Ruggedness is the degree of reproducibility of test
results obtained by the analysis of the same samples under a
variety of test conditions such as different laboratories, analysis,
instruments, reagent lots, elapsed assay times, temperature, days,
etc.
It can be expressed as a lack influence of the operation and
environmental variable on the test results of the analytical
method.
5. VALIDATION PARAMETERS :

40. VIII.Robustness
Definition:
It is a measure of the method's ability 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 be suitably controlled
or a precautionary statement should be included in the procedure.
5. VALIDATION PARAMETERS :

41. Examples of typical variations are:
Stability of analytical solutions
Extraction time
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
5. VALIDATION PARAMETERS :

42. The following are the typical method parameters need to change
deliberately and verify during method validation:
Flow rate: (+/- 0.2ml/minutes).
Mobile phase composition: (+/- 10% of organic phase).
Column oven temperature: (+/- 5°C).
PH of buffer in mobile phase: (+/- 0.2 units).
Filter suitability: (At least two filters).
5. VALIDATION PARAMETERS :

43. Methodology:
a) Mobile phase variation: Prepare the mobile phases by changing organic
phase to +/-10 % of the mobile phase composition.
b) Flow rate: Change the flow rate by +/- 0.2 ml/minutes of the target flow
rate mentioned in test method.
c) Temperature of the Column: Change the temperature of the column by +/-
5.0°C of the target temperature mentioned in Test method.
d) PH of the buffer of mobile phase: Prepare the mobile phases by changing
the pH of the buffer by +/- 0.2 units of the pH mentioned in the test method.
e) Filter Suitability: Prepare the test solution as per the test method and filter
through two different types of filters. Analyse the sample as per the test
method and compare the results against the unfiltered / centrifuged sample.
5. VALIDATION PARAMETERS :

44. 1. Prabh Simran Singh, Gagan Shah, Analytical Method Development and
Validation, Journal of Pharmacy Research, 4(7), 2011, 2330-2332.
2. Ravisankar P, Gowthami S, and Devala Rao G, A review on analytical method
development, Indian journal of research in pharmacy and biotechnology, 2,
2014, 1183-1195.
3. Validation of analytical procedure: Methodology Q2B, ICH Harmonized
Tripartite Guidelines, 1996:1-8.
4. International Conference on Harmonization of Technical Requirements for
Registration of Pharmaceuticals for Human Use ICH Harmonized tripartite
guideline Validation
5. Ravisankar P, Anusha S, Supriya K, Ajith Kumar U, Fundamental
chromatographic parameters, Int. J. Pharm. Sci. Rev. Res., 55(2), 2019,46-50.
REFERENCES