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Validation of Analytical Procedures: Methodology
http://www.nihs.go.jp/drug/validation/q2bwww.html

ICH Topic Q 2 B
Validation of Analytical Procedures: Methodology

Step 4, Consensus Guideline, 6 November 1996

[ICH Harmonised Tripartite Guideline]

INTRODUCTION

This guideline is complementary to the parent guideline* which presents a discussion of the characteristics that should be considered during the validation of analytical procedures. Its purpose is to provide some guidance and recommendations on how to consider the various validation characteristics for each analytical procedure. In some cases (for example, demonstration of specificity), the overall capabilities of a number of analytical procedures in combination may be investigated in order to ensure the quality of the active substance or medicinal product. In addition, the document provides an indication of the data which should be presented in an application for marketing authorisation.

All relevant data collected during validation and formulae used for calculating validation characteristics should be submitted and discussed as appropriate.

Approaches other than those set forth in this guideline may be applicable and acceptable. It is the responsibility of the applicant to choose the validation procedure and protocol most suitable for the product. However it is important to remember that the main objective of validation of an analytical procedure is to demonstrate that the procedure is suitable for its intended purpose. Due to their complex nature, analytical procedures for biological and biotechnological products in some cases may be approached differently than in this document.

Well-characterised reference materials, with documentated purity, should be used throughout the validation study. The degree of purity necessary depends on the intended use.

In accordance with the parent guideline*, and for the sake of clarity, this document considers the various validation characteristics in distinct sections. The arrangement of these sections reflects the process by which an analytical procedure may be developed and evaluated.

In practice, it is usually possible to design the experimental work so that the appropriate validation characteristics can be considered simultaneously to provide a sound, overall knowledge of the capabilities of the analytical procedure, for instance: specificity, linearity, range, accuracy and precision.
*ICH Harmonised Tripartite Guideline: Validation of Analytical Methods: Definitions and Terminology, ICH Topic Q2A.

1. SPECIFICITY

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.
1.1 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 (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. The choice of such potentially interfering materials should be based on sound scientific judgement with a consideration of the interferences that could occur.
1.2 Assay and Impurity Test(s)

For chromatographic procedures, representative chromatograms should be used to demonstrate specificity and individual components should be appropriately labelled. Similar considerations should be given to other separation techniques.

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 active substance for release, the combination of the assay and a suitable test for impurities can be used.

The approach is similar for both assay and impurity tests.

1.2.1. Discrimination of analytes where 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 (active substance or product) with appropriate levels of impurities and/or excipients and demonstrating that the assay result is unaffected by the presence of these materials (by comparison with the assay result obtained on unspiked samples).

For the impurity test, the discrimination may be established by spiking active substance or product with appropriate levels of impurities and demonstrating the separation of these impurities individually and/or from other components in the sample matrix.

1.2.2. Discrimination of the analyte where impurities are not available

If impurity or degradation product standards are unavailable, specificity may be demonstrated by comparing the test results of samples containing impurities or degradation products to a second well-characterised procedure e.g.: pharmacopoeial 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.

- for the assay, the two results should be compared.

- for the impurity tests, the impurity profiles should be compared.

Peak purity tests may be useful to show that the analyte chromatographic peak is not attributable to more than one component (e.g., diode array, mass spectrometry).
2. LINEARITY

A linear relationship should be evaluated across the range (see section 3) of the analytical procedure. It may be demonstrated directly on the active substance (by dilution of a standard stock solution) and/or on separate weighings of synthetic mixtures of the product components, using the proposed procedure. The latter aspect can be studied during investigation of the range.

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.

The correlation coefficient, y-intercept, slope of the regression line and residual sum of squares should be submitted. A plot of the data should be included. 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.

For the establishment of linearity, a minimum of 5 concentrations is recommended. Other approaches should be justified.
3. 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.

The following minimum specified ranges should be considered:

- for the assay of an active substance or a finished product: normally from 80 to 120 percent of the test concentration;

- for content uniformity, covering a minimum of 70 to 130 percent of the test concentration, unless a wider more appropriate range, based on the nature of the dosage form (e.g., metered dose inhalers), is justified;

- 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.

- for the determination of an impurity: from the reporting level of an impurity to 120% of the specification; for impurities known to be unusually potent or to produce toxic or unexpected pharmacological effects, the detection/ quantitation limit should be commensurate with the level at which the impurities must be controlled.
Note: for validation of impurity test procedures carried out during development, it may be necessary to consider the range around a suggested (probable) limit;

- if assay and purity are performed together as one test and only a 100% standard is used, linearity should cover the range from the reporting level of the impurities1 to 120% of the assay specification;
4. ACCURACY

Accuracy should be established across the specified range of the analytical procedure.
4.1 Assay

4.1.1 Active Substance

Several methods of determining accuracy are available:

a) application of an analytical procedure to an analyte of known purity (e.g. reference material);

b) comparison of the results of the proposed analytical procedure with those of a second well-characterised procedure, the accuracy of which is stated and/or defined (independent procedure, see 1.2.2);

c) accuracy may be inferred once precision, linearity and specificity have been established.

4.1.2 Medicinal Product

Several methods for determining accuracy are available:

a) application of the analytical procedure to synthetic mixtures of the product components to which known quantities of the substance to be analysed have been added;

b) in cases where it is impossible to obtain samples of all product components , it may be acceptable either to add known quantities of the analyte to the product or to compare the results obtained from a second, well characterised procedure, the accuracy of which is stated and/or defined (independent procedure, see 1.2.2).

c) accuracy may be inferred once precision, linearity and specificity have been established.
4.2 Impurities (Quantitation)

Accuracy should be assessed on samples (substance/ 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 (see 1.2.2). 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.
4.3 Recommended Data

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 together with the confidence intervals.
5. PRECISION

Validation of tests for assay and for quantitative determination of impurities includes an investigation of precision.
5.1 Repeatability

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.
5.2 Intermediate Precision

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.
5.3 Reproducibility

Reproducibility is assessed by means of an inter-laboratory trial. Reproducibility should be considered in case of the standardisation of an analytical procedure, for instance, for inclusion of procedures in pharmacopoeias. This data is not part of the marketing authorisation dossier.
5.4 Recommended Data

The standard deviation, relative standard deviation (coefficient of variation) and confidence interval should be reported for each type of precision investigated.
6. DETECTION LIMIT

Several approaches for determining the detection limit are possible, depending on whether the procedure is a non-instrumental or instrumental. Approaches other than those listed below may be acceptable.
6.1 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 .
6.2 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 or 2:1 is generally considered acceptable for estimating the detection limit.
6.3 Based on the Standard Deviation of the Response and the Slope

The detection limit (DL) may be expressed as:

where
s = 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. The estimate of may be carried out in a variety of ways, for example:

6.3.1 Based on the Standard Deviation of the Blank

Measurement of the magnitude of analytical background response is performed by analysing an appropriate number of blank samples and calculating the standard deviation of these responses.

6.3.2 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.
6.4 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.
7. QUANTITATION LIMIT

Several approaches for determining the quantitation limit are possible, depending on whether the procedure is a non-instrumental or instrumental. Approaches other than those listed below may be acceptable.
7.1 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.
7.2 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.
7.3 Based on the Standard Deviation of the Response and the Slope

The quantitation limit (QL) may be expressed as:

where
s = 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. The estimate of may be carried out in a variety of ways including:

7.3.1 Based on Standard Deviation of the Blank

Measurement of the magnitude of analytical background response is performed by analysing an appropriate number of blank samples and calculating the standard deviation of these responses.

7.3.2 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.
7.4 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.
8. ROBUSTNESS

The evaluation of robustness should be considered during the development phase and depends on the type of procedure under study. It should show the reliability of an analysis with respect to deliberate variations in method parameters.

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.

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.

In the case of gas-chromatography, examples of typical variations are

- different columns (different lots and/or suppliers),

- temperature,

- flow rate.
9. 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 analysed 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. See Pharmacopoeias for additional information.



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   1.    Global Warming Albedo Enhancement

      1.0 Introduction
      2.0 Executive Summary
      3.0 Background
      4.0 Surface Albedo Enhancement
      5.0 References


The Chrom-Ed Chromatography Series by
Dr. R. P. W. Scott

   1. Principles and Practice of Chromatography

      Introduction
      The Development Process
      Chromatography Nomenclature
      Factors Controlling Retention
      Factors Affecting the Magnitude of the Distribution Coefficient (K)
      Molecular Forces and Chromatographic Selectivity
      The Control of Chromatographically Available Stationary Phase (Vs)
      Peak Dispersion in a Chromatographic Column
      The Basic Column Chromatograph
      Thin Layer Chromatography
      Chromatography Applications
      References

   2. Gas Chromatography

      Introduction
      The Modern Gas Chromatograph
      Gas Supplies
      Injection Devices
      GC Columns
      The Column Oven and Temperature Programmer
      GC Detectors
      Data Acquisition and Processing
      Quantitative Analysis
      Preparative Gas Chromatography
      Applications
      References

   3. Liquid Chromatography

      Introduction
      The Basic Liquid Chromatograph
      Column Ovens
      Detectors
      The UV Detector
      The Electrical Conductivity Detectors.
      The Fluorescence Detector
      The Refractive Index Detector
      The Tridet Multi Functional Detector
      Data Acquisition and Processing
      Liquid Chromatography Stationary Phases
      Macroporous Polymers
      LC Mobile Phases
      Chiral Stationary Phases
      Liquid Chromatography Applications
      References

   4. Gas Chromatography Detectors

      Introduction
      Classification of Detectors
      Detector Specifications
      The Form of Detector Response
      The Dynamic Range of the Detector
      Detector Linearity
      Detector Response
      Detector Noise
      Detector Sensitivity or Minimum Detectable Concentration
      System Dispersion and Sensor Dispersion
      Peak Dispersion from the Overall Detector Time Constant
      Pressure Sensitivity
      Flow Sensitivity
      Temperature Sensitivity
      Summary of Detector Criteria
      Early Gas Chromatography Detectors
      The General Properties of GC Detectors
      The Katharometer Detector
      The Simple Gas Density Balance
      The Flame Ionization detector
      The Response Mechanism of the FID
      The Operation of the FID
      The Nitrogen Phosphorus Detector (NPD)
      The Emissivity or Photometric Detector
      Ionization Detectors
      The Radioactivity Detector
      Some Less Common GC Detectors
      Closing Notes
      References

   5. Liquid Chromatography Detectors

      Introduction
      Detector Specifications
      Dispersion in Detector Sensors
      LC Detectors Based on Refractive Index Measurement
      The UV Detectors
      The Fluorescence Detector
      Transport Detectors
      The Evaporative Light Scattering Detector
      Liquid Light Scattering Detectors
      The Electrical Conductivity Detector
      The Electrochemical Detector
      References

   6. Plate Theory and Extensions
      
   7. The Mechanism of Chromatographic Retention

      Introduction
      Chromatographic Interactions
      Mixed Phases
      The Association of Methanol with Water
      Solvent/Solute Interactions with Adsorbent Surfaces
      Solute Stationary Phase Interactions
      Retention and Exclusion
      Chiral Chromatography
      References

   8. The Thermodynamics of Chromatography
      
   9. Dispersion in Chromatography Columns
      
  10. Extra Column Dispersion
      
  11. Preparative Chromatography


      Introduction
      The Loading Capacity of a Column
      The Maximum Sample Volume
      Sample Volume Overload
      Sample Mass Overload
      Preparative Chromatography Apparatus
      Packing Preparative Columns
      Recycling Development
      Alternative Preparative Techniques
      Radial Flow Chromatography
      The Preparative Separation of the Enantiomers of Chlorokynurenine
      Criteria for the Successful Operation of Preparative Chromatographs.
      References
       


GC Trouble shooting:
GC Trouble shooting:

Baseline problems arise from many causes. Some of these are:
Electronic or mechanical failure
Contamination in critical areas, such as detectors
Incorrect or inappropriate setpoints
Leaks, column or septum bleed, or other chromatographic difficulties
These problems may interact to a certain degree and or arise from any of the above areas.
Baseline Symptoms:
Position
1. Baseline not at left (lower) part of chart:
-Check the zero of your recording device: An attenuation or range change during
the run may be responsible.
-Check the TCD polarity.
Gas Chromatographic Baseline Problems.doc http:// www.chem.agilent.com Page 2 of 4
2. Baseline position changes suddenly during the run:
-This usually results from a range or attenuation change.
-It can also result from valve operations: If valves are being switched during the run.
-Septum leak
Wander and Drift
Baseline wander and drift may occur when a flow or temperature setting is changed. If the system is not stabilized at the new conditions before starting a run, some baseline changes are to be expected.
(The following assumes that sufficient time has elapsed for stabilization.)
1. Baseline moves steadily upscale or downscale (drift) during the run.
-This is most frequently seen during temperature programming: Operation with a single column (no column compensation) at moderate to low attenuation causes this. If dual columns are used, check that the signal mode is correct for column compensation.
-It is also possible that the compensation is insufficient or too great. Thorough column conditioning minimizes (this cause of drift).
2. Baseline erratic, moves up and down (wander):
- Suspect a leak in the system: Check septum condition and replace if necessary.
Check column connections.
- If there is a leak at the detector end of the system then retention times should be
stable and only sensitivity is reduced. A leak at the inlet end of the column will result in decreased sensitivity and delayed retention times.
Gas Chromatographic Baseline Problems.doc http:// www.chem.agilent.com Page 3 of 4
Noise
Noise is rapid vertical baseline fluctuations, broadening the baseline and giving it a hairy appearance. Noise is different from spiking; spikes are isolated events, rather than almost continuous.
Some noise is inevitable with any detector. At high attenuation it is invisible but appears as attenuation is decreased.
1. Noise appears suddenly on a previously clean baseline:
-Consider all changes made recently to the system: Reduced attenuation for example.
-New septa may contribute noise from bleed of low molecular weight material. If noise decrease when inlet temperature is lowered, this is the likely cause.
-Contaminated carrier gas: Check to see if a new tank was replaced recently, replace with a different lot number. If the new gas was badly contaminated it may have contaminated the traps and changing the tank may not show any improvement until the traps are regenerated.
-Contaminated detector gases (hydrogen or air)
-Air currents from a fan or air conditioner blowing across the top of the instrument may interfere with gas exiting from the detector.
-A contaminated detector results in noise.
2. Noise increases gradually to an unacceptable level:
-This indicates a gradual build up of the noise source, rather than an abrupt change as discussed above. Flame ionization detectors are susceptible to build up of deposits in the collector. In extreme cases spiking occurs along with increased noise level.
-Silicon dioxide deposits are formed when bleed from a silicone column is burned in the flame. This material is removed mechanically. Preventative measures include use of low column loadings, stationary phases with high temperature limit, thorough column conditioning before use, and the lowest possible oven temperatures for the analysis.
-Carbon deposits may form from solvents that burn poorly (chlorinated and aromatics). If possible, avoid such solvents. If they are necessary, periodic cleaning of the collector is required.
Gas Chromatographic Baseline Problems.doc http:// www.chem.agilent.com Page 4 of 4
-Gradual noise increase may occur from saturated carrier gas drier or chemical traps. When these approach their capacities, contaminants begin to pass through and create noise. Trap and drier regeneration or replacement eliminates this source
of noise.
Spiking： Spikes are isolated baseline disturbances, usually as sudden and large upscale
movements. If accompanied by noise, the noise problem should be solved first, since spiking may disappear at the same time.
1. Spikes appear whenever the chart is running:
-The cause is almost always electronic in origin: Loose connections are likely. Check signal cable connections at the detector and controller ends.
-Loose or dirty contacts between printed circuit boards and their connectors may be responsible.
2. Spikes appear on chromatograms but not when the recorder is isolated, (no input signal)
-This could be indicative of a detector problem: For example, an extremely dirty FID collector.
-If a metal or glass packed column is being used column material could have been blown into the detector: FID and NPD are more susceptible due to the narrow bore of the jet.
Systematically troubleshooting the GC is key to understanding and diagnosing the cause of baseline problems. Isolating the problem can usually be accomplished by simply identifying “what was changed last.” If problems still occur after stepping through the suggestions in this document please call for Agilent Technical Assistance.