Wednesday 29 August 2018

Introduction to Analytical Method Validation

Introduction to Analytical Method Validation

The analytical results you communicate can have far-reaching consequences and can form the basis for taking decision on safety of use of commercial products, foods and natural resources in addition to decisions involving legal matters. As a responsible analyst before you undertake analysis in the laboratory you should make sure that your results are authentic and are universally acceptable. This key objective can be realized only if the method selected for the purpose is duly validated.
Analytical method validation establishes documented evidence that the procedure adopted for a test is fit for the intended purpose in terms of quality, reliability and consistency of results.

Each and every method requires validation:

  • Before putting to routine use
  • When analytical conditions are changed such as change of technique, change in desired concentration range or change of sample matrix
  • Whenever changes are made to an existing procedure
It is important to collect relevant information on analysis requirements before you plan validation of the procedure
  • Components to be detected
  • Expected concentration levels
  • Required level of detection and quantification
  • Nature of sample matrix
  • Type of analytical technique to be used
  • Required degree of precision and accuracy

Parameters of Method Validation

  • Selectivity and specificity
  • Linearity
  • Range
  • Accuracy
  • Precision
  • Limit of quantification
  • Ruggedness
  • Robustness
We shall discuss each of the parameters in detail so that you can better understand analytical method validation

Selectivity and Specificity

Selectivity refers to ability of a method to determine a specific analyte or group of analytes without interference from other components of the sample matrix.
Specificity refers to ability of the method to respond to a single specific analyte only.
Selectivity is more frequently used as analytical techniques are seldom specific to only one analyte. Further selectivity should not be affected by interfering species such as degradation products, impurities and other matrix components.

Linearity

Linearity refers to the ability of analytical procedures to produce results in direct proportion to the concentration range of analyte in samples within the required concentration levels.
  • Linearity should be determined using a minimum of 6 standards whose concentration spans from 80% to 120% of expected concentration level.
  • Linearity report should include slope of line, linear range and correlation coefficient data. Correlation coefficient r should be greater than or equal to 0.99 in the working range

Range

Operating range is deduced from the calibration plot. It is the interval between the upper and lower concentration of analyte falling in the linear range. The results corresponding to this range demonstrate acceptable levels of precision, accuracy and linearity.

Accuracy

  • Degree to which the determine value of analyte corresponds to the true value.
  • Accuracy can vary over the expected concentration range.
  • It should be determined using a working or reference standards in the 80% – 120% level of expected range
  • Accuracy is determined by :
  1. Analyzing a sample of known concentration and comparing with the true value
  2. Spiking a blank (Sample having all components except the analyte) and comparing with the expected result.
  3. Standard addition method in which the sample concentration is determined. A known amount of analyte is added and the concentration is once again determined. The difference of the two concentration values is compared with the actual value of added analyte.
  • Accuracy is also defined by the comparison of test results with those obtained using another validated test procedure

Precision

  • Precision expresses closeness of a series of measurements of the same sample under identical conditions
  • High degree of precision does not necessarily means a high degree of accuracy
  • Precision is expressed as variance, standard deviation or as coefficient of variation of a series of measurements
  • Minimum of five replicate sample determinations should be carried out

Limit of Detection

  • Lowest amount of an analyte that can be detected but not necessarily quantified
  • Lowest concentration of calibration standard which produces a peak response corresponding to the analyte should be measured at least 6 to 10 times. Average response (X) and standard deviation (SD) are required to calculate limit of detection
Limit of detection = X + (3SD)
  • Signal to noise ratio at limit of detection should be at least 3:1

Signal to noise ratio should be greater than 3 at limit of detection and greater than 10 at limit of quantification

 Limit of Quantitation 

  • Lowest amount of the analyte that can be quantitatively determined with defined precision under the stated experimental conditions
  • 6 – 10 observations should be made for average response and standard deviation
Limit of quantitation = X + (10SD)
  • Signal to noise ratio should be at least 10:1 at the limit of quantitation

Ruggedness

Ruggedness measures reproducibility of test results under following conditions :
  • Results generated for same sample under identical conditions by different laboratories
  • Results generated for sample under identical conditions by different analysts
  • Same analysis using different instruments
  • Same analysis under different environmental conditions
  • Same analysis using test materials from different sources

Robustness

Robustness examines the effect of operational parameters changes on the analytical results
  • pH
  • Temperature
  • Operational conditions such as flow rate, injection volume, detection wavelength or mobile phase composition in chromatographic analysis
Variation should be deliberate but within realistic range to study the robustness of the method. The results of the analysis after making the deliberate changes should be within the method’s specified tolerance limits.

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