You are hereA REVIEW ON ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF PHARMACEUTICAL TECHNOLOGY
A REVIEW ON ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF PHARMACEUTICAL TECHNOLOGY
7. Limit of quantification:
The limit of quantization is the minimum injected amount that produces quantitative Measurements in the target matrix with acceptable precision in chromatography, typically requiring peak heights 10 to 20 times higher than the baseline noise. If the required precision of the method at the limit of quantization has been specified, the EURACHEM (22) approach Can be used. It is important to use not only pure standards for this test but also spiked matrices that closely represent the unknown samples. For the limit of detection, the ICH (5) recommends, in addition to the procedures as described above, the visual inspection and the standard deviation of the response and the slope of the calibration curve. Figure 3 illustrates the limit of quantization (along with the limit of detection, range and linearity). Figure 4 illustrates both the limit of detection and the limit of quantization.
Figure No 2 Shows Limit of Quantification&Detection
From the repeatability standard deviation are it is useful to calculate the ‘repeatability limit ‘r’’, which enables the analyst to decide whether the difference between duplicate analyses of a sample, determined under repeatability conditions, is significant.
9. Measurement uncertainty
Measurement uncertainty is a single parameter (usually a standard deviation with a Coverage factor or confidence interval) expressing the range of values possible on the basis of the measurement result. A measurement uncertainty estimate takes account of all Recognized effects operating on the result; the uncertainties associated with each effect are combined according to well-established procedures. An uncertainty estimate for analytical Chemistry is often termed an ‘uncertainty budget’ and should take into account .The overall, long-term precision of the method;[ 55-56]
· Bias and its uncertainty, including the statistical uncertainty involved in the bias measurements, and the reference material or method uncertainty. It may be necessary to increase the estimate where a significant bias is detected but left uncorrected.
· Calibration uncertainties. As most equipment calibration uncertainties will be Negligibly small by comparison with overall precision and uncertainty in the bias; this needs only to be verified;
· Any significant effects operating in addition to the above. For example, temperature or time ranges permitted by the method may not be fully exercised in validation studies, and their effect may need to be added. Such effects can be usefully quantified by robustness studies (see ‘Ruggedness’ below) or related studies which establish the size of a given effect on the result. Where the contribution of individual effects is important, for example in calibration laboratories.
This is effectively the gradient of the response curve, i.e. the change in instrument response, which corresponds; to a change in analyze concentration. Where the response has been established as linear with respect to concentration, i.e. within the linear range of the method, and the intercept of the response curve has been determined, sensitivity is a useful parameter to calculate and use in formulae for quantization. 
11. Ruggedness (or robustness)
Ruggedness is normally evaluated during method development, typically by the originating Laboratory, before collaborating with other laboratories and is a measure how well a method stands up to less than perfect implementation. Performance, and may even result in the method not working at all. These stages should be identified, usually as part of method development, and if possible, their influence on method performance evaluated using ‘ruggedness tests’, sometimes also called ‘robustness tests’[56 57]
The efficient development and validation of analytical methods are critical elements in the development of pharmaceuticals. Success in these areas can be attributed to several important factors, which, in turn, will contribute to regulatory compliance. Experience is one of these factors both the experience level of the individual scientists and the collective experience level of the development and validation department .Recent development in pharmaceutical and biotechnological field generates a cumulative demand for analytical methods. Rapid and accurate quantification of the substrate and drug product is important in the process development. Improvements in analytical instrumentation leads to development of new techniques like isocratic and gradient RP-HPLC, which evolved as the primary techniques for the analysis of nonvolatile APIs and impurities. These analytical methods are critical elements of pharmaceutical development so it is very important to develop efficient and accurately validated analytical methods to develop safe and effective drugs. 
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