Method performance indicators

Several method performance indicators are tracked, monitored and recorded. Items that are recorded include the date of analysis, identification of the HPLC system, identification of the analyst, number and type of samples analyzed, the system precision, the critical resolution or... 

FIGURE 19 Control charts of six quantitative method performance indicators. 

FIGURE 23 Quantitative method performance indicators can be piotted in controi charts. 

Several method performance indicators are tracked, monitored, and recorded, including the date of analysis, identification of equipment, identification of the analyst, number and type of samples analyzed, the system precision, the critical resolution or tailing factor, the recovery at the reporting threshold level, the recovery of a second reference weighing, the recovery for the control references (repeated reference injections for evaluation of system drift), the separation quality, blank issues, out of spec issues, carry over issues, and other nonconformances. The quantitative indicators are additionally visualized by plotting on control charts (Figure 23). 

The performance of a chemical plant depends upon an enormously high number of design and operating variables. This great number of process variables makes it impossible to find optimal conditions within the region of safe operation if no quantitative relationships (defined in terms of mathematics) between performance indices and process variables are known. In general, optima are complex functions of process variables, and therefore quantification of experimental ressults is needed. The methods for scale-up that were conventionally used at the time of Perkin chemistry resulted in successful commercialization of many laboratory recipes. This evolutionary, step-by-step method of scale-up is illustrated in Fig. 5.3-1 (after Moulijn et al. 2001). 

Where the performance verification data indicate that method performance is not adequate, the method may be modified as appropriate and subsequently validated. 

DP-6 over 3000 soil samples collected from several terrestrial field dissipation studies. The sample procedural recoveries using this method, conducted concurrently with the treated samples during soil residue analysis, are summarized in Table 5. This method was proven to be short, rugged, sensitive, and suitable for measuring residues in soil and sediment at levels down to 0.01 mg kg . The reproducibility of the methods also indicated acceptable method performance and, as a result, thousands of samples were analyzed using this methodology. 

A mathematical formulation based on uneven discretization of the time horizon for the reduction of freshwater utilization and wastewater production in batch processes has been developed. The formulation, which is founded on the exploitation of water reuse and recycle opportunities within one or more processes with a common single contaminant, is applicable to both multipurpose and multiproduct batch facilities. The main advantages of the formulation are its ability to capture the essence of time with relative exactness, adaptability to various performance indices (objective functions) and its structure that renders it solvable within a reasonable CPU time. Capturing the essence of time sets this formulation apart from most published methods in the field of batch process integration. The latter are based on the assumption that scheduling of the entire process is known a priori, thereby specifying the start and/or end times for the operations of interest. This assumption is not necessary in the model presented in this chapter, since water reuse/recycle opportunities can be explored within a broader scheduling framework. In this instance, only duration rather start/end time is necessary. Moreover, the removal of this assumption allows problem analysis to be performed over an unlimited time horizon. The specification of start and end times invariably sets limitations on the time horizon over which water reuse/recycle opportunities can be explored. In the four scenarios explored in... 

Hasegawa et al. [76] measured miconazole serum concentration by a high performance liquid chromatographic method. The authors assessed whether the internal standard method produced an intra-assay error and found that the method gave more precise and more reproducible results compared to the absorption calibration curve method. With 0.5 pg/mL of miconazole, the coefficient of variation produced by that method was 3.41%, whereas that of the absorption calibration curve method was 5.20%. The concentration of absorptions calibration curve method showed higher values than the internal standard method. This indicated that the internal standard method was far more precise in measuring the miconazole serum concentrations than the absorption calibration curve method. 

Key Performance Indicators (KPIs) in supply chain balanced scorecards and performance management are one example for analysis methods. Beamon (1998) and Chan (2003) distinguish qualitative performance measures such as customer satisfaction, on-time delivery, fill rate or flexibility as well as quantitative measures based on costs in distribution, manufacturing and inventory or warehousing. 

For the dissolution test to be used as an effective drug product characterization and quality control tool, the method must be developed with the various end uses in mind. In some cases, the method used in the early phase of product and formulation development could be different from the final test procedure utilized for control of the product quality. Methods used for formulation screening or BA and/or bioequivalency evaluations may simply be impractical for a quality control environment. It is essential that with the accumulation of experience, the early method be critically re-evaluated and potentially simplified, giving preference to compendial apparatus and media. Hence, the final dissolution method submitted for product registration may not necessarily closely imitate the in vivo environment but should still test the key performance indicators of the formulation. 

The data compiled in Tables 6.15 and 6.16 indicate how a selection of methods perform in determining reaction barriers for methyl radical additions to a series of substituted alkenes. The experimental values with which comparisons are made in Tables 6.15 - 6.20 come from experiments in solution [40, 42, 45, 46] so there is the possibility of non-negligible solvent effects in some instances. 

The development lab can benefit from valuable objective data to detect method shortcomings and to identify gaps in the method development process. The feedback on method performance should be discussed regularly. During the monitoring a number of key performance indicators are recorded and filled out in feedback sheets by the application labs (stability and operational labs) each time the method is applied. The method feedback sheet is sent together with the method description to the application labs at transfer. An example of such a feedback sheet is shown in Figure 22. 

Where A tp is the number of true positives, A/pw is the number of false negatives, A/jn is the number of true negatives, A pp is the number of false positives, and N = A/pp + AlpN + A/tn + A fp- Sensitivity and specificity are often expressed as either fractional quantities ranging from 0 to 1, or percentage quantities ranging up to 100%. In either case, 1.0 or 100% for both metrics indicates perfect method performance. 

The purpose of an analytical method is the deliverance of a qualitative and/or quantitative result with an acceptable uncertainty level. Therefore, theoretically, validation boils down to measuring uncertainty . In practice, method validation is done by evaluating a series of method performance characteristics, such as precision, trueness, selectivity/specificity, linearity, operating range, recovery, LOD, limit of quantification (LOQ), sensitivity, ruggedness/robustness, and applicability. Calibration and traceability have been mentioned also as performance characteristics of a method [2, 4]. To these performance parameters, MU can be added, although MU is a key indicator for both fitness for purpose of a method and constant reliability of analytical results achieved in a laboratory (IQC). MU is a comprehensive parameter covering all sources of error and thus more than method validation alone. 

Measure of capacity of analytical procedure to remain unaffected by small but deliberate variations in method performance parameters, which provides an indication of its reliability during normal usage (term used by USP/ICH only)... 

Laboratories using these methods for regulatory purposes are required to operate a formal quality control program. The minimum requirements of the program consist of an initial demonstration of laboratory capability and an ongoing analysis of spiked samples to evaluate and document data quality. The laboratory must maintain records to document the quality of data that is generated. Ongoing data quality checks are compared with established performance criteria to determine whether or not the results of analyses meet the demonstrated performance characteristics of the method. When results of spike sample analyses indicate atypical method performance, a quality control check standard must be analyzed to confirm that the measurements were performed in an in-control mode of operation. 

ED appears to be an inefficient method to recover free citric acid because of its low electric conductivity (Novalic et al., 1995). As it is converted into the monovalent (at pH ca. 3), divalent (at pH ca. 5), or trivalent (at pH about 7) citrate anion, there is a significant increase in the electric conductivity (%), the latter increasing from 0.95 to 2.18 and to 3.9 S/m, respectively, in the case of an aqueous solution containing 50 kg/m3 of citric acid equivalent (Moresi and Sappino, 1998). By increasing the pH from 3 to 7, e reduced about eight times, the solute flux (JB) practically doubled, while the overall water transport (/w) increased 3-4 times. The latter partly counterbalanced the greater effectiveness of the electrodialytic concentration of citric acid at pH 7 with respect to that at pH 3. Table XV presents a summary of the effect of current density ( j) on the main performance indicators of the electrodialytic recovery of the monovalent, divalent, or trivalent ionic fractions of citric acid (Moresi and Sappino, 1998). All the mean values or empirical correlations of the earlier indicators were useful to evaluate the economic feasibility of this separation technique (Moresi and Sappino, 2000). 

According to the first method the indicated multiplication would be performed, the mole fractions expressed in terms of the mole numbers and the differentiation carried out. According to the second method the indicated... 

Figure 6.1 Bar-graph of MeHg in CRM 580. The results correspond to six replicate determinations as performed by different laboratories using various methods. MEANS indicates the mean of laboratory means with 95% confidence interval. Abbreviations-. CVAAS, cold vapour atomic absorption spectrometry CVAFS, cold vapour atomic fluorescence spectrometry ECD, electron capture detection GC, gas chromatography HPLC, high-performance liquid chromatography ICPMS, inductively coupled plasma mass spectrometry MIP, microwave induced plasma atomic emission spectrometry QFAAS, quartz furnace atomic absorption spectrometry SFE, supercritical fluid extraction.

---