Accuracy evaluation quality control

Relatively recently, AIS Sommer GmbH of Germany delivered a laser-induced fluorescence (LIP) analyzer for quality control in minerals and mineral processing (Broicher 2000). The LIP analyzer includes two light detector systems with three photomultipliers each, which evaluate three spectral bands in two time windows each. It was done in the Kiruna phosphorous iron ore mine, Sweden. The limitation of LIP analysis is that its accuracy depends on the complexity of the composition of the ore and the concentration and fluorescence properties of the critical minerals in relation to all the other minerals present. The phosphorous iron ore in Kiruna is ideal for LIP analyzes, because its iron minerals are practically non-luminescent, while magmatic apatite is strongly fluorescent with intensive emissions of Ce and Eu ". ... 

The error of an analytical result is related to the (in)accuracy of an analytical method and consists of a systematic component and a random component [14]. Precision and bias studies form the basis for evaluation of the accuracy of an analytical method [18]. The accuracy of results only relates to the fitness for purpose of an analytical system assessed by method validation. Reliability of results however has to do with more than method validation alone. MU is more than just a singlefigure expression of accuracy. It covers all sources of errors which are relevant for all analyte concentration levels. MU is a key indicator of both fitness for purpose and reliability of results, binding together the ideas of fitness for purpose and quality control (QC) and thus covering the whole QA system [4,37]. 

Laboratory equipment and procedures must be qualified and validated. Every NDA/ANDA inspection will include both an evaluation of laboratory controls and procedures and an audit of some of the raw data used to generate results. These data may be located in research and development test logs. The authenticity and accuracy of data used in the development of a test method should be established. (See the Guide to Inspection of Pharmaceutical Quality Control Laboratories, July 1993.)... 

When conducting an inspection, several target areas must be evaluated. Control limits or "charts" are helpful and should be established by plotting the defined limits of acceptable quality control. These charts are important tools for assessing laboratory precision, accuracy, and reproducibility. They can be based on a curve established from the high, mid, and low concentrations of a standard analyte. Either the mid level or the average of the three concentrations then becomes the mid-line for the control chart. Acceptable levels of fluctuation for routine mid-level standards,... 

When the analytical laboratory is not responsible for sampling, the quality management system often does not even take these weak links in the analytical process into account. Furthermore, if sample preparation (extraction, cleanup, etc.) has not been carried out carefully, even the most advanced, quality-controlled analytical instruments and sophisticated computer techniques cannot prevent the results of the analysis from being called into question. Finally, unless the interpretation and evaluation of results are underpinned by solid statistical data, the significance of these results is unclear, which in turn greatly undermines their merit. We therefore believe that quality control and quality assurance should involve all the steps of chemical analysis as an integral process, of which the validation of the analytical methods is merely one step, albeit an important one. In laboratory practice, quality criteria should address the rationality of the sampling plan, validation of methods, instruments and laboratory procedures, the reliability of identifications, the accuracy and precision of measured concentrations, and the comparability of laboratory results with relevant information produced earlier or elsewhere. 

Quality control procedures are generally established to provide checks on the data that have been collected to evaluate whether in fact the quality assurance procedures were followed and whether the data meet agreed-upon norms. Otherwise, it is difficult for the user to judge the integrity of a data set per se, because there may be few ways to tell that procedures were not followed or values properly recorded. Quality control measures can be linked to the quality assurance procedures. In the example given above for use of field blanks, spikes and duplicate samples, laboratories must provide evidence that their analysis of these samples meets acceptable statistical guidelines for accuracy and precision. Quality control can also simply involve careful analysis of a data set to determine whether it is internally consistent. 

Apart from the extraction and analytical methods, it is fundamental that the quality of analytical data is demonstrated by running quality controls (QC). De Vivo et al. (2004) recommend to validate analytical data by evaluating precision (which expresses the extent of reproducibility of analytical determinations) and accuracy (which expresses the degree of correctness of the data compared with true values) of results through the use of standard samples analysed together with the samples collected during the mapping activities. The accuracy and precision so determined should not exceed 15% for the analytical results to be considered acceptable. 

The precision and accuracy of the method was assessed by analyzing batches on three occasions (days). Each run included a duplicate set of calibration standards (CS) and a set of quality control samples (5 QC levels in 5 replicates). The following QC levels have been used 1, 3, 100, 800 2500 ng/mL in plasma and 0.25, 0.6, 25.2, 40 and 128 ng/mL in urine. The highest QC level was above the upper limit of quantification (ULQ). These samples were analyzed after 5-fold dilution in human plasma/urine prior to analysis in order to evaluate the possibility of diluting samples with concentrations above ULQ. 

Calibration of balances calibration of ultraviolet grating for wavelength accuracy exchange of lamps system suitability testing analysis of quality control samples and evaluation of results using control charts. 

Zhang et al. [43] developed and validated a stability indicating HPLC method for the determination of lornoxicam in pharmaceutical formulation. The isocratic procedure was performed in Shimadzu ODS (4.6 mm x 15 cm, 5 pm) column maintained at 25 °C. The mobile phase was degassed mixture of sodium acetate (0.05 mol/L, pH 5.8) and methanol (55 45). The flow rate was 1 ml/min and detection at 290 nm. Selectivity, specificity, linearity, precision, accuracy, and robustness were evaluated to validate the analytical method. Forced degradation studies were performed to provide an indication of the stability-indicating capacity. The stability indicating method for lornoxicam in the injectable dosage was developed and validated. The method can be considered for routine analysis and quality control of lornoxicam in injectable formulation. 

E572 Stella, P., Spagliardi, G., Lovagnini-Scher, C.A., Guagnellini, E. and Okely, C. (1989). Kodak Ektachem 700 analyzer precision and accuracy evaluation Actual data from laboratory quality control over one year. Biochim. Clin. 13, Suppl. I /8, 150, Abstr. A 24. 

FdPLC has contributed many successes in product development and in quality control for the pharmaceutical industry. The UV detector coupling with HPLC equipment is the most important analytical instrument for preformulation, QC/QA, and in-process control in pharmaceutical analysis. HPLC is a basic and reliable analytical tool for preformulation study because of the high-resolution capacity, accuracy, and reproducibility of the equipment. Its primary function includes search for and detection of impurities in drug substances, as well as stability evaluation of dosage forms in terms of detection and quantitation of degradation products. 

Since important decisions affecting the health and welfare of humanity must be made on the basis of analytical results, considerable effort must be directed toward assuring greater confidence in the reliability of the output of analytical laboratories. The Commission of the European Communities, after performing a study to determine the comparability of chemical analyses for drinking water quality, concluded that analytical quality control must be required as a routine component of analytical work. They state ( ), "Only the combination of intralaboratory controls of precision and accuracy complemented by interlaboratory intercomparison tests can lead to a significant evaluation and improvement of analytical results."... 

As an analytical approach to residue analysis, immunoassay methods are not well characterized, and no validation protocols have been established. The Association of Official Analytical Chemists, whose primary purpose is validation of analytical methods, established a Task Force on Test Kits and Proprietary Methods (2), which has addressed some of the issues relating to immunoassay methods. The International Union of Pure and Applied Chemistry s Commission on Food Chemistry has established a Working Group on Immunochemical Methods, whose first project is to develop draft guidelines on criteria for evaluation, validation, and quality control for r o-immunoassay methods (10). Similar guidelines for EIAs will also be developed. These documents will assist in development and standardization of requirements for precision for both between-laboratories and within-laboratory andyses, accuracy, and ruggedness, and— for qualitative methods— false positive and false negative rates. 

CRMs are products of very high added value. Their production and certification are very costly and, therefore, these materials should not be used for routine quality control or external quality assurance (interlaboratory studies). In order to fulfil the needs related to these uses, noncertified RMs may be prepared, linking them to one or several CRMs as a means of evaluating the accuracy of the values assigned to the so-called secondary materials. This approach is straightforward in the case of calibrants (pure compovmds or calibrating solutions), but is more difficult in the case of matrix CRMs owing to the likely matrix differences. 

Quality control samples at three concentrations (low, middle, and high) around the expected range can be used to assess accuracy by two to five injections. The acceptance criteria estabhshed for the SST evaluation must balance the need to ensure adequate performance with the practical reahty of performing chemical analyses. This means that they must be sufficiently tight, but not so restrictive that acceptable systems fail to pass. Some examples of the acceptance criteria are summarized in Table 3. 

---