Spiked sample evaluations

External standards also give the analyst the ability to conduct spiked sample evaluations to evaluate for any procedural biases. 

Moreover recovery studies on commercial spiked samples were developed in order to asses the no contribution of the matrix and evaluate the accuracy of the proposed procedure. 

Accuracy is the closeness in agreement between the accepted trne valne or a reference valne and the actual result obtained. Accuracy studies are usually evaluated by determining the recovery of a spiked sample of the analyte into the matrix of the sample to be analyzed. 

The analysis method was evaluated with four different benzidine-based dye formulations (Figure 1). The results of a repeatability study utilizing spiked samples are shown in Table III. Spiking levels were arbitrarily chosen but do reflect the lower limit of the method. 

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. 

Method validation is usually carried out in several steps (Fig. 8). First, the sensitivity and specificity of the assay are evaluated. Second, bias is estimated by comparison with reference methods using reference materials, analysis of samples of known composition or of spiked samples. Finally, the new method must be... 

The objective of improvement schemes is to study and validate each step of different analytical procedures applied by different laboratories in a collaborative manner. Such programmes usually involve groups of 20-50 laboratories. In the best case, each critical step of the procedure should be evaluated in an adapted exercise. The individual steps may be studied with a series of different materials in a stepwise manner. In principle the strategy consists of starting from the simplest matrix, e.g. pure solutions and/or mixtures of compounds in solution, for testing the performance of the detector. The analysis of more complex matrices (e.g. raw extract, purified extract) enables the separation and/or clean-up steps to be tested, whereas solid samples are used to test the entire procedure. Spiked samples can be analysed to evaluate the extraction procedure, within the limits of this evaluation (as commented in Section 2.3.1). Such an approach is actually similar to the steps that should be followed when developing and validating a new method in a laboratory. 

The diligent analyst would develop a robust method with rigorous matrix effect tests on multiple lots, including hemolyzed and lipidemic samples. An initial test would be a spike-recovery evaluation on at least six individual lots. Samples should be spiked at or near the LLOQ, and at a high level near the ULOQ. If matrix interference were indicated by unacceptable relative error (RE) percentage in certain lots, the spiked sample of the unacceptable lots should be diluted with the standard calibrator matrix to estimate the minimum dilution requirement (MDR) at and above which the spike-recovery is acceptable. The spike-recovery test should then be repeated with the test samples diluted at the MDR. Note that this approach will increase the LLOQ for a less sensitive assay. If sensitivity is an issue, then other venues will be required to address the matrix effect problem. For example, the method can be modified to include sample clean-up, antibodies and/or assay conditions may be changed, or the study purpose may be tolerable to acknowledge that the method may not be selective for a few patients (whose data may require special interpretation). 

The selection of an analytical technique and the development of procedures and operating conditions are only one part of the process for achieving reliable measurements. Among the first steps of the validation figure the assessment of the method precision this parameter must be assessed between analysts and days. Appropriate precision, although necessary for reliable work, is not sufficient to guarantee accurate results Evaluation of sample matrix effect, development, and analysis of spiked samples, analysis of Certified Reference Materials (CRM) of similar composition for which the Pb concentration has been established by other laboratories and comparison of results between laboratories (proficiency testing) are equally important [13]. 

In practice, the absolute %ME has limited relevance. In bioanalytical practice, it is more important to demonstrate the absence of relative matrix effects, i.e., between different sources of the biofiuid [70]. Alternatively, relative matrix effects may be evaluated by a comparison of precision expressed as %RSD in repetitive injection of standards and post-extraction spiked samples. If significant differences in the %RSD exist, a relative matrix effect is present between the different sample batches. 

Becker et al. [94] evaluated matrix effects in the multiresidue analysis of 15 penicillins and cephalosporins in bovine muscle and kidney tissue and in milk. Comparison of the responses between standard solution and post-extraction spiked samples for all compounds in all three matrices showed different behaviour of different analytes and in different matrices. For one target compound, cefquinone, the standard addition method had to be apphed to get sufficiently accurate and precise results. 

Responses are obtained from replicate analyses (n = 4) of a field blank and the field blank spiked to contain a level of analyte that is close to the LOQ. The means of the obtained responses are tested statistically (with the f-test) to determine whether they are statistically different. If the difference is significant, the variability of the response in the spiked sample is evaluated by taking the ratio of its mean response to the response standard deviation. If the ratio is greater than or equal to 3, then the spiked concentration is taken as the LOQ. 

Where the method scope covers a range of sample matrices and/or analyte concentrations, an additional uncertainty term Rs is required to take account of differences in the recovery of a particular sample type, compared to the material used to estimate Rm. This can be evaluated by analysing a representative range of spiked samples, covering typical matrices and analyte concentrations, in replicate. The mean recovery for each sample type is calculated. Rs is normally assumed to be equal to 1. However, there will be an uncertainty associated with this assumption, which appears in the spread of mean recoveries observed for the different spiked samples. The uncertainty, u(Rs), is therefore taken as the standard deviation of the mean recoveries for each sample type. 

We have applied this protocol to the evaluation of the measurement uncertainty for a method for the determination of three markers (Cl solvent red 24, Cl solvent yellow 124 and quinizarin (1,4-dihydroxyanthra-quinone)) in road fuel. The method requires the extraction of the markers from the sample matrix by solid phase extraction, followed by quantification by HPLC with diode array detection. The uncertainty evaluation involved four experimental studies which were also required as part of the method validation. The studies were precision, trueness (evaluated via the analysis of spiked samples) and ruggedness tests of the extraction and HPLC stages. The experiments and uncertainty calculations are described in detail in Part 2. A summary of the uncertainty budget for the method is presented in Fig. 3. 

A fourth experiment would be an evaluation of precision and recovery at one to four concentration levels (n — 6 to 24 plus a recovery standard), plus recovery of an internal standard (n — 3 plus recovery standard). Therefore, as a minimal method development exercise, 60—70 spiked samples would be prepared and extracted within 1 day. The experiments need to be performed sequentially because the results from each will impact how subsequent experiments are designed. Selectivity is assessed through the course of the method development. The analytical chemist with access to API LC/MS/MS will spend less time on solid-phase extraction selectivity development. 

Validation of biological sample analysis methods is critical to the evaluation of the final data. A description of the validation procedure utilized by the NTP is provided here. The method needs to demonstrate the appropriate specificity, precision, absolute recovery, measurement limits, and relative error. An evaluation of the blank biological sample matrix contribution to responses seen in spiked samples also needs to be determined. 

The improvement schemes, usually involving a group of 20 to 50 laboratories, may start with a simple exercise, e.g. by distributing solutions or pure substances. This enables to evaluate the methods of final detection and to possibly optimise them. More complex samples, e.g. complex mixtures of compounds including interferents or extracts, are therefore analysed and the pretreatment/separation steps are assessed at this stage, the performance of the method is re-evaluated and the procedure may be fully reconsidered if necessary. An intermediate step can be the analysis of a spiked sample, which is followed by real samples. The outcome of the different exercises is discussed... 

Many experiments on the recoverability, persistence, and toxicity of xenobiotics have used spiked samples and therefore do not take into account the cardinal issue of aging after deposition that has been discussed in Chapter 3, Section 3.2.3 and that should be critically evaluated. Some examples are given as illustrative. 

Nonspecific nonspecificity results from interference of matrix components that are structurally unrelated to the analyte of interest. Examples of such interfering matrix components would include serum proteins, lipids, heterophilic antibodies, rheumatoid factor, proteases, and so on. Nonspecific nonspecificity is often referred to as matrix effect. Figure 4.3 depicts the impact of matrix on the assay performance. Matrix interference is one of the chief reasons that LB As often require more method development and validation prior to switching from one species matrix to another or even within the same species. In addition, we recommend during clinical study support that matrix from the relevant disease populations be tested for matrix effects as soon as that matrix becomes available. Matrix effects should be evaluated by comparing the concentration response relationship of both spiked and unspiked samples of the biological matrix (recommendation is 10 or more lots of individual sources) to a comparable buffer solution. It is recommended that the spiked sample... 

The details of the assessment of stability data are under intense discussion within the scientific community. A majority of laboratories evaluate data with acceptance criteria relative to the nominal concentration of the spiked sample. The rationale for this is that it is not feasible to introduce more stringent criteria for stability evaluations than that of the assay acceptance criterion. Another common approach is to compare data against a baseline concentration (or day zero concentration) of a bulk preparation of stability samples established by repeated analysis, either during the accuracy and precision evaluations, or by other means. This evaluation then eliminates any systematic errors that may have occurred in the preparation of the stability samples. A more statistically acceptable method of stability data evaluations would be to use confidence intervals or perform trend analysis on the data [24]. In this case, when the observed concentration or response of the stability sample is beyond the lower confidence interval (as set a priori), the data indicate a lack of analyte stability under the conditions evaluated. 

Evaluation of parallelism for ligand-binding PK assays is very similar to that for biomarker PD assays since most PK assays that employ commercial kit methods are likely to be for endogenous compounds. This describes the dilution of incurred samples rather than dilution of spiked samples. The dilution of spiked samples is termed dilution linearity [3]. 

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