Validated Sample Analysis

The previous sections in this chapter addressed the process of validating the method and documenting the results in a final validation report. When reviewing the analytical data for the study samples the validation report and associated tables and supporting documentation must be carefully reviewed for accuracy and scientific content, to ensure that the necessary experiments have been run and that the data supports the original uncertainty tolerances (Section 9.3). In addition to the validation report, the final method must be reviewed and approved for sample analysis. Specific acceptance criteria that will be used during sample analysis should be documented in the approved method or equivalent SOP. 

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A validation plan or protocol (Section 10.3.1) that specifies the experiments to be run on each day should be prepared prior to validation sample analysis. This document should specify how the validation should be conducted and, for validations that are conducted over multiple days, the plan should specify what experiments should be run on each day. Prior to the initiation of work, the protocol should be reviewed. Any questions or discrepancies should be resolved and, if necessary, an amendment should be prepared to resolve these issues. 

Suppose we have two methods of preparing some product and we wish to see which treatment is best. When there are only two treatments, then the sampling analysis discussed in the section Two-Population Test of Hypothesis for Means can be used to deduce if the means of the two treatments differ significantly. When there are more treatments, the analysis is more detailed. Suppose the experimental results are arranged as shown in the table several measurements for each treatment. The goal is to see if the treatments differ significantly from each other that is, whether their means are different when the samples have the same variance. The hypothesis is that the treatments are all the same, and the null hypothesis is that they are different. The statistical validity of the hypothesis is determined by an analysis of variance. 

The data in the training set are used to derive the calibration which we use on the spectra of unknown samples (i.e. samples of unknown composition) to predict the concentrations in those samples. In order for the calibration to be valid, the data in the training set which is used to find the calibration must meet certain requirements. Basically, the training set must contain data which, as a group, are representative, in all ways, of the unknown samples on which the analysis will be used. A statistician would express this requirement by saying, "The training set must be a statistically valid sample of the population... 

The legalistic notion that only validated processes are to be used assumes that the chain of events from raw materials to analysis of the final material can be validated in globo, something that is patently impossible with the given number of adjustable parameters, not to mention unforeseen glitches. Doing the validations in bits and pieces (modules process, sampling, analysis, data evaluation, etc.) certainly helps, but does not cover the... 

Alternatively, during the course of method validation and sample analysis, control samples fortified at the ELOQ (determined by one of the methods described above) are extracted and analyzed. The standard deviation of these fortified control samples ( LLMv) can also be used to calculate the MDL and the MQL for the method. In the latter case, llmv would replace. eloq in equation (14). 

The third and last phase of the trial is the analysis of the validation samples. All data collected are reported. No results are discarded unless a determinate error can be identified. Any request to repeat the assay of a sample should be approved by... 

Once soil samples have been analyzed and it is certain that the corresponding results reflect the proper depths and time intervals, the selection of a method to calculate dissipation times may begin. Many equations and approaches have been used to help describe dissipation kinetics of organic compounds in soil. Selection of the equation or model is important, but it is equally important to be sure that the selected model is appropriate for the dataset that is being described. To determine if the selected model properly described the data, it is necessary to examine the statistical assumptions for valid regression analysis. 

On-line SFE-SFC method development for validated quantitative analysis of PP/(Irganox 1010/1076, Tinuvin 327) has been reported [93]. SFE conditions required optimisation of extraction time and pressure, matrix type (particle or film) and matrix parameters (particle size, film thickness, sample weight). About 30% of extracts were lost during collection. Very poor recoveries (20-25 %) were reported from ground samples (particle size 100 p,m dependent recoveries of 45-70% for 30-p.m-thick films. Biicherl... 

In each of the aforementioned studies, qualitative IR spectroscopy was used. It is important to realize that IR is also quantitative in nature, and several quantitative IR assays for polymorphism have appeared in the literature. Sulfamethoxazole [35] exists in at least two polymorphic forms, which have been fully characterized. Distinctly different diffuse reflectance mid-IR spectra exist, permitting quantitation of one form within the other. When working with the diffuse reflectance IR technique, two critical factors must be kept in mind when developing a quantitative assay (1) the production of homogeneous calibration and validation samples, and (2) consistent particle size for all components, including subsequent samples for analysis. During the assay development for... 

Sampling Interval To be able to perform valid toxicokinetic analysis, it is not only necessary to properly collect samples of appropriate biological fluids, but also to collect a sufficient number of samples at the current intervals. Both of these variables are determined by the nature of the answers sought. Useful parameters in toxico-kinetic studies are Cmax, which is the peak plasma test compound concentration Tmax, which is the time at which the peak plasma test compound concentration occurs, Cmin, which is the plasma test compound concentration immediately before the next dose is administered AUC, which is the area under the plasma test compound concentration-time curve during a dosage interval, and t which is the half-life for the decline of test compound concentrations in plasma. The samples required to obtain these parameters are shown in Table 18.12. Cmin requires one blood sample immediately before a dose is given and provides information on accumulation. If there is no accumulation in plasma, the test compound may not be detected in this sample. 

Sampling procedures are extremely important in the analysis of soils, sediments and sludges. It is essential to ensure that the composition of the portion of the sample being analysed is representative of the material being analysed. This fact is even more evident when it is conceded that the size of the portion of sample being analysed is in many modern methods of analysis extremely small. It is therefore essential to ensure before the analysis is commenced that correct statistically validated sampling procedures are used to ensure as far as is possible that the portion of the sample being analysed is representative of the bulk of material from which the sample was taken. 

The company has in place numerous checks and balances to prevent human error quality assurance (QA)-driven processes require validation (secondary checks/rechecks) of operator actions, sampling/analysis, etc. 

From the PCA analysis, it was concluded that appropriate ranks for the TEA and MEK SI.MCA models are two and one, respectively. The next step is to construct SIMCA models and test their performance on validation samples. The ranks determined during the PCA analyses and the default settings for the class volume size for the models are used. 

Table I summarizes the sampling media used in the last three years of the study. Previously, we have developed validated sampling and analytical methods for many of the common organic solvents that could be collected on charcoal, desorbed with carbon disulfide, and analyzed by gas chromatography. These procedures are usually nearly identical with the NIOSH method P CAM 127. Likewise, methods for substances that give well-behaved particulates both in collection and analysis had been validated. The substances summarized in Table I represent a wide variety of problems in sampling and analysis. Consequently, many of the samplers were charged with unusual collection media.

As already mentioned, any multivariate analysis should include some validation, that is, formal testing, to extrapolate the model to new but similar data. This requires two separate steps in the computation of each model component calibration, which consists of finding the new components, and validation, which checks how well the computed components describe the new data. Each of these two steps needs its own set of samples calibration samples or training samples, and validation samples or test samples. Computation of spectroscopic data PCs is based solely on optic data. There is no explicit or formal relationship between PCs and the composition of the samples in the sets from which the spectra were measured. In addition, PCs are considered superior to the original spectral data produced directly by the NIR instrument. Since the first few PCs are stripped of noise, they represent the real variation of the spectra, presumably caused by physical or chemical phenomena. For these reasons PCs are considered as latent variables as opposed to the direct variables actually measured. 

Samples are to be taken during and/or after each critical manufacturing step. All control parameters for the manufacturing process have to be monitored and recorded. Each sample analysis will be performed in duplicate using validated or accepted pharmacopeia methods. The sample results will be used to confirm in-process and final product quality attributes as defined by the preestablished specifications. Conformance with specifications will justify the appropriateness of the critical parameters used during the process validation. 

The validation requirements are discussed as they apply to both the sample preparation and sample analysis aspects of a dissolution method. The focus of the discussion in this chapter is on the validation considerations that are unique to a dissolution method. Validation is the assessment of the performance of a defined test method. The result of any successful validation exercise is a comprehensive set of data that will support the suitability of the test method for its intended use. To this end, execution of a validation exercise without a clearly defined plan can lead to many difficulties, including an incomplete or flawed set of validation data. Planning for the validation exercise must include the following determination of what performance characteristics to assess (i.e., strategy), how to assess each characteristic (i.e., experimental), and what minimum standard of performance is expected (i.e., criteria). The preparation of a validation protocol is highly recommended to clearly define the experiments and associated criteria. Validation of a test method must include experiments to assess both the sample preparation (i.e., sample dissolution) and the sample analysis. ICH Q2A [1] provides guidance for the validation characteristics of the dissolution test and is summarized in Table 4.1. 

Although there are various stages in the validation of a bioanalytical procedure, the process by which a specific assay is developed, validated, and used in routine sample analysis can be divided into four main steps ... 

Application of validated method to routine sample analysis... 

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