Method in-house

Use of Validated Methods In-Home Versus Interlaboratory Validation Wherever possible or practically achievable, a laboratory should use methods which have been fully validated through a collaborative trial, also called interlaboratory study or method performance study. Validation in collaborative studies is required for any new analytical method before it can be published as a standard method (see below). However, single-laboratory validation is a valuable source of data usable to demonstrate the fitness for purpose of an analytical method. In-house validation is of particular interest in cases where it is inconvenient or impossible for a laboratory to enter into or to organize itself a collaborative study [4,5]. 

On the one hand, even if an in-house vahdated method shows good performance and reliable accuracy, such a method cannot be adopted as a standard method. In-house validated methods need to be compared between at least eight laboratories in a collaborative trial. On the other hand, a collaborative study should not be conducted with an unoptimized method [58]. Interlaboratory studies are restricted to precision and trueness while other important performance characteristics such as specificity and LOD are not addressed [105]. For these reasons, single-laboratory validation and interlaboratory validation studies do not exclude each other but must be seen as two necessary and complementary stages in a process, presented in Figure... 

In addition to property value assignment, based on traceable methods, in -house RMs should be stable and homogeneous, at an appropriate level of uncertainty, and stored appropriately... 

If the laboratory develops the validation method in-house, there always needs to be some sample to be used for this purpose a sample that best mimics routine samples is the most suitable. The usual practice is that a routine sample is used for this purpose as knowledge of the true value is not a critical issue at this stage. Next, the trueness of a method is usually determined by analyzing an appropriate CRM and/or participating in an ILC, one with an externally defined reference value.10... 

The use of color graphics is also an effective means for displaying chemical stmctures. This method is far better than typesetting the three-dimensional architecture of complex multimolecule assembly (112). For developing in-house CAD software programs, the three-dimensional, sohd-modeling capabiUties of SdverScreen can also be utilized either in monochrome or color for constmction of such stmctures (113). 

If in-house, personnel are required to provide a flare system piping layout, many good literature articles are available. Reference 2 has simplified the procedure by allowing the calculations to begin with the outlet (atmospheric pressure) and work back towards the source thus overcoming tedious trial and eiTor required by methods that require beginning at the source. 

Statistical Methods for Nonelectronic Reliability, Reliability Specifications, Special Application Methods for Reliability Prediction Part Failure Characteristics, and Reliability Demonstration Tests. Data is located in section 5.0 on Part Failure Characteristics. This section describes the results of the statistical analyses of failure data from more than 250 distinct nonelectronic parts collected from recent commercial and military projects. This data was collected in-house (from operations and maintenance reports) and from industry wide sources. Tables, alphabetized by part class/ part type, are presented for easy reference to part failure rates assuminng that the part lives are exponentially distributed (as in previous editions of this notebook, the majority of data available included total operating time, and total number of failures only). For parts for which the actual life times for each part under test were included in the database, further tables are presented which describe the results of testing the fit of the exponential and Weibull distributions. 

The similarity matrices are constructed by one in-house program developed inside CHIRBASE using the application development kit of ISIS. They contain the similarity coefficients as expressed by the Tanimoto method. In ISIS, the Tanimoto coefficients are calculated from a set of binary descriptors or molecular keys coding the structural fragments of the molecules. 

It also contains heat loss calculation methods. This Standard should be the basis for any specification drawn up by a company that does not have its own in-house insulation standards manual. 

Considering the failure of available log D methods to predict in-house data and taking into account that such data are usually generated just for a few fixed pH values, a number of companies started to elaborate in-house methods for log D prediction at fixed pH. Up to date several companies have reported development of such methods. For example, Cerep has developed methods to predict log D at pH 7.4 and 6.5 included in their Bio Print package [107], but details of their method are not pubhshed. HQSAR Tripos descriptors were used by Bayer to develop log D models at pH 2.3 and 7.5 using 70000 (qi =0.76, STD =0.60) and 7000 (qi =0.83, STD =0.67) compounds, respectively [108] however, again, no details of the approach were provided. 

A low accuracy of models for prediction of log D at any pH would not encourage the use of these models for practical applications in industry. Thus, it is likely that the methods for log D prediction at fixed pH that are developed in house by pharmaceutical companies will dominate in industry. However, log D measurements... 

A review is presented here of certification approaches, followed by several of the major agencies and individual developers of RMs for chemical composition, addressing some of the many associated scientific aspects that significantly impinge on the conduct and outcome of the analytical characterization exercises. These include definition of analytical methods selection of analytical methodologies, analysts and laboratories in-house characterization and cooperative inter-laboratory characterization. 

Even if most examples and procedures presented apply to in-house validation, the procedure does not distinguish between validations conducted in a single laboratory and those carried out within inter-laboratory method performance studies. A preference for inter-laboratory studies can be concluded from the statement that laboratories should always give priority to methods which have been tested in method performance studies. Within the procedure a profound overview of different categories of analytical methods according to the available documentation and previous external validation is given. For example, if a method is externally validated in a method performance study, it should be tested for trueness and precision only. On the other hand, a full validation is recommended for those methods which are published in the scientific literature without complete presentation of essential performance characteristics (Table 9). 

These requirements have special implications with regard to immunoassay methods. Eirst, the lack of commercial availability of reagents precludes preparing antibody-coated tubes or plates on-site, which may require knowledge of special skills. Commercial availability also ensures the analyst access to a reproducibly manufactured product. Therefore, the method must be based on an immunoassay that is a commercial product. Method developers may choose to introduce an in-house assay to the marketplace by partnering with a manufacturer, although this approach is costly and time-consuming. 

The values quoted above are for FYM from overwintered cattle, but the method of housing influences nutrient loss. With cattle in covered yards sufficient bedding must be used to absorb the liquid manure and there is little or no drainage the dung is kept well compressed by the animals and fermentation is reduced to a minimum. Under such conditions very little loss takes place. 

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