Quantitation robustness

The method can be robust concerning its quantitative aspect, but non-robust regarding one or more qualitative aspects, i.e., significant effects are found on responses, such as, resolution. Then SST limits can be mathematically or experimentally derived, based on the results of the robustness test. These SST limits correspond to the interval in which a qualitative response is allowed to vary, to still obtain a quantitatively robust method. 

The most-common methods employed are based on liquid chromatography, due to the high resolution, excellent reproducibility, effective quantitation, robustness, and ease of use. The resolution and speed of analysis continues to improve, with the availability of columns packed with sub-2 micron particles. 

Dispersion Characteristics The chief characteristics of gas-in-liquid dispersions, like those of hquid-in-gas suspensions, are heterogeneity and instabihty. The composition and structure of an unstable dispersion must be obsei ved in the dynamic situation by looking at the mixture, with or without the aid of optical devices, or by photographing it, preferably in nominal steady state photographs usually are required for quantitative treatment. Stable foams may be examined after the fact of their creation if they are sufficiently robust or if an immobilizing technique such as freezing is employed [Chang et al., Ind. Eng Chem., 48, 2035 (1956)]. 

PLS metliod applied to speetral data provides exeellent quantitative analytieal results. It offers more aeeurate and robust predietion eompared with the results obtained by LR method. Therefore, the Ca(OH) determination by FTIR using a PLS model ealibration has demonstrated to be an adequate tool, despite the disadvantages of quantitative analysis using FTIR speetroseopie teehnique. 

Equipment technology and processing software for FTIR are very robust and provide a high degree of reliability. Concerns arise for only the most demanding applications. For quantitative work on an isolated feature in the spectrum, the rule of thumb is that the spectrometer resolution be one-tenth the width of the band. FTIR instruments routinely meet that requirement for solids. 

ADMET is quite possibly the most flexible transition-metal-catalyzed polymerization route known to date. With the introduction of new, functionality-tolerant robust catalysts, the primary limitation of this chemistry involves the synthesis and cost of the diene monomer that is used. ADMET gives the chemist a powerful tool for the synthesis of polymers not easily accessible via other means, and in this chapter, we designate the key elements of ADMET. We detail the synthetic techniques required to perform this reaction and discuss the wide range of properties observed from the variety of polymers that can be synthesized. For example, branched and functionalized polymers produced by this route provide excellent models (after quantitative hydrogenation) for the study of many large-volume commercial copolymers, and the synthesis of reactive carbosilane polymers provides a flexible route to solvent-resistant elastomers with variable properties. Telechelic oligomers can also be made which offer an excellent means for polymer modification or incorporation into block copolymers. All of these examples illustrate the versatility of ADMET. 

Dynamic simulation with discrete-time events and constraints. In an effort to go beyond the integer (logical) states of process variables and include quantitative descriptions of temporal profiles of process variables one must develop robust numerical algorithms for the simulation of dynamic systems in the presence of discrete-time events. Research in this area is presently in full bloom and the results would significantly expand the capabilities of the approaches, discussed in this chapter. 

The importance of the degree of esterification (%DE) to the gelation properties of pectins makes it desirable to obtain a fast and robust method to determine (predict) the %DE in pectin powders. Vibrational spectroscopy is a good candidate for the development of such fast methods as spectrometers and quantitative software algorithms (chemometric methods) becomes more reliable and sophisticated. Present poster is a preliminary report on the quantitative performance of different instrumentations, spectral regions, sampling techniques and software algorithms developed within the area of chemometrics. 

Nevertheless, DFT has been shown over the past two decades to be a fairly robust theory that can be implemented with high efficiency which almost always surpasses HF theory in accuracy. Very many chemical and spectroscopic problems have been successfully investigated with DFT. Many trends in experimental data can be successfully explained in a qualitative and often also quantitative way and therefore much insight arises from analyzing DFT results. Due to its favorable price/performance ratio, it dominates present day computational chemistry and it has dominated theoretical solid state physics for a long time even before DFT conquered chemistry. However, there are also known failures of DFT and in particular in spectroscopic applications one should be careful with putting unlimited trust in the results of DFT calculations. 

Verification implies that the laboratory investigates trueness and precision in particular. Elements which should be included in a full validation of an analytical method are specificity, calibration curve, precision between laboratories and/or precision within laboratories, trueness, measuring range, LOD, LOQ, robustness and sensitivity. The numbers of analyses required by the NMKL standard and the criteria for the adoption of quantitative methods are summarized in Table 10. 

It is often difficult to define where sample extraction ends and cleanup procedures begin. Sample extracts may be injected directly into a gas or liquid chromatograph in certain cases, but this will be dependent on the analyte, sample matrix, injection, separation and detection system, and the limit of determination (LOD) which is required. It is also more likely that matrix-matched calibration standards will be needed in order to obtain robust quantitative data if no cleanup steps are employed. 

The development of a robust analytical method is a complex issue. The residue analyst has available a vast array of techniques to assist in this task, but there are a number of basic rules that should be followed to produce a reliable method. The intention of this article is to provide the analyst with ideas from which a method can be constructed by considering each major component of the analytical method (sample preparation, extraction, sample cleanup, and the determinative step), and to suggest modern techniques that can be used to develop an effective and efficient overall approach. The latter portion emphasizes mass spectrometry (MS) since the current trend for pesticide residue methods is leading to MS becoming the method of choice for simultaneous quantitation and confirmation. This article also serves to update previous publications on similar topics by the authors. ... 

While over the past ten years, our ability to measure U-series disequilibria and interpret this data has improved significantly it is important to note that many questions still remain. In particular, because of uncertainties in the partition coefficients, fully quantitative constraints can only be obtained when more experimental data, as a function of P and T as well as source composition, become available. Furthermore, the robustness of the various melting models that are used to interpret the data needs to be established and 2D and 3D models need to be developed. However, full testing of these models will only be possible when more comprehensive data sets including all the geochemical parameters are available for more locations and settings. 

The centric scan, one-dimensional, DHK SPRITE measurement was used to study the ingress of lithium. This measurement technique was selected due to the low absolute sensitivity of 7Li (27% of [36]), the small amounts that are present and the short signal lifetimes (bulk Tx of 10 ms and T2 of 120 ps). In addition to the robust, quantitative nature of this technique, lithium is a quadrupolar nucleus and interpretation of the image intensity is more complex than spin % nuclei. Once again Eq. (3.4.2) is quantitatively correct for even quadrupolar nuclei due to the fact the longitudinal steady state does not influence the image intensity. 

FPD (PFPD) Relatively inexpensive High sensitivity Relatively robust Not suited for quantitation in complex mixtures Destructive [31,40,41]... 

Simple, robust quantitative algorithms (peak height/area of isolated bands) standards usually needed... 

The use of the in vivo labeling methods described above is limited by the fact that the sample must be grown in the presence of the labeling isotopes. In many cases, it is not feasible to perform in vivo metabolic labeling. For example, for human clinical samples it is not possible to perform in vivo labeling and yet it is highly desirable to obtain accurate quantitative information on protein expression levels within these samples. Therefore, robust methods are needed for quantitation of protein levels in the absence of in vivo labeling with isotopes. 

For PyMS to be used for (1) routine identification of microorganisms and (2) in combination with ANNs for quantitative microbiological applications, new spectra must be comparable with those previously collected and held in a data base.127 Recent work within our laboratory has demonstrated that this problem may be overcome by the use of ANNs to correct for instrumental drift. By calibrating with standards common to both data sets, ANN models created using previously collected data gave accurate estimates of determi-nand concentrations, or bacterial identities, from newly acquired spectra.127 In this approach calibration samples were included in each of the two runs, and ANNs were set up in which the inputs were the 150 new calibration masses while the outputs were the 150 old calibration masses. These associative nets could then by used to transform data acquired on that one day to data acquired at an earlier data. For the first time PyMS was used to acquire spectra that were comparable with those previously collected and held in a database. In a further study this neural network transformation procedure was extended to allow comparison between spectra, previously collected on one machine, with spectra later collected on a different machine 129 thus calibration transfer by ANNs was affected. Wilkes and colleagues130 have also used this strategy to compensate for differences in culture conditions to construct robust microbial mass spectral databases. 

Analytical methods, particularly those used by accredited laboratories, have to be validated according to official rules and regulations to characterize objectively their reliability in any special field of application (Wegscheider [1996] EURACHEM/WELAC [1993]). Validation has to control the performance characteristics of analytical procedures (see Chap. 7) such as accuracy, precision, sensitivity, selectivity, specificity, robustness, ruggedness, and limit values (e.g., limit of detection, limit of quantitation). 

Typical performance characteristics that should be considered in the validation are precision, accuracy, limit of detection, limit of quantitation, selectivity, range, linearity, robustness, ruggedness... 

---