Integrated database analysis

Cetuximab concentration data from the 19 studies were combined into a common PK database for an integrated PK analysis [16]. This analysis was performed for the following purposes ... 

Based on the integrated PK database analysis, CL values were estimated and are displayed in Fig. 14.6 as a function of the cetuximab serum concentrations. A concentration-dependent decrease in CL was observed in the integrated PK database analysis, similar to that observed in the non-compartmental analysis. 

Hu, Z., Barker, W. C. (2004). The iProClass integrated database for protein functional analysis. Comput. Biol. Chem. 28, 87-96. 

The final step, risk characterization, involves the integration and analysis of the existing database to provide a numerical estimate of the incidence of the adverse effect in a given population, assuming specific conditions of exposure. 

Table 4 Integrated Database Retrieval and Analysis Systems ...

When voids in needs, constraints, etc. are identified or needs are not properly addressed, requirements analysis and validation are repeated until a valid requirements basehne is generated. The validated reqnirements baseline is documented in the integrated database and is an input to funetional analysis. The tasks assoeiated with validation are identified in Figure 11. 

Once the estabhshed requirements baseline variations and conflicts are satisfactorily resolved, the requirements baseline is considered valid. This validated requiremraits baseline is thrai used as input to functional analysis (6.3) and documented in the integrated database. 

Because ICP spectra for many elements are so rich in lines, spectral interferences are always possible. To avoid this type of error requires knowledge of all of the components likely to be present in the sample and a careful study of the information in the reference works listed in note 16. The software for modern computerized instruments has powerful routines for wavelength and concentration calibration, spectral analysis, and deconvolution of overlapping lines. These features coupled with integrated databases of spectral lines make spotting and correcting for interferences an integral part of the analytical process. 

KBr) databases. Quantitative analysis by GC-FUR is complicated by many uncertainties associated with both the chromatography and spectroscopy [196]. Bulk property detectors (e.g. TCD, FID, etc.) can be used for quantitative analysis when mixture components are known, but provide little structural information for unknown mixture components. Both integrated absorbance and Gram-Schmidt vector methods have been used for the quantitative analysis of mixture components in GC-FTIR. 

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