Databases degradant identification

The strategy for impurity and degradant identification described by Rourick et al. subjects lead candidates to various development conditions followed by LC/MS and LC/MS/MS analysis protocols. A structure database is constructed from the corresponding results and is used to reveal unstable regions within the drug structure as well as to ascertain which candidate or homologous series of drug candidates may be the most favorable for further development. 

Obviously, use of such databases often fails in case of interaction between additives. As an example we mention additive/antistat interaction in PP, as observed by Dieckmann et al. [166], In this case analysis and performance data demonstrate chemical interaction between glycerol esters and acid neutralisers. This phenomenon is pronounced when the additive is a strong base, like synthetic hydrotalcite, or a metal carboxylate. Similar problems may arise after ageing of a polymer. A common request in a technical support analytical laboratory is to analyse the additives in a sample that has prematurely failed in an exposure test, when at best an unexposed control sample is available. Under some circumstances, heat or light exposure may have transformed the additive into other products. Reaction product identification then usually requires a general library of their spectroscopic or mass spectrometric profiles. For example, Bell et al. [167] have focused attention on the degradation of light stabilisers and antioxidants... 

Once a database is established, it is made available to other laboratories through the company s secured intranet, so that the information therein can be updated, retrieved and reviewed. The resulting structural library can be referenced throughout the lifetime of the drug for rapid identification of impurities, degradants, and metabolites. 

In the past, sequencing of peptides was accomplished using the Edman degradation procedure (see Section 8.2) [3]. Currently, this objective is more often accomplished by interpretation of a peptide s product-ion spectrum. As discussed above, one easy way is to submit the mass spectral data to the database search. Often, this search fails to provide an unequivocal identification of a peptide or protein. Therefore, one needs to resort to a manual interpretation of the mass spectrum. This procedure, known as de novo peptide sequencing, requires a detailed, complete, and... 

Content-related fields are information type , use of chemicals , number of chemicals , and descriptor . A few data-sources specialize in types of information, e.g., ecotoxicity or identification parameters. On the other hand, there exist special databases for specific uses of chemical substances, e.g., pesticide databases. As there are databases which contain thousands of chemicals and others which only describe hundreds, the field number of chemicals is given. For a comprehensive description of the content of a source, a thesaurus containing key words which are of interest to the problem of environmental chemicals, has been developed. These key words can be found in the descriptor field. The thesaurus, which takes into account most of the parameters required by the German Chemicals Act for registering chemical substances, treats not only environmental but also health and worlqrlace exposure aspects. The thesaurus encompasses, for example, the identification of chemicals, data on detection of chemicals in the environment, use of chemicals, economic data, physical-chemical properties, degradation and accumulation data, ecotoxicity, eff ects on wildlife, toxicity effects on mammals, effects on human organisms, information in relation to the workplace, etc. 

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