Qualidade analítica baseada no projeto como ferramenta de desenvolvimento de métodos em cromatografia líquida de ultra eficiência
The pharmaceutical industry and analytical laboratories around the world have focused on quality, safety and efficacy of their products. Processes used to minimize risks, such as Quality by Design (QbD), which recently has been attributed to the development of analytical methods, especially chrom...
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Formato: | doctoralThesis |
Idioma: | por |
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Brasil
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Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/21438 |
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Resumo: | The pharmaceutical industry and analytical laboratories around the world have focused
on quality, safety and efficacy of their products. Processes used to minimize risks, such as
Quality by Design (QbD), which recently has been attributed to the development of analytical
methods, especially chromatographic methods. The Analytical Quality by Design (aQbD)
uses planning tools experiments, risk analysis and continuous monitoring. For this, it makes
use of simulation software, statistical tools and chemometrics.
It is known that chromatographic methods are well consolidated and required by the
regulatory agencies. It has been applied in various determinations in the pharmaceutical field,
such as identification and quantification of drugs, metabolites, degradation products and
impurities. The aim of this study was to use aQbD tools for the development of methods for
ultra high performance liquid chromatography (UHPLC). Four methods were developed,
namely: simultaneous quantification of dexamethasone acetate and clotrimazole in semisolid
dosage forms, via HPLC to UHPLC method transfer (Chapter 1); simultaneous determination
of corticosteroids and preservatives in solid core column with particle size of 1.3 μm by using
simulation software (Chapter 2); betamethasone valerate quantification in samples of cream,
gel, lotion and ointment after method development by full factorial design 33 (Chapter 3); and
simultaneous determination of corticosteroids after retention factor prediction model by
QSRR (Chapter 4).
The results showed that despite the need for optimization by the analyst, the use of
aQbD tools such as statistical design or use of software, the aQbD is promising in the
development of chromatographic methods of ultra efficiency, since they were able to promote
time savings, lower costs and risks. The tests showed satisfactory results in terms of analysis
speed and decrease of solvent consumption. |
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