Desirability Function in analytical method development for determination of glitazones and metabolites employing HF-LPME

Autor(es)

Matheus Santiago da Silva ^[1] ; Greyce Kelly Steinhorst Calixto ^[2] ; Débora Cristina de Oliveira ^[3] ; Felipe Rebello Lourenço ^[4] ; Leandro Augusto Calixto ^[5]

Afiliação do(s) autor(es)

^[1] Federal University of São Paulo. Department of Pharmaceutical Sciences - Brasil

^[2] University of São Paulo. Faculty of Pharmaceutical Sciences of Ribeirão Preto. Department of Pharmaceutical Sciences - Brasil

^[3] Federal University of São Paulo. Department of Pharmaceutical Sciences - Brasil

^[4] University of São Paulo. Faculty of Pharmaceutical Sciences. Department of Pharmacy - Brasil

^[5] Federal University of São Paulo. Department of Pharmaceutical Sciences - Brasil

• Tipo de documento: Artigo Científico
• Fonte: Brazilian Journal of Pharmaceutical Sciences; v. 58, 2022-05-23.

Resumo

Abstract Thiazolidinedione, often shortened to TZD or glitazone, helps lower insulin resistance, which is the underlying problem for many people with type 2 diabetes. The two most known glitazones are pioglitazone (PGZ), with the brand name medicine Actos®, and rosiglitazone (RSG), which is Avandia®. This study presented a multivariate optimization in the microextraction procedure employing Fractional Factorial Design (FFD) combined with Desirability Function (DF) to determine TZD and metabolites in biological samples. Microextraction requires several parameters to be optimized; however, most of them still use univariate optimization. Finding optimum conditions by simple response is relatively simple, but the problems, in case of microextractions, are often more complex when it has more responses. For example, changing one factor that promotes one response may suppress the effect of the others. Thus, this multivariate optimization was applied for two bioanalytical methods for determination of TZD and metabolites, one by HPLC and other by CE, both using Hollow Fiber Liquid-Phase Microextraction (HF-LPME). The results establish the optimal values and elucidate how the factors that affect HF-LPME procedure perform in extraction efficiency for TZDs. Additionally, this study demonstrates that DF can be an important tool to optimize microextraction procedures. (AU)

• Processo FAPESP: 16/25256-6 - Determinação de metais pesados em produtos tradicionais fitoterápicos por técnicas analíticas alternativas empregando princípios da química verde
• Beneficiário: Leandro Augusto Calixto
• Modalidade de apoio: Auxílio à Pesquisa - Regular