Unbiased Scanning Method and Data Banking Approach Using Ultra-High Performance Liquid Chromatography Coupled with High-Resolution Mass Spectrometry for Quantitative Comparison of Metabolite Exposure in Plasma across Species Analyzed at Different Dates.
Anal Chem
; 87(23): 11771-6, 2015 Dec 01.
Article
em En
| MEDLINE
| ID: mdl-26528960
ABSTRACT
An unbiased scanning methodology using ultra high-performance liquid chromatography coupled with high-resolution mass spectrometry was used to bank data and plasma samples for comparing the data generated at different dates. This method was applied to bank the data generated earlier in animal samples and then to compare the exposure to metabolites in animal versus human for safety assessment. With neither authentic standards nor prior knowledge of the identities and structures of metabolites, full scans for precursor ions and all ion fragments (AIF) were employed with a generic gradient LC method to analyze plasma samples at positive and negative polarity, respectively. In a total of 22 tested drugs and metabolites, 21 analytes were detected using this unbiased scanning method except that naproxen was not detected due to low sensitivity at negative polarity and interference at positive polarity; and 4'- or 5-hydroxy diclofenac was not separated by a generic UPLC method. Statistical analysis of the peak area ratios of the analytes versus the internal standard in five repetitive analyses over approximately 1 year demonstrated that the analysis variation was significantly different from sample instability. The confidence limits for comparing the exposure using peak area ratio of metabolites in animal plasma versus human plasma measured over approximately 1 year apart were comparable to the analysis undertaken side by side on the same days. These statistical analysis results showed it was feasible to compare data generated at different dates with neither authentic standards nor prior knowledge of the analytes.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Plasma
/
Bases de Dados Factuais
Limite:
Animals
/
Humans
Idioma:
En
Ano de publicação:
2015
Tipo de documento:
Article