Dataset Information

UHPLC-QqQ-MS/MS method development and validation with statistical analysis: Determination of raspberry ketone metabolites in mice plasma and brain.

ABSTRACT: Raspberry ketone (RK) (4-(4-hydroxyphenyl)-2-butanone) is the major compound responsible for the characteristic aroma of red raspberries, and has long been used commercially as a flavoring agent and recently as a weight loss supplement. A targeted UHPLC-QqQ-MS/MS method was developed and validated for analysis of RK and 25 associated metabolites in mouse plasma and brain. Dispersion and projection analysis and central composite design were used for method optimization. Random effect analysis of variance was applied for validation inference and variation partition. Within this framework, repeatability, a broader sense of precision, was calculated as fraction of accuracy variance, reflecting instrumental imprecision, compound degradation and carry-over effects. Multivariate correlation analysis and principle component analysis were conducted, revealing underlying association among the manifold of method traits. R programming was engaged in streamlined statistical analysis and data visualization. Two particular phenomena, the analytes' background existence in the enzyme solution used for phase II metabolites deconjugation, and the noted lability of analytes in pure solvent at 4 ℃ vs. elevated stability in biomatrices, were found critical to method development and validation. The approach for the method development and validation provided a foundation for experiments that examine RK metabolism and bioavailability.

SUBMITTER: Yuan B

PROVIDER: S-EPMC7391222 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:The emergence of Mycobacterium tuberculosis strains resistant to current first-line antibiotic regimens constitutes a major global health threat. New treatments against multidrug-resistant tuberculosis (MDR-TB) are thus eagerly needed in particular in countries with a high MDR-TB prevalence. In this context, macozinone (PBTZ169), a promising drug candidate with an unique mode of action and highly potent in vitro tuberculocidal properties against MDR Mycobacterium strains, has now reached the clinical phase and has been notably tested in healthy male volunteers in Switzerland. To that endeavor, a multiplex UHPLC-MS/MS method has been developed for the sensitive and accurate human plasma levels determination of PBTZ169 along with five metabolites retaining in vitro anti-TB activity. Plasma protein precipitation with methanol was carried out as a simplified sample clean-up procedure followed by direct injection of the undiluted supernatant for the bioanalysis of the six analytes within 5 min, using 1.8 μm reversed-phase chromatography coupled to triple quadrupole mass spectrometry employing electrospray ionization in the positive mode. Stable isotopically-labelled PBTZ169 was used as internal standard (ISTD), while metabolites could be reliably quantified using two unlabeled chemical analogues selected as ISTD from a large in-house analogous compounds library. The overall methodology was fully validated according to current recommendations (FDA, EMEA) for bioanalytical methods, which include selectivity, carryover, qualitative and quantitative matrix effect, extraction recovery, process efficiency, trueness, precision, accuracy profiles, method and instrument detection limits, integrity to dilution, anticoagulant comparison and short- and long-term stabilities. Stability studies on the reduced metabolite H2-PBTZ169 have shown no significant impact on the actual PBTZ169 concentrations determined with the proposed assay. This simplified, rapid, sensitive and robust methodology has been applied to the bioanalysis of human plasma samples collected within the frame of a phase I clinical study in healthy volunteers receiving PBTZ169.

Project description:BackgroundHydroxychloroquine (HCQ) and azithromycin (AZM) are antimalarial drugs recently reported to be active against severe acute respiratory syndrome coronavirus- 2 (SARS-CoV-2), which is causing the global COVID-19 pandemic. In an emergency response to the pandemic, we aimed to develop a quantitation method for HCQ, its metabolites desethylhydroxychloroquine (DHCQ) and bisdesethylchloroquine (BDCQ), and AZM in human plasma.MethodsLiquid chromatography tandem mass spectrometry was used to develop the method. Samples (20 μL) are extracted by solid-phase extraction and injected onto the LC-MS/MS system equipped with a PFP column (2.0 × 50 mm, 3 μm). ESI+ and MRM are used for detection. Ion pairs m/z 336.1→247.1 for HCQ, 308.1→179.1 for DHCQ, 264.1→179.1 for BDCQ, and 749.6→591.6 for AZM are selected for quantification. The ion pairs m/z 342.1→253.1, 314.1→181.1, 270.1→181.1, and 754.6→596.6 are selected for the corresponding deuterated internal standards (IS) HCQ-d4, DHCQ-d4, BDCQ-d4, and AZM-d5. The less abundant IS ions from 37Cl were used to overcome the interference from the analytes.ResultsUnder optimized conditions, retention times are 0.78 min for BDCQ, 0.79 min for DHCQ, 0.92 min for HCQ and 1.87 min for AZM. Total run time is 3.5 min per sample. The calibration ranges are 2-1000 ng/mL for HCQ and AZM, 1-500 ng/mL for DHCQ and 0.5-250 ng/mL for BDCQ; samples above the range are validated for up to 10-fold dilution. Recoveries of the method ranged from 88.9-94.4% for HCQ, 88.6-92.9% for DHCQ, 88.7-90.9% for BDCQ, and 98.6%-102% for AZM. The IS normalized matrix effect were within (100±10) % for all 4 analytes. Blood samples are stable for at least 6 hr at room temperature. Plasma samples are stable for at least 66 hr at room temperature, 38 days at -70°C, and 4 freeze-thaw cycles.ConclusionsAn LC-MS/MS method for simultaneous quantitation of HCQ, DHCQ, BDCQ, and AZM in human plasma was developed and validated for clinical studies requiring fast turnaround time and small samples volume.

Dataset Information

UHPLC-QqQ-MS/MS method development and validation with statistical analysis: Determination of raspberry ketone metabolites in mice plasma and brain.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets