Browning Marc R, Drexler Dieter M, Olah Timothy V, Morgan Daniel G
Bioanalytical Research, Pharmaceutical Candidate Optimization, Bristol-Myers Squibb, Wallingford, CT 06492-7660, USA.
Bioanalysis. 2010 Apr;2(4):745-53. doi: 10.4155/bio.10.25.
Bioanalytical support of drug-discovery efforts increasingly requires more complex multiple component analysis, including the bioanalysis of drugs, prodrugs and metabolites. Just as the physiochemical properties of these components may differ widely from each other, optimal LC and MS conditions, including polarity, can also vary greatly among the analytes of interest, thus presenting significant challenges during quantitative LC-MS-based bioanalysis. A single compromised method for the determination of all analytes may sacrifice sensitivity or chromatographic conditions for one analyte in order to achieve adequate results for another. Manually switching between assay conditions to analyze samples under separately optimized conditions for individual compounds can be time consuming.
The method presented here addresses the problem of differential analyte optimization using a multiplexed approach for simultaneous quantitative bioanalysis of multiple analytes in the same sample, employing a mixed mode of both turbulent- and laminar-flow chromatography.
The approach is illustrated with the quantitation of a lipophilic drug and its hydrophilic phosphate ester prodrug in a biological matrix under individually optimized LC-MS conditions.
药物研发工作的生物分析支持越来越需要更复杂的多组分分析，包括药物、前体药物和代谢物的生物分析。正如这些组分的物理化学性质可能彼此差异很大一样，包括极性在内的最佳液相色谱（LC）和质谱（MS）条件在感兴趣的分析物之间也可能有很大差异，因此在基于LC-MS的定量生物分析过程中带来了重大挑战。用于测定所有分析物的单一折衷方法可能会为了一种分析物获得足够的结果而牺牲另一种分析物的灵敏度或色谱条件。在单独优化的条件下手动切换分析条件以分析各个化合物的样品可能很耗时。
本文提出的方法通过采用一种多路复用方法解决了分析物差异优化的问题，该方法用于在同一样品中同时对多种分析物进行定量生物分析，采用了湍流色谱和层流色谱的混合模式。
该方法通过在单独优化的LC-MS条件下对生物基质中的亲脂性药物及其亲水性磷酸酯前体药物进行定量得到了说明。
