Good Preclinical Bioanalytical Chemistry Requires Proper Sampling from Laboratory Animals: Automation of Blood and Microdialysis Sampling Improves the Productivity of LC/MSMS

The preclinical bioanalytical process with animal models begins with sampling biological fluids and tissue. The goal is to understand oral absorption kinetics, distribution, metabolism, excretion, blood brain barrier penetration, drug-drug interactions, and the influences on biomarkers, hematology,...

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Veröffentlicht in:Analytical Sciences 2003, Vol.19(4), pp.479-485
Hauptverfasser: XIE, Fuming, BRUNTLETT, Craig S., ZHU, Yongxin, KISSINGER, Candice B., KISSINGER, Peter T.
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Sprache:eng
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Zusammenfassung:The preclinical bioanalytical process with animal models begins with sampling biological fluids and tissue. The goal is to understand oral absorption kinetics, distribution, metabolism, excretion, blood brain barrier penetration, drug-drug interactions, and the influences on biomarkers, hematology, electrophysiology, cardiology, blood pressure and behavior. An overview is obtained by periodic blood sampling of 8 - 12 samples over a total time span of 10 - 24h. Urine, feces, bile and microdialysates can augment the information available from whole blood. In today’s preclinical environment, the majority of samples are processed by LC/MSMS augmented by robotic sample preparation tools. These tools save labor and improve precision for smaller volume/lower concentration samples. Our laboratories have been engaged in a project that is focused on improving both the quality and throughput for laboratory animal studies, while providing for reduced numbers of animals and enhanced animal comfort. We have implemented a robotic system that can accomplish most of the above goals for laboratory rats, dogs and primates. Studies with mice are at an earlier stage, but feasibility has been demonstrated. This presentation is a progress report on this evolving research program in cooperation with multiple pharmaceutical and drug development companies. We will illustrate results and discuss future directions.
ISSN:0910-6340
1348-2246
DOI:10.2116/analsci.19.479