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• W4385076248 abstract "Pharmacokinetic/pharmacodynamic modelling has emerged as a valuable technique for understanding drug exposure and response relationships in drug development. Pharmacokinetic data are often obtained by taking multiple blood samples, which may disturb physiological parameters and complicate study designs. Wearable automatic blood sampling systems can improve this limitation by collecting dried blood samples at programmable time points without disrupting cardiovascular parameters. It is the objective of this study to evaluate the bioanalysis of DBS in comparison to conventional blood sampling techniques and to optimize the recovery of various compounds spiked into canine blood dried on filter paper tape. Incubated blood samples from Beagle dogs were spiked with 16 different compounds and half of the whole blood sample was centrifuged to obtain plasma. After the dried blood sample drops were dried, liquid chromatography-mass spectrometry methods were used to analyze the samples. The study explored different anticoagulants, sample preparation methods and technical approaches to best determine the compound concentrations in dried blood samples. With the two anticoagulants tested and using the optimized sample preparation methods and technical approaches we employed, the bioanalysis of dried blood samples can provide equivalent results to conventional blood sampling techniques. Automated blood sampling systems have the potential to provide increased numbers of blood samples, providing substantially more Pharmacokinetic data within safety pharmacology studies without disrupting physiological parameters. They can provide a viable alternative to traditional methods of obtaining blood for various other types of studies or analyses." @default.
• W4385076248 created "2023-07-23" @default.
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• W4385076248 date "2023-09-01" @default.
• W4385076248 modified "2023-09-26" @default.
• W4385076248 title "Optimization of bioanalysis of dried blood samples" @default.
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• W4385076248 doi "https://doi.org/10.1016/j.vascn.2023.107296" @default.
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