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- W4367183902 abstract "Pharmacokinetics have historically been assessed using drug concentration data obtained via blood draws and bench-top analysis. The cumbersome nature of these typically constrains studies to at most a dozen concentration measurements per dosing event. This, in turn, limits our statistical power in the detection of hours-scale, time-varying physiological processes. Given the recent advent of in vivo electrochemical aptamer-based (EAB) sensors, however, we can now obtain hundreds of concentration measurements per administration. Our aim in this paper was to assess the ability of these time-dense datasets to describe time-varying pharmacokinetic models with good statistical significance.We used seconds-resolved measurements of plasma tobramycin concentrations in rats to statistically compare traditional one- and two-compartmental pharmacokinetic models to new models in which the proportional relationship between a drug's plasma concentration and its elimination rate varies in response to changing kidney function.We found that a modified one-compartment model in which the proportionality between the plasma concentration of tobramycin and its elimination rate falls reciprocally with time either meets or is preferred over the standard two-compartment pharmacokinetic model for half of the datasets characterized. When we reduced the impact of the drug's rapid distribution phase on the model, this one-compartment, time-varying model was statistically preferred over the standard one-compartment model for 80% of our datasets.Our results highlight both the impact that simple physiological changes (such as varying kidney function) can have on drug pharmacokinetics and the ability of high-time resolution EAB sensor measurements to identify such impacts." @default.
- W4367183902 created "2023-04-28" @default.
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- W4367183902 date "2023-05-23" @default.
- W4367183902 modified "2023-10-02" @default.
- W4367183902 title "Using seconds‐resolved pharmacokinetic datasets to assess pharmacokinetic models encompassing time‐varying physiology" @default.
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- W4367183902 doi "https://doi.org/10.1111/bcp.15756" @default.
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