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Semin Nephrol. 2019 Mar;39(2):176-189. doi: 10.1016/j.semnephrol.2018.12.006.

Modeling Exposure to Understand and Predict Kidney Injury.

Author information

1
Medicine Design Modeling and Simulation, Pfizer, Inc, Cambridge, MA. Electronic address: Zhenhong.Li@pfizer.com.
2
Translational Science, Drug Metabolism and Pharmacokinetics, Certara UK Ltd, Simcyp Division, Sheffield, UK.
3
Translational Science, Certara UK Ltd, Simcyp Division, Sheffield, UK.
4
Drug Metabolism and Pharmacokinetics, Janssen Research & Development, Springhouse PA.
5
Medicine Design Pharmacokinetics, Dynamics and Metabolism, Pfizer, Inc, Cambridge, MA.
6
Medicine Design Modeling and Simulation, Pfizer, Inc, Cambridge, MA.

Abstract

Exposure is a critically important aspect to consider in the study and management of drug-induced kidney injury. Although blood concentrations of kidney toxicants often may provide a valid surrogate measure of kidney exposure, the kidney has several unique physiological and biochemical properties that lend themselves to accumulation or exclusion of some drugs at sites of toxicity. In such cases, an understanding of these pharmacokinetic mechanisms can be as important as understanding the underlying mechanisms of toxicity. Physiologically based pharmacokinetic models, which mathematically codify such mechanisms in a biologically plausible form, increasingly are being used for developing an understanding of pharmacokinetics across patient populations, drug-drug interactions, and pharmacokinetic-pharmacodynamic relationships. This perspective provides a review of the physiological and biochemical mechanisms as well as the physiochemical properties that theoretically could drive drug accumulation or exclusion within the kidney, along with examples in which these mechanisms have proven important in driving the manifestation of toxicity in vivo. In addition, an overview of the structure, applications, and limitations of existing kidney physiologically based pharmacokinetic models is provided. Finally, a perspective on gaps and associated challenges to such models in the field of toxicology is discussed briefly.

KEYWORDS:

Physiologically based pharmacokinetic (PBPK) modeling; active transport; drug-induced kidney injury (DIKI); intracellular accumulation; kidney exposure; passive permeation

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