Development of a Physiologically Based Pharmacokinetic Model for Nitrofurantoin in Rabbits, Rats, and Humans

Nitrofurantoin (NFT) is a commonly used antibiotic for the treatment of urinary tract infections that can cause liver toxicity. Despite reports of hepatic adverse events associated with NFT exposure, there is still limited understanding of the interplay between NFT exposure, its disposition, and the...

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Vydáno v:Pharmaceutics Ročník 15; číslo 9; s. 2199
Hlavní autoři: Sharma, Raju Prasad, Burgers, Elsje J., Beltman, Joost B.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 25.08.2023
MDPI
Témata:
Antibiotics
Drug dosages
drug-induced liver injury
Health aspects
Liver
Medical research
Medicine, Experimental
Nitrofurantoin
Normal distribution
Pharmacokinetics
Physiological aspects
physiologically based pharmacokinetic model
Physiology
Plasma
Rabbits
renal insufficiency
Simulation methods
Urinary tract diseases
Urinary tract infections
Urine
Urogenital system
Timor-Leste
ISSN:1999-4923, 1999-4923
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Shrnutí:Nitrofurantoin (NFT) is a commonly used antibiotic for the treatment of urinary tract infections that can cause liver toxicity. Despite reports of hepatic adverse events associated with NFT exposure, there is still limited understanding of the interplay between NFT exposure, its disposition, and the risk of developing liver toxicity. In this study, we aim to develop a physiologically based pharmacokinetic (PBPK) model for NFT in three different species (rabbits, rats, and humans) that can be used as a standard tool for predicting drug-induced liver injury (DILI). We created several versions of the PBPK model using previously published kinetics data from rabbits, and integrated enterohepatic recirculation (EHR) using rat data. Our model showed that active tubular secretion and reabsorption in the kidney are critical in explaining the non-linear renal clearance and urine kinetics of NFT. We subsequently extrapolated the PBPK model to humans. Adapting the physiology to humans led to predictions consistent with human kinetics data, considering a low amount of NFT to be excreted into bile. Model simulations predicted that the liver of individuals with a moderate-to-severe glomerular filtration rate (GFR) is exposed to two-to-three-fold higher concentrations of NFT than individuals with a normal GFR, which coincided with a substantial reduction in the NFT urinary concentration. In conclusion, people with renal insufficiency may be at a higher risk of developing DILI due to NFT exposure, while at the same time having a suboptimal therapeutic effect with a high risk of drug resistance. Our PBPK model can in the future be used to predict NFT kinetics in individual patients on the basis of characteristics like age and GFR.
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ISSN:1999-4923
1999-4923
DOI:10.3390/pharmaceutics15092199