The aim of the study was to apply Physiologically-Based Pharmacokinetic (PBPK) modelling to predict the effect of liver disease (LD) on the pharmacokinetics (PK) of dexamethasone (DEX) in the treatment of COVID-19. A whole-body PBPK model was created to simulate 100 adult individuals aged 18-60 years. Physiological changes (e.g., plasma protein concentration, liver size, CP450 expression, hepatic blood flow) and portal vein shunt were incorporated into the LD model. The changes were implemented by using the Child-Pugh (CP) classification system. DEX was qualified using clinical data in healthy adults for both oral (PO) and intravenous (IV) administrations and similarly propranolol (PRO) and midazolam (MDZ) were qualified with PO and IV clinical data in healthy and LD adults. The qualified model was subsequently used to simulate a 6 mg PO and 20 mg IV dose of DEX in patients with varying degrees of LD, with and without shunting. The PBPK model was successfully qualified across DEX, MDZ and PRO. In contrast to healthy adults, the simulated systemic clearance of DEX decreased (35%-60%) and the plasma concentrations increased (170%-400%) in patients with LD. Moreover, at higher doses of DEX, the AUC ratio between healthy/LD individuals remained comparable to lower doses. The exposure of DEX in different stages of LD was predicted through PBPK modelling, providing a rational framework to predict PK in complex clinical scenarios related to COVID-19. Model simulations suggest dose adjustments of DEX in LD patients are not necessary considering the low dose administered in the COVID-19 protocol.
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http://dx.doi.org/10.3389/fphar.2022.814134 | DOI Listing |
J Pharm Sci
December 2024
Certara UK Ltd., Certara Predictive Technologies Division, 1 Concourse Way, Level 2-Acero, Sheffield, S1 2BJ, United Kingdom. Electronic address:
Predicting steady-state volume of distribution (V) is a key component of pharmacokinetic predictions and often guided using preclinical data. However, when bottom-up prediction from physiologically-based pharmacokinetic (PBPK) models and observed V misalign in preclinical species, or predicted V from different models varies significantly, no consensus exists for selecting models or preclinical species to improve the prediction. Through systematic analysis of V prediction across rat, dog, monkey, and human, using common methods, a practical strategy for predicting human V, with or without integration of preclinical PK information is warranted.
View Article and Find Full Text PDFBiopharm Drug Dispos
December 2024
Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, China.
Amphotericin B (AmB) has been a cornerstone in the treatment of invasive fungal infections for over 6 decades. Compared with conventional amphotericin B deoxycholate (AmB-DOC), liposomal amphotericin B has comparable efficacy but less nephrotoxicity. The main purpose of this study was to investigate the reason why liposomal amphotericin B has similar therapeutic effects but lower toxicity and the differences of distribution in humans between liposomal amphotericin B and AmB-DOC.
View Article and Find Full Text PDFClin Pharmacol Ther
December 2024
College of Pharmacy, CHA University, Seongnam-si, Gyeonggi-do, South Korea.
Escitalopram is commonly prescribed for depressive and anxiety disorders in elderly patients, who often show variable drug responses and face higher risks of side effects due to age-related changes in organ function. The CYP2C19 polymorphism may further affect escitalopram pharmacokinetics in elderly patients, complicating dose optimization for this group. Previous pharmacogenetic studies examining the impact of CYP2C19 phenotype on escitalopram treatment outcomes have primarily focused on younger adults, leaving a gap in understanding its effects on the elderly.
View Article and Find Full Text PDFDrugs R D
December 2024
Galapagos SASU, Romainville, France.
Background And Objective: This study provides a physiologically based pharmacokinetic (PBPK) model-based analysis of the potential drug-drug interaction (DDI) between cyclosporin A (CsA), a breast cancer resistance protein transporter (BCRP) inhibitor, and methotrexate (MTX), a putative BCRP substrate.
Methods: PBPK models for CsA and MTX were built using open-source tools and published data for both model building and for model verification and validation. The MTX and CsA PBPK models were evaluated for their application in simulating BCRP-related DDIs.
CPT Pharmacometrics Syst Pharmacol
December 2024
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, USA.
Ritonavir (RTV) is a potent CYP3A inhibitor that is widely used as a pharmacokinetic (PK) enhancer to increase exposure to select protease inhibitors. However, as a strong and complex perpetrator of CYP3A interactions, RTV can also enhance the exposure of other co-administered CYP3A substrates, potentially causing toxicity. Therefore, the prediction of drug-drug interactions (DDIs) and estimation of dosing requirements for concomitantly administered drugs is imperative.
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