Abstract
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.
Highlights
Chronic liver disease (LD) is prevalent in 3–8% of patients suffering with COVID-19. (Qiu et al, 2020)
DEX exposure was predicted to be more than 3 times higher in CP-C individuals, no dose adjustments seem necessary in patients with LD considering DEX’s low hepatic extraction, the low dose administered in the COVID-19 protocol and short period of treatment (10 days), and the therapeutic index of DEX
This study provides in silico evidence-based guidance towards the management of complex clinical scenarios related to COVID-19 and provides a rational framework for future Physiologically-Based Pharmacokinetic (PBPK) modelling applications in LD patients
Summary
Chronic liver disease (LD) is prevalent in 3–8% of patients suffering with COVID-19. (Qiu et al, 2020). Chronic liver disease (LD) is prevalent in 3–8% of patients suffering with COVID-19. Chronic LD has been associated with a higher rate of mortality in COVID-19 patients and can affect the drug distribution of several treatments. End stage chronic liver disease leads to cirrhosis which is characterised by the replacement of injured tissue with a collagenous scar and is accompanied by a loss of functional hepatocytes as well as a distortion in hepatic vasculature (Schuppan and Afdhal, 2008; Johnson et al, 2010). The severity of liver disease can be classified using the CP score A, B, and C and is based on physiological and biological parameters. As the severity of liver disease increases, the distortion of the hepatic vasculature may lead to portal hypertension and in turn portacaval shunting.
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