Adult and infant pharmacokinetic profiling of dihydrocodeine using physiologically based pharmacokinetic modeling

Abstract

We previously analysed the serum concentrations of dihydrocodeine in a 1‐month‐old infant with respiratory depression after being prescribed dihydrocodeine phosphate 2.0 mg/day divided t.i.d. for 2 days. The purpose was to develop a full physiologically based pharmacokinetic (PBPK) model that could account for these and other drug monitoring results. Based on experiments in Caco‐2 cell monolayers, the effective permeability of dihydrocodeine in human jejunum was established as 1.28 × 10−4 cm/s. The in vitro Vmax/Km values for dihydrocodeine demethylation mediated by recombinant cytochrome P450 2D6 and 3A4 were 0.19 and 0.066 μl/min/pmol, respectively, and for dihydrocodeine 6‐O‐glucuronidation mediated by recombinant UGT2B4 and 2B7, the Vmax/Km values were 0.14 and 0.22 μl/min/mg protein, respectively. Renal clearance was calculated as 5.37 L/h on the total clearance value multiplied by the fraction recovered in urine. The reported plasma concentration–time profiles of dihydrocodeine after intravenous administration in healthy volunteers were used to adjust the tissue partitioning ratios. The developed model simulated the pharmacokinetic profiles of dihydrocodeine after single and multiple oral administrations reasonably well in the same population. Subsequently, the validated model was used to simulate pharmacokinetic profiles for five pediatric cases, including the 1‐month‐old Japanese boy and a 14‐year‐old Japanese girl who took an overdose of dihydrocodeine phosphate (37 mg). The simulated pharmacokinetic profiles for five virtual pediatric subjects matching the age, gender, and P450 2D6 phenotype of each case approximately reflected the observed values. These results suggested that our dihydrocodeine PBPK model reproduced the results of clinical cases reasonably well for subjects.

Physiologically Based Pharmacokinetic Modeling and Allometric Scaling in Pediatric Drug Development: Where Do We Draw the Line?

“…For example, on average, 39% of Chinese subjects have an intermediate phenotype for CYP2D6, whereas North European White populations do not have this phenotype. Some recent studies have applied PBPK modeling to different pediatric ethnic groups 35,43–45 . Notably, Cui et al 46 simulated dosing of chloroquine for the treatment of coronavirus disease 2019 in Chinese pediatric subjects.…”

Machine Learning Prediction of the Three Main Input Parameters of a Simplified Physiologically Based Pharmacokinetic Model Subsequently Used to Generate Time-Dependent Plasma Concentration Data in Humans after Oral Doses of 212 Disparate Chemicals

“…1,2) Such monitoring methods could be supported by pharmacokinetic modeling and simulations to address critical questions related to patient care. 3) Full physiologically based pharmacokinetic (PBPK) models 4) can predict drug monitoring results in patients [5][6][7] based on the physiological and anatomical properties of the relevant organ and the chemical properties of the modeled substance. 8,9) Simplified PBPK models, which are easier to handle than full models, have been developed for use by a wide range of paramedical staff for predicting drug monitoring results and have been applied in some nonfatal overdose cases.…”

Pharmacokinetic modeling of over-the-counter drug diphenhydramine self-administered in overdoses in Japanese patients admitted to hospital

“…The drug monitoring of steady-state plasma concentrations in individual patients in the clinical setting can, in general, be supported by pharmacokinetic models and simulations. Full physiologically based pharmacokinetic (PBPK) models [5] can predict drug monitoring results in patients [6][7][8]. We have developed simplified PBPK models [9] and have applied them to cases of edoxaban overdose [10] and to an overdose of duloxetine along with other antipsychotic drugs [11].…”