Development of a Physiologically Based Pharmacokinetic Model of Ethionamide in the Pediatric Population by Integrating Flavin‐Containing Monooxygenase 3 Maturational Changes Over Time

Nguyen, Phuong Thi Thu; Parvez, Masud; Kim, Min Jung; Lee, Jung Ho; Ahn, Sang Ho; Ghim, Jong-Lyul; Shin, Jae‐Gook

doi:10.1002/jcph.1133

Cited by 6 publications

(10 citation statements)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The MRP‐3 adult levels can only be reached at adult age (Prasad et al, ) which is not a sensitive PBPK model parameter. Scaling the verified adult PBPK models to children is a common successful practice (Korth‐Bradley, ; Maharaj, Barrett, & Edginton, ; Nguyen et al, ). The scaled Pop‐PBPK model well‐predicted the experimentally observed MPA and MMF concentrations in plasma and saliva at steady state in Jordanian pediatric SKTP.…”

Section: Discussionmentioning

confidence: 99%

The development of a population physiologically based pharmacokinetic model for mycophenolic mofetil and mycophenolic acid in humans using data from plasma, saliva, and kidney tissue

Alsmadi

Alfarah

Albderat

et al. 2019

Biopharm & Drug Disp

View full text Add to dashboard Cite

Background Mycophenolic acid (MPA) is used widely to prevent graft rejection in kidney‐transplant patients. Therapeutic drug monitoring (TDM) in plasma requires an invasive procedure that is inconvenient, especially in pediatric patients. TDM in saliva is a more convenient non‐invasive alternative compared with plasma. Methods A population physiologically based pharmacokinetic (Pop‐PBPK) model of mycophenolate mofetil (MMF) and MPA with enterohepatic recycling was built and verified using previously published plasma, saliva, and kidney biopsy data in healthy and kidney‐transplant adult patients. The verified model was then used to predict experimentally observed plasma and saliva MMF and MPA TDM data in Jordanian pediatric kidney transplant patients measured using LC‐MS/MS. A correlation was established between plasma and saliva exposures in pediatrics. Results The developed LCMS was sensitive to both MMF and MPA in plasma and saliva. The developed Pop‐PBPK model predicted well the previously reported MMF and MPA levels in plasma, saliva, and kidney tissue and those observed in the current study (more than 75% of observed data points were within 90% predictive interval of population simulations). A statistically significant correlation was found between plasma and saliva exposures for both MMF (Pop‐PBPK predicted and observed) and MPA (Pop‐PBPK predicted). Conclusion Both MPA and MMF can be classified as class III compounds in the Salivary Excretion Classification System. Saliva is an alternative body fluid to plasma that can be used for TDM of MPA and MMF in kidney‐transplant patients in pediatrics. Exposure to MPA and MMF in plasma, saliva, and kidney tissue was reliably predicted using the developed Pop‐PBPK model.

show abstract

Section: Discussionmentioning

confidence: 99%

The development of a population physiologically based pharmacokinetic model for mycophenolic mofetil and mycophenolic acid in humans using data from plasma, saliva, and kidney tissue

Alsmadi

Alfarah

Albderat

et al. 2019

Biopharm & Drug Disp

View full text Add to dashboard Cite

show abstract

“…After 30 minutes, the reaction was stopped, and concentrations of the internal standard and ethionamide sulfoxide in the solvent and acetonitrile were measured. The liquid chromatography–tandem mass spectrometry method for the quantitation of ethionamide and ethionamide sulfoxide was performed in accordance with a previous report …”

Section: Methodsmentioning

confidence: 99%

“…DDI predictions were carried out by simulating the substrate‐inhibitor interaction according to the study design. In particular, the PBPK model of ethionamide developed in our previous study was used to predict single‐dose DDI outcomes with methimazole using PBPK modeling. Ten trials consisting of 10 subjects each were simulated; the age range of the virtual population was 18 to 50 years, with 50% of the subjects being women.…”

Section: Methodsmentioning

confidence: 99%

“…In contrast, FMO2 is primarily located in the lungs and expressed in most mammals . Oxidative activation of the thioamide, ethionamide, by FMOs 1 through 3 occurs in mammals and mycobacteria in 2 oxygenation steps that cause oxidative stress in vivo; however, our previous study showed that ethionamide clearance was highly sensitive to reductions in FMO3 activity …”

mentioning

confidence: 89%

“…In addition to the endogenous factors, drug‐drug interaction (DDI)‐mediated metabolism and transport are well‐known exogenous factors affecting the drug PK causing interindividual variations. In vitro studies have suggested that ethionamide is a high‐affinity substrate of FMOs . Therefore, it is imperative to evaluate the drug interaction potential of ethionamide with drugs that are FMO3 inhibitors.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Physiologically Based Pharmacokinetic Modeling Approach to Predict Drug‐Drug Interactions With Ethionamide Involving Impact of Genetic Polymorphism on FMO3

Nguyen

Parvez

Kim

et al. 2019

The Journal of Clinical Pharma

Self Cite

View full text Add to dashboard Cite

The widely used second‐line antituberculosis drug ethionamide shows wide interindividual variability in its disposition; however, the relevant factors affecting this phenomenon have not been characterized. We previously reported the major contribution of flavin‐containing monooxygenase 3 (FMO3) in the reductive elimination pathway of ethionamide. In this study, ethionamide metabolism was potentially inhibited by methimazole in vitro. The drug‐drug interaction leading to methimazole affecting the disposition of ethionamide mediated by FMO3 was then quantitated using a bottom‐up approach with a physiologically based pharmacokinetic framework. The maximum concentration (Cmax) and area under the curve (AUC) of ethionamide were estimated to increase by 13% and 16%, respectively, when coadministered with methimazole. Subsequently, we explored the effect of FMO3 genetic polymorphism on metabolic capacity, by constructing 2 common functional variants, Lys158‐FMO3 and Gly308‐FMO3. Compared to the wild type, recombinant Lys158‐FMO3 and Gly308‐FMO3 variants significantly decreased the intrinsic clearance of ethionamide by 2% and 24%, respectively. Two prevalent functional variants of FMO3 were predicted to affect ethionamide disposition, with mean ratios of Cmax and AUC of up to 1.5 and 1.7, respectively, in comparison with the wild type. In comparing single ethionamide administration with the wild type, simulations of the combined effects of comedications and FMO3 genetic polymorphism estimated that the Cmax and AUC ratios of ethionamide increased up to 1.7 and 2.0, respectively. These findings suggested that FMO3‐mediated drug‐drug interaction and genetic polymorphism could be important determinants of interindividual heterogeneity in ethionamide disposition that need to be considered comprehensively to optimize the personalized dosing of ethionamide.

show abstract

Development of physiologically‐based pharmacokinetic models for standard of care and newer tuberculosis drugs

Humphries

Almond

Berg

et al. 2021

CPT Pharmacom & Syst Pharma

View full text Add to dashboard Cite

Tuberculosis (TB) remains a global health problem and there is an ongoing effort to develop more effective therapies and new combination regimes that can reduce duration of treatment. The purpose of this study was to demonstrate utility of a physiologically‐based pharmacokinetic modeling approach to predict plasma and lung concentrations of 11 compounds used or under development as TB therapies (bedaquiline [and N‐desmethyl bedaquiline], clofazimine, cycloserine, ethambutol, ethionamide, isoniazid, kanamycin, linezolid, pyrazinamide, rifampicin, and rifapentine). Model accuracy was assessed by comparison of simulated plasma pharmacokinetic parameters with healthy volunteer data for compounds administered alone or in combination. Eighty‐four percent (area under the curve [AUC]) and 91% (maximum concentration [Cmax]) of simulated mean values were within 1.5‐fold of the observed data and the simulated drug‐drug interaction ratios were within 1.5‐fold (AUC) and twofold (Cmax) of the observed data for nine (AUC) and eight (Cmax) of the 10 cases. Following satisfactory recovery of plasma concentrations in healthy volunteers, model accuracy was assessed further (where patients’ with TB data were available) by comparing clinical data with simulated lung concentrations (9 compounds) and simulated lung: plasma concentration ratios (7 compounds). The 5th–95th percentiles for the simulated lung concentration data recovered between 13% (isoniazid and pyrazinamide) and 88% (pyrazinamide) of the observed data points (Am J Respir Crit Care Med, 198, 2018, 1208; Nat Med, 21, 2015, 1223; PLoS Med, 16, 2019, e1002773). The impact of uncertain model parameters, such as the fraction of drug unbound in lung tissue mass (fumass), is discussed. Additionally, the variability associated with the patient lung concentration data, which was sparse and included extensive within‐subject, interlaboratory, and experimental variability (as well interindividual variability) is reviewed. All presented models are transparently documented and are available as open‐source to aid further research.

show abstract

Development of a Physiologically Based Pharmacokinetic Model of Ethionamide in the Pediatric Population by Integrating Flavin‐Containing Monooxygenase 3 Maturational Changes Over Time

Cited by 6 publications

References 54 publications

The development of a population physiologically based pharmacokinetic model for mycophenolic mofetil and mycophenolic acid in humans using data from plasma, saliva, and kidney tissue

The development of a population physiologically based pharmacokinetic model for mycophenolic mofetil and mycophenolic acid in humans using data from plasma, saliva, and kidney tissue

Physiologically Based Pharmacokinetic Modeling Approach to Predict Drug‐Drug Interactions With Ethionamide Involving Impact of Genetic Polymorphism on FMO3

Development of physiologically‐based pharmacokinetic models for standard of care and newer tuberculosis drugs

Contact Info

Product

Resources

About