Application of Physiologically Based Pharmacokinetic Modeling to Predict Acetaminophen Metabolism and Pharmacokinetics in Children

Jiang, Xianyang; Zhao, Ping; Barrett, Jeffrey S.; Lj, Lesko; Schmidt, Stephan

doi:10.1038/psp.2013.55

Cited by 96 publications

(96 citation statements)

References 49 publications

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“…Such an ontogeny-based approach has been successfully used recently to predict pediatric drug disposition of acetaminophen (Jiang et al, 2013). Together, the CES1 absolute ontogeny data presented here show a difference in the prodrug-metabolizing capacities of neonates and infants versus those of older children and adults.…”

Section: Age-dependent Hepatic Carboxylesterase Abundancementioning

confidence: 77%

Age-Dependent Absolute Abundance of Hepatic Carboxylesterases (CES1 and CES2) by LC-MS/MS Proteomics: Application to PBPK Modeling of Oseltamivir In Vivo Pharmacokinetics in Infants

et al. 2016

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The age-dependent absolute protein abundance of carboxylesterase (CES) 1 and CES2 in human liver was investigated and applied to predict infant pharmacokinetics (PK) of oseltamivir. The CES absolute protein abundance was determined by liquid chromatography-tandem mass spectrometry proteomics in human liver microsomal and cytosolic fractions prepared from tissue samples obtained from 136 pediatric donors and 35 adult donors. Two surrogate peptides per protein were selected for the quantification of CES1 and CES2 protein abundance. Purified CES1 and CES2 protein standards were used as calibrators, and the heavy labeled peptides were used as the internal standards. In hepatic microsomes, CES1 and CES2 abundance (in picomoles per milligram total protein) increased approximately 5-fold (315.2 vs. 1664.4) and approximately 3-fold (59.8 vs. 174.1) from neonates to adults, respectively. CES1 protein abundance in liver cytosol also showed age-dependent maturation. Oseltamivir carboxylase activity was correlated with protein abundance in pediatric and adult liver microsomes. The protein abundance data were then used to model in vivo PK of oseltamivir in infants using pediatric physiologically based PK modeling and incorporating the protein abundance-based ontogeny function into the existing pediatric Simcyp model. The predicted pediatric area under the curve, maximal plasma concentration, and time for maximal plasma concentration values were below 2.1-fold of the clinically observed values, respectively.

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Section: Age-dependent Hepatic Carboxylesterase Abundancementioning

confidence: 77%

Age-Dependent Absolute Abundance of Hepatic Carboxylesterases (CES1 and CES2) by LC-MS/MS Proteomics: Application to PBPK Modeling of Oseltamivir In Vivo Pharmacokinetics in Infants

et al. 2016

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“…Several groups reviewed the use of PBPK in pediatric drug development and research, with various versions of workflow being proposed to predict drug PK in pediatrics using PBPK (Barrett et al, 2012;Leong et al, 2012;Jiang et al, 2013;Maharaj and Edginton, 2014;Willmann et al, 2014). All proposals articulate the importance of establishing/ verifying an adult PBPK model, followed by utilizing the most up-todate pediatric physiology models to prospectively predict drug PK in subjects of different pediatric age groups.…”

Section: Discussionmentioning

confidence: 99%

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Mehrotra¹,

Bhattaram²,

Earp³

et al. 2016

Drug Metabolism and Disposition

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Dose selection is one of the key decisions made during drug development in pediatrics. There are regulatory initiatives that promote the use of model-based drug development in pediatrics. Pharmacometrics or quantitative clinical pharmacology enables development of models that can describe factors affecting pharmacokinetics and/or pharmacodynamics in pediatric patients. This manuscript describes some examples in which pharmacometric analysis was used to support approval and labeling in pediatrics. In particular, the role of pharmacokinetic (PK) comparison of pediatric PK to adults and utilization of dose/exposure-response analysis for dose selection are highlighted. Dose selection for esomeprazole in pediatrics was based on PK matching to adults, whereas for adalimumab, exposure-response, PK, efficacy, and safety data together were useful to recommend doses for pediatric Crohn's disease. For vigabatrin, demonstration of similar dose-response between pediatrics and adults allowed for selection of a pediatric dose. Based on model-based pharmacokinetic simulations and safety data from darunavir pediatric clinical studies with a twicedaily regimen, different once-daily dosing regimens for treatmentnaïve human immunodeficiency virus 1-infected pediatric subjects 3 to <12 years of age were evaluated. The role of physiologically based pharmacokinetic modeling (PBPK) in predicting pediatric PK is rapidly evolving. However, regulatory review experiences and an understanding of the state of science indicate that there is a lack of established predictive performance of PBPK in pediatric PK prediction. Moving forward, pharmacometrics will continue to play a key role in pediatric drug development contributing toward decisions pertaining to dose selection, trial designs, and assessing disease similarity to adults to support extrapolation of efficacy.

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“…During the development of the PBPK model, prior knowledge of the biological system is often used to help identify the behavior of drugs in different systems, such as children and patients with decreases in renal function (12,38,39). This PBPK analysis, on the other hand, showcases the potential of using the drug information to help understand the system.…”

Section: Discussionmentioning

confidence: 99%

Development of a Physiologically Based Pharmacokinetic Model to Predict Disease-Mediated Therapeutic Protein–Drug Interactions: Modulation of Multiple Cytochrome P450 Enzymes by Interleukin-6

Jiang

Zhuang

et al. 2016

AAPS J

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Abstract. Disease-mediated therapeutic protein-drug interactions have recently gained attention from regulatory agencies and pharmaceutical industries in the development of new biological products. In this study, we developed a physiologically based pharmacokinetic (PBPK) model using SimCYP to predict the impact of elevated interleukin-6 (IL-6) levels on cytochrome P450 (CYP) enzymes and the treatment effect of an anti-IL-6 monoclonal antibody, sirukumab, in patients with rheumatoid arthritis (RA). A virtual RA patient population was first constructed by incorporating the impact of systemic IL-6 level on hepatic and intestinal expression of multiple CYP enzymes with information from in vitro studies. Then, a PBPK model for CYP enzyme substrates was developed for healthy adult subjects. After incorporating the virtual RA patient population, the PBPK model was applied to quantitatively predict pharmacokinetics of multiple CYP substrates in RA patients before and after sirukumab treatment from a clinical cocktail drug interaction study. The results suggested that, compared with observed clinical data, changes in systemic exposure to multiple CYP substrates by anti-IL-6 treatment in virtual RA patients have been reasonably captured by the PBPK model, as manifested by modulations in area under plasma concentration versus time curves for midazolam, omeprazole, S-warfarin, and caffeine. This PBPK model reasonably captured the modulation effect of IL-6 and sirukumab on activity of CYP3A, CYP2C9, CYP2C19, and CYP1A2 and holds the potential to be utilized to assess the modulation effect of sirukumab on the metabolism and pharmacokinetics of concomitant small-molecule drugs in RA patients.

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Application of Physiologically Based Pharmacokinetic Modeling to Predict Acetaminophen Metabolism and Pharmacokinetics in Children

Cited by 96 publications

References 49 publications

Age-Dependent Absolute Abundance of Hepatic Carboxylesterases (CES1 and CES2) by LC-MS/MS Proteomics: Application to PBPK Modeling of Oseltamivir In Vivo Pharmacokinetics in Infants

Age-Dependent Absolute Abundance of Hepatic Carboxylesterases (CES1 and CES2) by LC-MS/MS Proteomics: Application to PBPK Modeling of Oseltamivir In Vivo Pharmacokinetics in Infants

Role of Quantitative Clinical Pharmacology in Pediatric Approval and Labeling

Development of a Physiologically Based Pharmacokinetic Model to Predict Disease-Mediated Therapeutic Protein–Drug Interactions: Modulation of Multiple Cytochrome P450 Enzymes by Interleukin-6

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