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Zhang W, Zhang Q, Cao Z, Zheng L, Hu W. Physiologically Based Pharmacokinetic Modeling in Neonates: Current Status and Future Perspectives. Pharmaceutics 2023; 15:2765. [PMID: 38140105 PMCID: PMC10747965 DOI: 10.3390/pharmaceutics15122765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/07/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
Rational drug use in special populations is a clinical problem that doctors and pharma-cists must consider seriously. Neonates are the most physiologically immature and vulnerable to drug dosing. There is a pronounced difference in the anatomical and physiological profiles be-tween neonates and older people, affecting the absorption, distribution, metabolism, and excretion of drugs in vivo, ultimately leading to changes in drug concentration. Thus, dose adjustments in neonates are necessary to achieve adequate therapeutic concentrations and avoid drug toxicity. Over the past few decades, modeling and simulation techniques, especially physiologically based pharmacokinetic (PBPK) modeling, have been increasingly used in pediatric drug development and clinical therapy. This rigorously designed and verified model can effectively compensate for the deficiencies of clinical trials in neonates, provide a valuable reference for clinical research design, and even replace some clinical trials to predict drug plasma concentrations in newborns. This review introduces previous findings regarding age-dependent physiological changes and pathological factors affecting neonatal pharmacokinetics, along with their research means. The application of PBPK modeling in neonatal pharmacokinetic studies of various medications is also reviewed. Based on this, we propose future perspectives on neonatal PBPK modeling and hope for its broader application.
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Affiliation(s)
| | | | | | - Liang Zheng
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (W.Z.); (Q.Z.); (Z.C.)
| | - Wei Hu
- Department of Clinical Pharmacology, The Second Affiliated Hospital of Anhui Medical University, Hefei 230601, China; (W.Z.); (Q.Z.); (Z.C.)
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2
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Dinh J, Johnson TN, Grimstein M, Lewis T. Physiologically Based Pharmacokinetics Modeling in the Neonatal Population-Current Advances, Challenges, and Opportunities. Pharmaceutics 2023; 15:2579. [PMID: 38004559 PMCID: PMC10675397 DOI: 10.3390/pharmaceutics15112579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 10/24/2023] [Accepted: 10/29/2023] [Indexed: 11/26/2023] Open
Abstract
Physiologically based pharmacokinetic (PBPK) modeling is an approach to predicting drug pharmacokinetics, using knowledge of the human physiology involved and drug physiochemical properties. This approach is useful when predicting drug pharmacokinetics in under-studied populations, such as pediatrics. PBPK modeling is a particularly important tool for dose optimization for the neonatal population, given that clinical trials rarely include this patient population. However, important knowledge gaps exist for neonates, resulting in uncertainty with the model predictions. This review aims to outline the sources of variability that should be considered with developing a neonatal PBPK model, the data that are currently available for the neonatal ontogeny, and lastly to highlight the data gaps where further research would be needed.
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Affiliation(s)
- Jean Dinh
- Certara UK Limited, Sheffield S1 2BJ, UK; (J.D.); (T.N.J.)
| | | | - Manuela Grimstein
- Office of Clinical Pharmacology, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD 20903, USA
| | - Tamorah Lewis
- Pediatric Clinical Pharmacology & Toxicology, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada
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3
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Miners JO, Polasek TM, Hulin JA, Rowland A, Meech R. Drug-drug interactions that alter the exposure of glucuronidated drugs: Scope, UDP-glucuronosyltransferase (UGT) enzyme selectivity, mechanisms (inhibition and induction), and clinical significance. Pharmacol Ther 2023:108459. [PMID: 37263383 DOI: 10.1016/j.pharmthera.2023.108459] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Revised: 05/18/2023] [Accepted: 05/22/2023] [Indexed: 06/03/2023]
Abstract
Drug-drug interactions (DDIs) arising from the perturbation of drug metabolising enzyme activities represent both a clinical problem and a potential economic loss for the pharmaceutical industry. DDIs involving glucuronidated drugs have historically attracted little attention and there is a perception that interactions are of minor clinical relevance. This review critically examines the scope and aetiology of DDIs that result in altered exposure of glucuronidated drugs. Interaction mechanisms, namely inhibition and induction of UDP-glucuronosyltransferase (UGT) enzymes and the potential interplay with drug transporters, are reviewed in detail, as is the clinical significance of known DDIs. Altered victim drug exposure arising from modulation of UGT enzyme activities is relatively common and, notably, the incidence and importance of UGT induction as a DDI mechanism is greater than generally believed. Numerous DDIs are clinically relevant, resulting in either loss of efficacy or an increased risk of adverse effects, necessitating dose individualisation. Several generalisations relating to the likelihood of DDIs can be drawn from the known substrate and inhibitor selectivities of UGT enzymes, highlighting the importance of comprehensive reaction phenotyping studies at an early stage of drug development. Further, rigorous assessment of the DDI liability of new chemical entities that undergo glucuronidation to a significant extent has been recommended recently by regulatory guidance. Although evidence-based approaches exist for the in vitro characterisation of UGT enzyme inhibition and induction, the availability of drugs considered appropriate for use as 'probe' substrates in clinical DDI studies is limited and this should be research priority.
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Affiliation(s)
- John O Miners
- Discipline of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Flinders University, Adelaide, Australia.
| | - Thomas M Polasek
- Certara, Princeton, NJ, USA; Centre for Medicines Use and Safety, Monash University, Melbourne, Australia
| | - Julie-Ann Hulin
- Discipline of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Andrew Rowland
- Discipline of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Robyn Meech
- Discipline of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, Flinders University College of Medicine and Public Health, Flinders University, Adelaide, Australia
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Algharably EA, Kreutz R, Gundert-Remy U. Infant Exposure to Antituberculosis Drugs via Breast Milk and Assessment of Potential Adverse Effects in Breastfed Infants: Critical Review of Data. Pharmaceutics 2023; 15:pharmaceutics15041228. [PMID: 37111713 PMCID: PMC10143885 DOI: 10.3390/pharmaceutics15041228] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/04/2023] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
Infants of mothers treated for tuberculosis might be exposed to drugs via breast milk. The existing information on the exposure of breastfed infants lacks a critical review of the published data. We aimed to evaluate the quality of the existing data on antituberculosis (anti-TB) drug concentrations in the plasma and milk as a methodologically sound basis for the potential risk of breastfeeding under therapy. We performed a systematic search in PubMed for bedaquiline, clofazimine, cycloserine/terizidone, levofloxacin, linezolid, pretomanid/pa824, pyrazinamide, streptomycin, ethambutol, rifampicin and isoniazid, supplemented with update references found in LactMed®. We calculated the external infant exposure (EID) for each drug and compared it with the recommended WHO dose for infants (relative external infant dose) and assessed their potential to elicit adverse effects in the breastfed infant. Breast milk concentration data were mainly not satisfactory to properly estimate the EID. Most of the studies suffer from limitations in the sample collection, quantity, timing and study design. Infant plasma concentrations are extremely scarce and very little data exist documenting the clinical outcome in exposed infants. Concerns for potential adverse effects in breastfed infants could be ruled out for bedaquiline, cycloserine/terizidone, linezolid and pyrazinamide. Adequate studies should be performed covering the scenario in treated mothers, breast milk and infants.
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Affiliation(s)
- Engi Abdelhady Algharably
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
| | - Reinhold Kreutz
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
| | - Ursula Gundert-Remy
- Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Institute of Clinical Pharmacology and Toxicology, Charitéplatz 1, 10117 Berlin, Germany
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Milani N, Qiu N, Fowler S. Contribution of UGT Enzymes to Human Drug Metabolism Stereoselectivity: A Case Study of Medetomidine, RO5263397, Propranolol, and Testosterone. Drug Metab Dispos 2023; 51:306-317. [PMID: 36810196 DOI: 10.1124/dmd.122.001024] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
The enantiomeric forms of chiral compounds have identical physical properties but may vary greatly in their metabolism by individual enzymes. Enantioselectivity in UDP-glucuronosyl transferase (UGT) metabolism has been reported for a number of compounds and with different UGT isoforms involved. However, the impact of such individual enzyme results on overall clearance stereoselectivity is often not clear. The enantiomers of medetomidine, RO5263397, and propranolol and the epimers testosterone and epitestosterone exhibit more than a 10-fold difference in glucuronidation rates by individual UGT enzymes. In this study, we examined the translation of human UGT stereoselectivity to hepatic drug clearance considering the combination of multiple UGTs to overall glucuronidation, the contribution of other metabolic enzymes such as cytochrome P450s (P450s), and the potential for differences in protein binding and blood/plasma partitioning. For medetomidine and RO5263397, the high individual enzyme (UGT2B10) enantioselectivity translated into ∼3- to >10-fold differences in predicted human hepatic in vivo clearance. For propranolol, the UGT enantioselectivity was irrelevant in the context of high P450 metabolism. For testosterone, a complex picture emerged due to differential epimeric selectivity of various contributing enzymes and potential for extrahepatic metabolism. Quite different patterns of P450- and UGT-mediated metabolism were observed across species, as well as differences in stereoselectivity, indicating that extrapolation from human enzyme and tissue data are essential when predicting human clearance enantioselectivity. SIGNIFICANCE STATEMENT: Individual enzyme stereoselectivity illustrates the importance of three-dimensional drug-metabolizing enzyme-substrate interactions and is essential when considering the clearance of racemic drugs. However, translation from in vitro to in vivo can be challenging as contributions from multiple enzymes and enzyme classes must be combined with protein binding and blood/plasma partitioning data to estimate the net intrinsic clearance for each enantiomer. Preclinical species may be misleading as enzyme involvement and metabolism stereoselectivity can differ substantially.
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Affiliation(s)
- Nicolò Milani
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.M., N.Q., S.F.) and Department of Chemistry, Biology, and Biotechnology, University of Perugia, Perugia, Italy (N.M.)
| | - NaHong Qiu
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.M., N.Q., S.F.) and Department of Chemistry, Biology, and Biotechnology, University of Perugia, Perugia, Italy (N.M.)
| | - Stephen Fowler
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.M., N.Q., S.F.) and Department of Chemistry, Biology, and Biotechnology, University of Perugia, Perugia, Italy (N.M.)
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Ho H, Means S, Safaei S, Hunter PJ. In silico modeling for the hepatic circulation and transport: From the liver organ to lobules. WIREs Mech Dis 2023; 15:e1586. [PMID: 36131627 DOI: 10.1002/wsbm.1586] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 08/08/2022] [Accepted: 08/15/2022] [Indexed: 11/12/2022]
Abstract
The function of the liver depends critically on its blood supply. Numerous in silico models have been developed to study various aspects of the hepatic circulation, including not only the macro-hemodynamics at the organ level, but also the microcirculation at the lobular level. In addition, computational models of blood flow and bile flow have been used to study the transport, metabolism, and clearance of drugs in pharmacokinetic studies. These in silico models aim to provide insights into the liver organ function under both healthy and diseased states, and to assist quantitative analysis for surgical planning and postsurgery treatment. The purpose of this review is to provide an update on state-of-the-art in silico models of the hepatic circulation and transport processes. We introduce the numerical methods and the physiological background of these models. We also discuss multiscale frameworks that have been proposed for the liver, and their linkage with the large context of systems biology, systems pharmacology, and the Physiome project. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering Cardiovascular Diseases > Computational Models.
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Affiliation(s)
- Harvey Ho
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Shawn Means
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Soroush Safaei
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Peter John Hunter
- Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
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Wei Y, Wu D, Chen Y, Dong C, Qi J, Wu Y, Cai R, Zhou S, Li C, Niu L, Wu T, Xiao Y, Liu T. Population pharmacokinetics of mycophenolate mofetil in pediatric patients early after liver transplantation. Front Pharmacol 2022; 13:1002628. [PMID: 36313303 PMCID: PMC9608800 DOI: 10.3389/fphar.2022.1002628] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 09/30/2022] [Indexed: 11/13/2022] Open
Abstract
Objective: To investigate the factors influencing the pharmacokinetics of mycophenolate mofetil (MMF) in pediatric patients after liver transplantation, and to establish a population pharmacokinetics model, which can provide a reference for clinical dosage adjustment. Methods: A prospective study in a single center was performed on pediatric patients who were administrated with mycophenolate mofetil dispersible tablets (MMFdt) for at least 4 days after liver transplantation continuously. Blood samples were collected in ethylene diamine tetraacetic acid anticoagulant tubes before dosing and 0.5, 1, 2, 4, 8, and 12 h after the morning intake of MMFdt. The concentrations of mycophenolic acid (MPA) in plasma were assayed with a validated reverse-phase high-performance liquid chromatography method. UGT1A8 518C > G, UGT1A9 -275T > A, UGT1A9 -2152C > T, UGT2B7 211G > T, SLC O 1B1 521T > C polymorphism were determined by Sanger sequencing. Nonlinear mixed effects modeling was used to establish the population pharmacokinetics (PPK) model. The predictability and stability of the model were internally evaluated by the goodness of fit plots, visual prediction check, normalized prediction errors, and bootstraps. Results: A two-compartment model with first-order absorption and first-order elimination was established with 115 MPA concentrations from 20 pediatric patients. The final model were: CL/F (L/h) = 14.8×(WT/7.5)0.75×(DOSE/11.16)0.452×е0.06, Ka (h−1) = 2.02×(WT/7.5)−0.25, Vc/F (L) = 6.01×(WT/7.5), Vp/F (L) = 269 (fixed), Q/F (L/h) = 15.4×(WT/7.5)0.75×е1.39. Where CL/F was the apparent clearance rate, Ka was the absorption rate constant, Vc/F was the apparent distribution volume of the central compartment, Vp/F was the apparent distribution volume of the peripheral compartment, Q/F was the atrioventricular clearance rate, WT was the body weight of the subject, and DOSE was the MMFdt administered dose. The model indicated there was large inter-individual variability in CL/F and Q/F after multiple dosing of MMFdt. Internal evaluation results showed that the final model had good stability and prediction performance. Conclusion: A stable and predictive population pharmacokinetic model of MMFdt in pediatric patients after the early stage of liver transplantation was established. The pediatric patient’s weight and the dose of MMFdt can be a reference to adjust the MMFdt dose.
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Affiliation(s)
- Yinyi Wei
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Dongni Wu
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yiyu Chen
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- *Correspondence: Taotao Liu, ; Yiyu Chen,
| | - Chunqiang Dong
- Department of Organ Transplant, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jianying Qi
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yun Wu
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Rongda Cai
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Siru Zhou
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Chengxin Li
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Lulu Niu
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Tingqing Wu
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yang Xiao
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Taotao Liu
- Department of Pharmacy, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- *Correspondence: Taotao Liu, ; Yiyu Chen,
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Applications, Challenges, and Outlook for PBPK Modeling and Simulation: A Regulatory, Industrial and Academic Perspective. Pharm Res 2022; 39:1701-1731. [PMID: 35552967 DOI: 10.1007/s11095-022-03274-2] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 04/25/2022] [Indexed: 12/20/2022]
Abstract
Several regulatory guidances on the use of physiologically based pharmacokinetic (PBPK) analyses and physiologically based biopharmaceutics model(s) (PBBM(s)) have been issued. Workshops are routinely held, demonstrating substantial interest in applying these modeling approaches to address scientific questions in drug development. PBPK models and PBBMs have remarkably contributed to model-informed drug development (MIDD) such as anticipating clinical PK outcomes affected by extrinsic and intrinsic factors in general and specific populations. In this review, we proposed practical considerations for a "base" PBPK model construction and development, summarized current status, challenges including model validation and gaps in system models, and future perspectives in PBPK evaluation to assess a) drug metabolizing enzyme(s)- or drug transporter(s)- mediated drug-drug interactions b) dosing regimen prediction, sampling timepoint selection and dose validation in pediatric patients from newborns to adolescents, c) drug exposure in patients with renal and/or and hepatic organ impairment, d) maternal-fetal drug disposition during pregnancy, and e) pH-mediated drug-drug interactions in patients treated with proton pump inhibitors/acid-reducing agents (PPIs/ARAs) intended for gastric protection. Since PBPK can simulate outcomes in clinical studies with enrollment challenges or ethical issues, the impact of PBPK models on waivers and how to strengthen study waiver is discussed.
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Silva M, Kwok RKH. Use of Computational Toxicology Tools to Predict In Vivo Endpoints Associated with Mode of Action and the Endocannabinoid System: A Case Study with Chlorpyrifos, Chlorpyrifos-oxon and Δ9Tetrahydrocannabinol. Curr Res Toxicol 2022; 3:100064. [PMID: 35243363 PMCID: PMC8860916 DOI: 10.1016/j.crtox.2022.100064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 01/16/2022] [Accepted: 02/03/2022] [Indexed: 01/04/2023] Open
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Robin S, Hassine KB, Muthukumaran J, Jurkovic Mlakar S, Krajinovic M, Nava T, Uppugunduri CRS, Ansari M. A potential implication of UDP-glucuronosyltransferase 2B10 in the detoxification of drugs used in pediatric hematopoietic stem cell transplantation setting: an in silico investigation. BMC Mol Cell Biol 2022; 23:5. [PMID: 35062878 PMCID: PMC8781437 DOI: 10.1186/s12860-021-00402-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 12/22/2021] [Indexed: 12/19/2022] Open
Abstract
Background Sinusoidal occlusion syndrome (SOS) is a potentially severe complication following hematopoietic stem cell transplantation (HSCT) in pediatric patients. Treatment related risk factors such as intensity of conditioning, hepatotoxic co-medication and patient related factors such as genetic variants predispose individuals to develop SOS. The variant allele for SNP rs17146905 in UDP-glucuronosyl transferase 2B10 (UGT2B10) gene was correlated with the occurrence of SOS in an exome-wide association study. UGT2B10 is a phase II drug metabolizing enzyme involved in the N-glucuronidation of tertiary amine containing drugs. Methods To shed light on the functionality of UGT2B10 enzyme in the metabolism of drugs used in pediatric HSCT setting, we performed in silico screening against custom based library of putative ligands. First, a list of potential substrates for in silico analysis was prepared using a systematic consensus-based strategy. The list comprised of drugs and their metabolites used in pediatric HSCT setting. The three-dimensional structure of UGT2B10 was not available from the Research Collaboratory Structural Bioinformatics - Protein Data Bank (RCSB - PDB) repository and thus we predicted the first human UGT2B10 3D model by using multiple template homology modeling with MODELLER Version 9.2 and molecular docking calculations with AutoDock Vina Version 1.2 were implemented to quantify the estimated binding affinity between selected putative substrates or ligands and UGT2B10. Finally, we performed molecular dynamics simulations using GROMACS Version 5.1.4 to confirm the potential UGT2B10 ligands prioritized after molecular docking (exhibiting negative free binding energy). Results Four potential ligands for UGT2B10 namely acetaminophen, lorazepam, mycophenolic acid and voriconazole n-oxide intermediate were identified. Other metabolites of voriconazole satisfied the criteria of being possible ligands of UGT2B10. Except for bilirubin and 4-Hydroxy Voriconazole, all the ligands (particularly voriconazole and hydroxy voriconazole) are oriented in substrate binding site close to the co-factor UDP (mean ± SD; 0.72 ± 0.33 nm). Further in vitro screening of the putative ligands prioritized by in silico pipeline is warranted to understand the nature of the ligands either as inhibitors or substrates of UGT2B10. Conclusions These results may indicate the clinical and pharmacological relevance UGT2B10 in pediatric HSCT setting. With this systematic computational methodology, we provide a rational-, time-, and cost-effective way to identify and prioritize the interesting putative substrates or inhibitors of UGT2B10 for further testing in in vitro experiments. Supplementary Information The online version contains supplementary material available at 10.1186/s12860-021-00402-5.
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van der Heijden JEM, Freriksen JJM, de Hoop-Sommen MA, van Bussel LPM, Driessen SHP, Orlebeke AEM, Verscheijden LFM, Greupink R, de Wildt SN. Feasibility of a Pragmatic PBPK Modeling Approach: Towards Model-Informed Dosing in Pediatric Clinical Care. Clin Pharmacokinet 2022; 61:1705-1717. [PMID: 36369327 PMCID: PMC9651907 DOI: 10.1007/s40262-022-01181-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2022] [Indexed: 11/13/2022]
Abstract
BACKGROUND AND OBJECTIVE More than half of all drugs are still prescribed off-label to children. Pharmacokinetic (PK) data are needed to support off-label dosing, however for many drugs such data are either sparse or not representative. Physiologically-based pharmacokinetic (PBPK) models are increasingly used to study PK and guide dosing decisions. Building compound models to study PK requires expertise and is time-consuming. Therefore, in this paper, we studied the feasibility of predicting pediatric exposure by pragmatically combining existing compound models, developed e.g. for studies in adults, with a pediatric and preterm physiology model. METHODS Seven drugs, with various PK characteristics, were selected (meropenem, ceftazidime, azithromycin, propofol, midazolam, lorazepam, and caffeine) as a proof of concept. Simcyp® v20 was used to predict exposure in adults, children, and (pre)term neonates, by combining an existing compound model with relevant virtual physiology models. Predictive performance was evaluated by calculating the ratios of predicted-to-observed PK parameter values (0.5- to 2-fold acceptance range) and by visual predictive checks with prediction error values. RESULTS Overall, model predicted PK in infants, children and adolescents capture clinical data. Confidence in PBPK model performance was therefore considered high. Predictive performance tends to decrease when predicting PK in the (pre)term neonatal population. CONCLUSION Pragmatic PBPK modeling in pediatrics, based on compound models verified with adult data, is feasible. A thorough understanding of the model assumptions and limitations is required, before model-informed doses can be recommended for clinical use.
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Affiliation(s)
- Joyce E. M. van der Heijden
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Jolien J. M. Freriksen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Marika A. de Hoop-Sommen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands ,Royal Dutch Pharmacist Association, The Hague, The Netherlands
| | - Lianne P. M. van Bussel
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Sander H. P. Driessen
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Anne E. M. Orlebeke
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Laurens F. M. Verscheijden
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Rick Greupink
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands
| | - Saskia N. de Wildt
- Department of Pharmacology and Toxicology, Radboud Institute for Health Sciences, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA Nijmegen, The Netherlands ,Intensive Care and Department of Paediatric Surgery, Erasmus MC-Sophia Children’s Hospital, Rotterdam, The Netherlands
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Wang K, Jiang K, Wei X, Li Y, Wang T, Song Y. Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development. AAPS PharmSciTech 2021; 22:208. [PMID: 34312742 PMCID: PMC8312709 DOI: 10.1208/s12249-021-02076-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 06/16/2021] [Indexed: 12/30/2022] Open
Abstract
Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.
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Takahashi RH, Forrest WF, Smith AD, Badee J, Qiu N, Schmidt S, Collier AC, Parrott N, Fowler S. Characterization of Hepatic UDP-Glucuronosyltransferase Enzyme Abundance-Activity Correlations and Population Variability Using a Proteomics Approach and Comparison with Cytochrome P450 Enzymes. Drug Metab Dispos 2021; 49:760-769. [PMID: 34187837 DOI: 10.1124/dmd.121.000474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 06/24/2021] [Indexed: 11/22/2022] Open
Abstract
The expression of ten major drug-metabolizing UDP-glucuronosyltransferase (UGT) enzymes in a panel of 130 human hepatic microsomal samples was measured using a liquid chromatography-tandem mass spectrometry-based approach. Simultaneously, ten cytochromes P450 and P450 reductase were also measured, and activity-expression relationships were assessed for comparison. The resulting data sets demonstrated that, with the exception of UGT2B17, 10th to 90th percentiles of UGT expression spanned 3- to 8-fold ranges. These ranges were small relative to ranges of reported mean UGT enzyme expression across different laboratories. We tested correlation of UGT expression with enzymatic activities using selective probe substrates. A high degree of abundance-activity correlation (Spearman's rank correlation coefficient > 0.6) was observed for UGT1As (1A1, 3, 4, 6) and cytochromes P450. In contrast, protein abundance and activity did not correlate strongly for UGT1A9 and UGT2B enzymes (2B4, 7, 10, 15, and 17). Protein abundance was strongly correlated for UGTs 2B7, 2B10, and 2B15. We suggest a number of factors may contribute to these differences including incomplete selectivity of probe substrates, correlated expression of these UGT2B isoforms, and the impact of splice and polymorphic variants on the peptides used in proteomics analysis, and exemplify this in the case of UGT2B10. Extensive correlation analyses identified important criteria for validating the fidelity of proteomics and enzymatic activity approaches for assessing UGT variability, population differences, and ontogenetic changes. SIGNIFICANCE STATEMENT: Protein expression data allow detailed assessment of interindividual variability and enzyme ontogeny. This study has observed that expression and enzyme activity are well correlated for hepatic UGT1A enzymes and cytochromes P450. However, for the UGT2B family, caution is advised when assuming correlation of expression and activity as is often done in physiologically based pharmacokinetic modeling. This can be due to incomplete probe substrate specificities, but may also be related to presence of inactive UGT protein materials and the effect of splicing variations.
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Affiliation(s)
- Ryan H Takahashi
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - William F Forrest
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Alexander D Smith
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Justine Badee
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - NaHong Qiu
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Stephan Schmidt
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Abby C Collier
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Neil Parrott
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
| | - Stephen Fowler
- Department of Drug Metabolism and Pharmacokinetics (R.H.T.) and Department of OMNI Bioinformatics (W.F.F.), Genentech, Inc., South San Francisco, California; Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Research and Early Development, Roche Innovation Centre Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland (N.Q., N.P., S.F.); Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada (A.D.S., A.C.C.)
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Liu XI, van den Anker JN, Burckart GJ, Dallmann A. Evaluation of Physiologically Based Pharmacokinetic Models to Predict the Absorption of BCS Class I Drugs in Different Pediatric Age Groups. J Clin Pharmacol 2021; 61 Suppl 1:S94-S107. [PMID: 34185902 DOI: 10.1002/jcph.1845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2021] [Accepted: 02/17/2021] [Indexed: 11/06/2022]
Abstract
Age-related changes in many parameters affecting drug absorption remain poorly characterized. The objective of this study was to apply physiologically based pharmacokinetic (PBPK) models in pediatric patients to investigate the absorption and pharmacokinetics of 4 drugs belonging to the Biopharmaceutics Classification System (BCS) class I administered as oral liquid formulations. Pediatric PBPK models built with PK-Sim/MoBi were used to predict the pharmacokinetics of acetaminophen, emtricitabine, theophylline, and zolpidem in different pediatric populations. The model performance for predicting drug absorption and pharmacokinetics was assessed by comparing the predicted absorption profile with the deconvoluted dose fraction absorbed over time and predicted with observed plasma concentration-time profiles. Sensitivity analyses were performed to analyze the effects of changes in relevant input parameters on the model output. Overall, most pharmacokinetic parameters were predicted within a 2-fold error range. The absorption profiles were generally reasonably predicted, but relatively large differences were observed for acetaminophen. Sensitivity analyses showed that the predicted absorption profile was most sensitive to changes in the gastric emptying time (GET) and the specific intestinal permeability. The drug's solubility played only a minor role. These findings confirm that gastric emptying time, more than intestinal permeability or solubility, is a key factor affecting BCS class I drug absorption in children. As gastric emptying time is prolonged in the fed state, a better understanding of the interplay between food intake and gastric emptying time in children is needed, especially in the very young in whom the (semi)fed condition is the prevailing prandial state, and hence prolonged gastric emptying time seems more plausible than the fasting state.
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Affiliation(s)
- Xiaomei I Liu
- Division of Clinical Pharmacology, Children's National Hospital, Washington, District of Columbia, USA
| | - John N van den Anker
- Division of Clinical Pharmacology, Children's National Hospital, Washington, District of Columbia, USA.,Division of Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
| | - Gilbert J Burckart
- Office of Clinical Pharmacology, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - André Dallmann
- Pharmacometrics/Modeling & Simulation, Research & Development, Pharmaceuticals, Bayer AG, Leverkusen, Germany
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15
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van Groen BD, Nicolaï J, Kuik AC, Van Cruchten S, van Peer E, Smits A, Schmidt S, de Wildt SN, Allegaert K, De Schaepdrijver L, Annaert P, Badée J. Ontogeny of Hepatic Transporters and Drug-Metabolizing Enzymes in Humans and in Nonclinical Species. Pharmacol Rev 2021; 73:597-678. [PMID: 33608409 DOI: 10.1124/pharmrev.120.000071] [Citation(s) in RCA: 55] [Impact Index Per Article: 18.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
The liver represents a major eliminating and detoxifying organ, determining exposure to endogenous compounds, drugs, and other xenobiotics. Drug transporters (DTs) and drug-metabolizing enzymes (DMEs) are key determinants of disposition, efficacy, and toxicity of drugs. Changes in their mRNA and protein expression levels and associated functional activity between the perinatal period until adulthood impact drug disposition. However, high-resolution ontogeny profiles for hepatic DTs and DMEs in nonclinical species and humans are lacking. Meanwhile, increasing use of physiologically based pharmacokinetic (PBPK) models necessitates availability of underlying ontogeny profiles to reliably predict drug exposure in children. In addition, understanding of species similarities and differences in DT/DME ontogeny is crucial for selecting the most appropriate animal species when studying the impact of development on pharmacokinetics. Cross-species ontogeny mapping is also required for adequate translation of drug disposition data in developing nonclinical species to humans. This review presents a quantitative cross-species compilation of the ontogeny of DTs and DMEs relevant to hepatic drug disposition. A comprehensive literature search was conducted on PubMed Central: Tables and graphs (often after digitization) in original manuscripts were used to extract ontogeny data. Data from independent studies were standardized and normalized before being compiled in graphs and tables for further interpretation. New insights gained from these high-resolution ontogeny profiles will be indispensable to understand cross-species differences in maturation of hepatic DTs and DMEs. Integration of these ontogeny data into PBPK models will support improved predictions of pediatric hepatic drug disposition processes. SIGNIFICANCE STATEMENT: Hepatic drug transporters (DTs) and drug-metabolizing enzymes (DMEs) play pivotal roles in hepatic drug disposition. Developmental changes in expression levels and activities of these proteins drive age-dependent pharmacokinetics. This review compiles the currently available ontogeny profiles of DTs and DMEs expressed in livers of humans and nonclinical species, enabling robust interpretation of age-related changes in drug disposition and ultimately optimization of pediatric drug therapy.
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Affiliation(s)
- B D van Groen
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - J Nicolaï
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - A C Kuik
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - S Van Cruchten
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - E van Peer
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - A Smits
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - S Schmidt
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - S N de Wildt
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - K Allegaert
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - L De Schaepdrijver
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - P Annaert
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
| | - J Badée
- Intensive Care and Department of Pediatric Surgery, Erasmus MC-Sophia Children's Hospital, Rotterdam, The Netherlands (B.D.v.G., K.A.); Development Science, UCB BioPharma SRL, Braine-l'Alleud, Belgium (J.N.); Leiden Academic Center for Drug Research, Leiden University, Leiden, The Netherlands (A.C.K.); Department of Veterinary Sciences, Faculty of Pharmaceutical, Biomedical and Veterinary Sciences, University of Antwerp, Wilrijk, Belgium (S.V.C.); Fendigo sa/nvbv, An Alivira Group Company, Brussels, Belgium (E.v.P.); Department of Development and Regeneration KU Leuven, Leuven, Belgium (A.S.); Neonatal intensive care unit, University Hospitals Leuven, Leuven, Belgium (A.S.); Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida (S.S.); Department of Pharmacology and Toxicology, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands (S.N.d.W.); Departments of Development and Regeneration and of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (K.A.); Department of Hospital Pharmacy, Erasmus MC, University Medical Center, Rotterdam, The Netherlands (K.A.); Nonclinical Safety, Janssen R&D, Beerse, Belgium (L.D.S.); Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium (P.A.); and Department of PK Sciences, Novartis Institutes for BioMedical Research, Basel, Switzerland (J.B.)
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16
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Jo H, Pilla Reddy V, Parkinson J, Boulton DW, Tang W. Model-Informed Pediatric Dose Selection for Dapagliflozin by Incorporating Developmental Changes. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 10:108-118. [PMID: 33439535 PMCID: PMC7894404 DOI: 10.1002/psp4.12577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 11/09/2020] [Indexed: 11/10/2022]
Abstract
This analysis reports a quantitative modeling and simulation approach for oral dapagliflozin, a primarily uridine diphosphate-glucuronosyltransferase (UGT)-metabolized human sodium-glucose cotransporter 2 selective inhibitor. A mechanistic dapagliflozin physiologically based pharmacokinetic (PBPK) model was developed using in vitro metabolism and clinical pharmacokinetic (PK) data and verified for context of use (e.g., exposure predictions in pediatric subjects aged 1 month to 18 years). Dapagliflozin exposure is challenging to predict in pediatric populations owing to differences in UGT1A9 ontogeny maturation and paucity of clinical PK data in younger age groups. Based on the exposure-response relationship of dapagliflozin, twofold acceptance criteria were applied between model-predicted and observed drug exposures and PK parameters (area under the curve and maximum drug concentration) in various scenarios, including monotherapy in healthy adults (single/multiple dose), monotherapy in hepatically or renally impaired patients, and drug-drug interactions with UGT1A9 modulators, such as mefenamic acid and rifampin. The PBPK model captured the observed exposure within twofold of the observed monotherapy data in adults and adolescents and in special population. As a guide to determining dosing regimens in pediatric studies, the verified PBPK model, along with UGT enzyme ontogeny maturation understanding, was used for predictions of dapagliflozin monotherapy exposures in pediatric subjects aged 1 month to 18 years that best matched exposure in adult patients with a 10-mg single dose of dapagliflozin.
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Affiliation(s)
- Heeseung Jo
- Modelling and Simulation, Early Oncology, Oncology R&D, AstraZeneca, Cambridge, UK
| | - Venkatesh Pilla Reddy
- Modelling and Simulation, Early Oncology, Oncology R&D, AstraZeneca, Cambridge, UK.,Clinical Pharmacology and Quantitative Pharmacology, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK
| | - Joanna Parkinson
- Clinical Pharmacology and Quantitative Pharmacology, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - David W Boulton
- Clinical Pharmacology and Quantitative Pharmacology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA
| | - Weifeng Tang
- Clinical Pharmacology and Quantitative Pharmacology, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, Maryland, USA
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17
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Zhou J, Argikar UA, Miners JO. Enzyme Kinetics of Uridine Diphosphate Glucuronosyltransferases (UGTs). Methods Mol Biol 2021; 2342:301-338. [PMID: 34272700 DOI: 10.1007/978-1-0716-1554-6_12] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Glucuronidation, catalyzed by uridine diphosphate glucuronosyltransferases (UGTs), is an important process for the metabolism and clearance of many lipophilic chemicals, including drugs, environmental chemicals, and endogenous compounds. Glucuronidation is a bisubstrate reaction that requires the aglycone and the cofactor, UDP-GlcUA. Accumulating evidence suggests that the bisubstrate reaction follows a compulsory-order ternary mechanism. To simplify the kinetic modeling of glucuronidation reactions in vitro, UDP-GlcUA is usually added to incubations in large excess. Many factors have been shown to influence UGT activity and kinetics in vitro, and these must be accounted for during experimental design and data interpretation. While the assessment of drug-drug interactions resulting from UGT inhibition has been challenging in the past, the increasing availability of UGT enzyme-selective substrate and inhibitor "probes" provides the prospect for more reliable reaction phenotyping and assessment of drug-drug interaction potential. Although extrapolation of the in vitro intrinsic clearance of a glucuronidated drug often underpredicts in vivo clearance, careful selection of in vitro experimental conditions and inclusion of extrahepatic glucuronidation may improve the predictivity of in vitro-in vivo extrapolation. Physiologically based pharmacokinetic (PBPK) modeling has also shown to be of value for predicting PK of drugs eliminated by glucuronidation.
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Affiliation(s)
- Jin Zhou
- Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, CT, USA.
| | - Upendra A Argikar
- Translational Medicine, Novartis Institutes for BioMedical Research, Inc., Cambridge, MA, USA
| | - John O Miners
- Department of Clinical Pharmacology, College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
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18
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Dickinson L, Walimbwa S, Singh Y, Kaboggoza J, Kintu K, Sihlangu M, Coombs JA, Malaba TR, Byamugisha J, Pertinez H, Amara A, Gini J, Else L, Heiberg C, Hodel EM, Reynolds H, Myer L, Waitt C, Khoo S, Lamorde M, Orrell C. Infant exposure to dolutegravir through placental and breastmilk transfer: a population pharmacokinetic analysis of DolPHIN-1. Clin Infect Dis 2020; 73:e1200-e1207. [PMID: 33346335 PMCID: PMC8423479 DOI: 10.1093/cid/ciaa1861] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Rapid reduction of HIV viral load is paramount to prevent peripartum transmission in women diagnosed late in pregnancy. We investigated dolutegravir population pharmacokinetics in maternal plasma, cord, breastmilk and infant plasma of DolPHIN-1 participants (NCT02245022) presenting with untreated HIV late in pregnancy (28-36 weeks gestation). METHODS Pregnant women from Uganda and South Africa were randomised (1:1) to daily dolutegravir (50 mg) or efavirenz-based therapy. Dolutegravir pharmacokinetic sampling (0-24 hours) was undertaken 14 days after treatment initiation and within 1-3 weeks of delivery, with matched maternal and cord samples at delivery. Mothers switched to efavirenz and maternal and infant plasma and breastmilk samples taken 24, 48 or 72 hours post-switch. Nonlinear mixed effects (NONMEM v. 7.4) was used to describe dolutegravir in all matrices and to evaluate covariates. RESULTS Twenty-eight women and 22 infants were included. Maternal dolutegravir was described by a two-compartment model linked to a fetal and breastmilk compartment. Cord and breastmilk to maternal plasma ratios were 1.279 (1.209-1.281) and 0.033 (0.021-0.050), respectively. Infant dolutegravir was described by breastmilk-to-infant and infant elimination rate constants. No covariate effects were observed. Predicted infant dolutegravir half-life and time to protein adjusted-IC90 (0.064 mg/L) for those above this threshold were 37.9 hours (22.1-63.5) and 108.9 hours [(18.6-129.6); 4.5 days (0.8-5.4); n=13]. CONCLUSIONS Breastfeeding contributed relatively little to infant plasma exposures but a median of 4.5 days additional prophylaxis to some of the breastfed infants was observed following maternal dolutegravir cessation (3-15 days postpartum), which waned with time postpartum as transplacental dolutegravir cleared.
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Affiliation(s)
- Laura Dickinson
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Stephen Walimbwa
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Yashna Singh
- Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa
| | - Julian Kaboggoza
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Kenneth Kintu
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Mary Sihlangu
- Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa
| | - Julie-Anne Coombs
- Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa
| | - Thokozile R Malaba
- Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Josaphat Byamugisha
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Henry Pertinez
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Alieu Amara
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Joshua Gini
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Laura Else
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Christie Heiberg
- Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa
| | - Eva Maria Hodel
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Helen Reynolds
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Landon Myer
- Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Cape Town, South Africa
| | - Catriona Waitt
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Saye Khoo
- Department of Molecular & Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Mohammed Lamorde
- Infectious Diseases Institute, Makerere University College of Health Sciences, Kampala, Uganda
| | - Catherine Orrell
- Desmond Tutu HIV Foundation, University of Cape Town, Cape Town, South Africa
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19
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Sandra L, Smits A, Allegaert K, Nicolaï J, Annaert P, Bouillon T. Population pharmacokinetics of propofol in neonates and infants: Gestational and postnatal age to determine clearance maturation. Br J Clin Pharmacol 2020; 87:2089-2097. [PMID: 33085795 DOI: 10.1111/bcp.14620] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Revised: 08/31/2020] [Accepted: 09/12/2020] [Indexed: 11/28/2022] Open
Abstract
AIMS Develop a population pharmacokinetic model describing propofol pharmacokinetics in (pre)term neonates and infants, that can be used for precision dosing (e.g. during target-controlled infusion) of propofol in this population. METHODS A nonlinear mixed effects pharmacokinetic analysis (Monolix 2018R2) was performed, based on a pooled study population in 107 (pre)term neonates and infants. RESULTS In total, 836 blood samples were collected from 66 (pre)term neonates and 41 infants originating from 3 studies. Body weight (BW) of the pooled study population was 3.050 (0.580-11.440) kg, postmenstrual age (PMA) was 36.56 (27.00-43.00) weeks and postnatal age (PNA) was 1.14 (0-104.00) weeks (median and min-max range). A 3-compartment structural model was identified and the effect of BW was modelled using fixed allometric exponents. Elimination clearance maturation was modelled accounting for the maturational effect on elimination clearance until birth (by gestational age [GA]) and postpartum (by PNA and GA). The extrapolated adult (70 kg) population propofol elimination clearance (1.64 L min-1 , estimated relative standard error = 6.02%) is in line with estimates from previous population pharmacokinetic studies. Empirical scaling of BW on the central distribution volume in function of PNA improved the model fit. CONCLUSIONS It is recommended to describe elimination clearance maturation by GA and PNA instead of PMA on top of size effects when analyzing propofol pharmacokinetics in populations including preterm neonates. Changes in body composition in addition to weight changes or other physio-anatomical changes may explain the changes in central distribution volume. The developed model may serve as a prior for propofol dose finding and target-controlled infusion in (preterm) neonates.
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Affiliation(s)
- Louis Sandra
- Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, Leuven, Belgium
| | - Anne Smits
- KU Leuven Department of Development and Regeneration, Leuven, Belgium.,Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium
| | - Karel Allegaert
- KU Leuven Department of Development and Regeneration, Leuven, Belgium.,Division of Clinical Pharmacy, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Johan Nicolaï
- Development Science, UCB BioPharma SPRL, Braine-l'Alleud, Belgium
| | - Pieter Annaert
- Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, Leuven, Belgium
| | - Thomas Bouillon
- Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, Leuven, Belgium.,Bionotus, Niel, Belgium
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20
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Miners JO, Rowland A, Novak JJ, Lapham K, Goosen TC. Evidence-based strategies for the characterisation of human drug and chemical glucuronidation in vitro and UDP-glucuronosyltransferase reaction phenotyping. Pharmacol Ther 2020; 218:107689. [PMID: 32980440 DOI: 10.1016/j.pharmthera.2020.107689] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Revised: 09/17/2020] [Accepted: 09/18/2020] [Indexed: 12/26/2022]
Abstract
Enzymes of the UDP-glucuronosyltransferase (UGT) superfamily contribute to the elimination of drugs from almost all therapeutic classes. Awareness of the importance of glucuronidation as a drug clearance mechanism along with increased knowledge of the enzymology of drug and chemical metabolism has stimulated interest in the development and application of approaches for the characterisation of human drug glucuronidation in vitro, in particular reaction phenotyping (the fractional contribution of the individual UGT enzymes responsible for the glucuronidation of a given drug), assessment of metabolic stability, and UGT enzyme inhibition by drugs and other xenobiotics. In turn, this has permitted the implementation of in vitro - in vivo extrapolation approaches for the prediction of drug metabolic clearance, intestinal availability, and drug-drug interaction liability, all of which are of considerable importance in pre-clinical drug development. Indeed, regulatory agencies (FDA and EMA) require UGT reaction phenotyping for new chemical entities if glucuronidation accounts for ≥25% of total metabolism. In vitro studies are most commonly performed with recombinant UGT enzymes and human liver microsomes (HLM) as the enzyme sources. Despite the widespread use of in vitro approaches for the characterisation of drug and chemical glucuronidation by HLM and recombinant enzymes, evidence-based guidelines relating to experimental approaches are lacking. Here we present evidence-based strategies for the characterisation of drug and chemical glucuronidation in vitro, and for UGT reaction phenotyping. We anticipate that the strategies will inform practice, encourage development of standardised experimental procedures where feasible, and guide ongoing research in the field.
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Affiliation(s)
- John O Miners
- Department of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, College of Medicine and Public Health, Flinders University, Adelaide, Australia.
| | - Andrew Rowland
- Department of Clinical Pharmacology and Flinders Centre for Innovation in Cancer, College of Medicine and Public Health, Flinders University, Adelaide, Australia
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21
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Badée J, Qiu N, Collier AC, Takahashi RH, Forrest WF, Parrott N, Schmidt S, Fowler S. Characterization of the Ontogeny of Hepatic UDP-Glucuronosyltransferase Enzymes Based on Glucuronidation Activity Measured in Human Liver Microsomes. J Clin Pharmacol 2020; 59 Suppl 1:S42-S55. [PMID: 31502688 DOI: 10.1002/jcph.1493] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 06/26/2019] [Indexed: 02/06/2023]
Abstract
An understanding of the postnatal development of hepatic UDP-glucuronosyltransferase (UGT) enzymes is required for accurate prediction of the age-dependent changes in pharmacokinetics of many drugs used in children. However, the maturation rate of hepatic UGT isoforms remains a major knowledge gap. This study aimed to establish the age-associated changes in glucuronidation activity of 10 major hepatic UGT isoforms in humans, namely, UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17. Human liver microsomes from pediatric and adult donors were incubated under optimized incubation conditions to assess the activity rates of hepatic UGT isoforms using a panel of 19 in vitro UGT probe substrates and clinically used drugs. Statistically strong correlations of glucuronidation activities allowed the ontogeny of UGT1A1, UGT1A4, UGT2B7, UGT2B10, and UGT2B15 to be established using multiple selective UGT substrates and matched human liver microsome samples. The postnatal development of hepatic UGTs is isoform-dependent using either individual or cross-correlated selective isoform substrates. Maximal adult activity was reached at different times ranging from within a month (UGT1A1, UGT2B4, UGT2B7, UGT2B10, and UGT2B15), during infancy (UGT1A3, UGT1A4, and UGT1A9), to adolescence (UGT1A6 and UGT2B17). This study provides an extensive characterization of the postnatal ontogeny profiles of hepatic UGT enzymes that are instrumental for predicting drug disposition via in vitro-in vivo extrapolation algorithms and verifying pharmacokinetic predictions against in vivo observations via pediatric physiologically based pharmacokinetic modeling in pediatric patients.
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Affiliation(s)
- Justine Badée
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida, USA
| | - Nahong Qiu
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland
| | - Abby C Collier
- Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Ryan H Takahashi
- Department of Drug Metabolism and Pharmacokinetics, Genentech, Inc., South San Francisco, California, USA
| | - William F Forrest
- Department of Bioinformatics and Computational Biology, Genentech, Inc., South San Francisco, California, USA
| | - Neil Parrott
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland
| | - Stephan Schmidt
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida, USA
| | - Stephen Fowler
- Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland
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22
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Ince I, Solodenko J, Frechen S, Dallmann A, Niederalt C, Schlender J, Burghaus R, Lippert J, Willmann S. Predictive Pediatric Modeling and Simulation Using Ontogeny Information. J Clin Pharmacol 2020; 59 Suppl 1:S95-S103. [PMID: 31502689 DOI: 10.1002/jcph.1497] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 07/01/2019] [Indexed: 12/19/2022]
Abstract
Food and Drug Administration submissions of physiologically based pharmacokinetic (PBPK) modeling and simulation of small-molecule drugs document the relevance of pediatric drug development and, in particular, information on dosing strategies in children. The most relevant prerequisite for reliable PBPK-based translation of adult pharmacokinetics of a small molecule to children is knowledge of the drug-specific absorption, distribution, metabolism, and elimination (ADME) processes in adults together with existing information about ontogeny of ADME processes relevant for the drug. All mechanisms driving a drug's clearance are of specific importance. For other drug modalities, our knowledge of ADME processes and ontogeny is still limited. More research is required, for example, to understand why some therapeutic proteins show complex differences in pharmacokinetics between adults and children, whereas other proteins seem to follow simple allometric scaling rules. Ontogeny information originates from various sources, such as (semi)quantitative mRNA expression, in vitro activity data, and deconvolution of in vivo pharmacokinetic data. The workflow for pediatric predictions is well described in several articles documenting successful translation from adults to children. The technical hurdles for PBPK modeling are low. State-of-the-art PBPK modeling software tools provide integrated pediatric translation workflows. For example, PK-Sim and MoBi are freely available as fully transparent open-source software via Open Systems Pharmacology (OSP). With the latest 2019 software release, version 8.0, OSP even provides a fully integrated technical framework for the qualification (and requalification) of any specific intended PBPK use in line with Food and Drug Administration and European Medicines Agency PBPK guidance. Qualification packages for pediatric translation are available on the OSP platform.
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Affiliation(s)
- Ibrahim Ince
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Juri Solodenko
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Sebastian Frechen
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - André Dallmann
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Christoph Niederalt
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Jan Schlender
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Rolf Burghaus
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Jörg Lippert
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
| | - Stefan Willmann
- Clinical Pharmacometrics, Research & Development, Pharmaceuticals, Bayer AG, Germany
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23
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Use of computational toxicology (CompTox) tools to predict in vivo toxicity for risk assessment. Regul Toxicol Pharmacol 2020; 116:104724. [PMID: 32640296 DOI: 10.1016/j.yrtph.2020.104724] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/20/2020] [Accepted: 06/30/2020] [Indexed: 12/19/2022]
Abstract
Computational Toxicology tools were used to predict toxicity for three pesticides: propyzamide (PZ), carbaryl (CB) and chlorpyrifos (CPF). The tools used included: a) ToxCast/Tox21 assays (AC50 s μM: concentration 50% maximum activity); b) in vitro-to-in vivo extrapolation (IVIVE) using ToxCast/Tox21 AC50s to predict administered equivalent doses (AED: mg/kg/d) to compare to known in vivo Lowest-Observed-Effect-Level (LOEL)/Benchmark Dose (BMD); c) high throughput toxicokinetics population based (HTTK-Pop) using AC50s for endpoints associated with the mode of action (MOA) to predict age-adjusted AED for comparison with in vivo LOEL/BMDs. ToxCast/Tox21 active-hit-calls for each chemical were predictive of targets associated with each MOA, however, assays directly relevant to the MOAs for each chemical were limited. IVIVE AEDs were predictive of in vivo LOEL/BMD10s for all three pesticides. HTTK-Pop was predictive of in vivo LOEL/BMD10s for PZ and CPF but not for CB after human age adjustments 11-15 (PZ) and 6-10 (CB) or 6-10 and 11-20 (CPF) corresponding to treated rat ages (in vivo endpoints). The predictions of computational tools are useful for risk assessment to identify targets in chemical MOAs and to support in vivo endpoints. Data can also aid is decisions about the need for further studies.
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24
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Adiwidjaja J, Boddy AV, McLachlan AJ. Physiologically-Based Pharmacokinetic Predictions of the Effect of Curcumin on Metabolism of Imatinib and Bosutinib: In Vitro and In Vivo Disconnect. Pharm Res 2020; 37:128. [PMID: 32529309 DOI: 10.1007/s11095-020-02834-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2019] [Accepted: 04/26/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE This study aimed to investigate the potential pharmacokinetic interactions between curcumin, imatinib and bosutinib, combining In Vitro and in silico methods. METHODS In Vitro metabolism of imatinib and bosutinib were investigated in pooled human liver microsomes and recombinant CYP3A4 enzyme in the presence and absence of curcumin and curcumin glucuronide using an LC-MS/MS assay for N-desmethyl metabolites. A physiologically-based pharmacokinetic (PBPK) model for curcumin formulated as solid lipid nanoparticles (SLN) was constructed using In Vitro glucuronidation kinetics and published clinical pharmacokinetic data. The potential effects of curcumin coadministration on systemic exposures of imatinib and bosutinib were predicted in silico using PBPK simulations. RESULTS Curcumin demonstrated potent reversible inhibition of cytochrome P450 (CYP)3A4-mediated N-demethylation of imatinib and bosutinib and CYP2C8-mediated metabolism of imatinib with inhibitory constants (ki,u) of ≤1.5 μmol. L-1. A confirmatory In Vitro study with paclitaxel, the 6α-hydroxylation of which is exclusively mediated by CYP2C8, was consistent with a potent inhibition of this enzyme by curcumin. Curcumin glucuronide also inhibited both CYP enzymes In Vitro, albeit to a lesser extent than that of curcumin. PBPK model simulations predicted that at recommended dosing regimens of SLN curcumin, coadministration would result in an increase in systemic exposures of imatinib and bosutinib of up to only 10%. CONCLUSION A PBPK model for curcumin in a SLN formulation was successfully developed. Although curcumin possesses a strong In Vitro inhibitory activity towards CYP3A4 and CYP2C8 enzymes, its interactions with imatinib and bosutinib were unlikely to be of clinical importance due to curcumin's poor bioavailability.
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Affiliation(s)
- Jeffry Adiwidjaja
- Sydney Pharmacy School, The University of Sydney, Sydney, NSW, 2006, Australia.
| | - Alan V Boddy
- School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, SA, 5001, Australia
- University of South Australia Cancer Research Institute, University of South Australia, Adelaide, SA, 5000, Australia
| | - Andrew J McLachlan
- Sydney Pharmacy School, The University of Sydney, Sydney, NSW, 2006, Australia
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Zhang S, Zhang E, Ho H. Extrapolation for a pharmacokinetic model for acetaminophen from adults to neonates: A Latin Hypercube Sampling analysis. Drug Metab Pharmacokinet 2020; 35:329-333. [PMID: 32307228 DOI: 10.1016/j.dmpk.2020.03.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2019] [Revised: 02/24/2020] [Accepted: 03/24/2020] [Indexed: 02/02/2023]
Abstract
Physiological and drug-specific parameters need to be adjusted when extrapolating a pharmacokinetic (PK) model from adults to neonates, so as to reproduce the time profiles of the studied drug(s) consistent with clinical, in vivo data or in vitro cell line measurements. In this paper we present a parameter analysis method, i.e. the Latin Hypercube Sampling (LHS) method for an acetaminophen (APAP) PK model. The original model consists of two compartments (the blood and the urine) with Michaelis-Menten kinetic parameters determined for APAP and its metabolites. The physiological parameters are scaled through allometric laws from adults to neonates, and APAP-specific parameters are adjusted for enzymatic maturational changes. The LHS method is used to statistically investigate the interplay between these parameters. The results for the extrapolated APAP model are consistent with published APAP PK data in neonates. We found the sulphation clearance parameter played a crucial role in the neonatal PK model, but its influence was weakened if the volume of distribution parameters were included. We suggest that this kind of in silico experiment could be valuable as the first step in PK model extrapolation between different ages.
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Affiliation(s)
- S Zhang
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand
| | - E Zhang
- Chongqing Institute for Food and Drug Control, Chongqing City, China
| | - H Ho
- Auckland Bioengineering Institute, The University of Auckland, Auckland, 1010, New Zealand.
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Liu Y, Badée J, Takahashi RH, Schmidt S, Parrott N, Fowler S, Mackenzie PI, Coughtrie MWH, Collier AC. Coexpression of Human Hepatic Uridine Diphosphate Glucuronosyltransferase Proteins: Implications for Ontogenetic Mechanisms and Isoform Coregulation. J Clin Pharmacol 2019; 60:722-733. [DOI: 10.1002/jcph.1571] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 12/02/2019] [Indexed: 11/12/2022]
Affiliation(s)
- Yuejian Liu
- Faculty of Pharmaceutical SciencesThe University of British Columbia Vancouver British Columbia Canada
| | - Justine Badée
- Novartis Institutes for BioMedical Research–Translational Medicine PK Sciences–Modeling & Simulation PBPK Novartis Campus Basel Switzerland
| | | | - Stephan Schmidt
- Center for Pharmacometrics & Systems PharmacologyDepartment of Pharmaceutics Lake Nona (Orlando)University of Florida Orlando Florida USA
| | - Neil Parrott
- Pharmaceutical SciencesRoche Pharma Research and Early DevelopmentRoche Innovation Centre Basel Basel Switzerland
| | - Stephen Fowler
- Pharmaceutical SciencesRoche Pharma Research and Early DevelopmentRoche Innovation Centre Basel Basel Switzerland
| | - Peter I. Mackenzie
- Department of Clinical PharmacologyFlinders University of South Australia Adelaide Australia
| | - Michael W. H. Coughtrie
- Faculty of Pharmaceutical SciencesThe University of British Columbia Vancouver British Columbia Canada
| | - Abby C. Collier
- Faculty of Pharmaceutical SciencesThe University of British Columbia Vancouver British Columbia Canada
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Quantitative mass spectrometry-based proteomics in the era of model-informed drug development: Applications in translational pharmacology and recommendations for best practice. Pharmacol Ther 2019; 203:107397. [DOI: 10.1016/j.pharmthera.2019.107397] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 07/29/2019] [Indexed: 02/08/2023]
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Badée J, Qiu N, Parrott N, Collier AC, Schmidt S, Fowler S. Optimization of Experimental Conditions of Automated Glucuronidation Assays in Human Liver Microsomes Using a Cocktail Approach and Ultra-High Performance Liquid Chromatography-Tandem Mass Spectrometry. Drug Metab Dispos 2018; 47:124-134. [PMID: 30478159 DOI: 10.1124/dmd.118.084301] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2018] [Accepted: 11/20/2018] [Indexed: 11/22/2022] Open
Abstract
UDP-glucuronosyltransferase (UGT)-mediated metabolism is possibly the most important conjugation reaction for marketed drugs. However, there are currently no generally accepted standard incubation conditions for UGT microsomal assays, and substantial differences in experimental design and methodology between laboratories hinder cross-study comparison of in vitro activities. This study aimed to define optimal experimental conditions to determine glucuronidation activity of multiple UGT isoforms simultaneously using human liver microsomes. Hepatic glucuronidation activities of UGT1A1, UGT1A3, UGT1A4, UGT1A6, UGT1A9, UGT2B4, UGT2B7, UGT2B10, UGT2B15, and UGT2B17 were determined using cocktail incubations of 10 UGT probe substrates. Buffer components and cosubstrates were assessed over a range of concentrations including magnesium chloride (MgCl2; 0-10 mM) and uridine 5'-diphosphoglucuronic acid (UDPGA; 1-25 mM) with either Tris-HCl or potassium phosphate buffer (100 mM, pH 7.4). Greater microsomal glucuronidation activity by different hepatic UGT isoforms was obtained using 10 mM MgCl2 and 5 mM UDPGA with 100 mM Tris-HCl buffer. The influence of bovine serum albumin (BSA; 0.1%-2% w/v) on glucuronidation activity was also assessed. Enzyme- and substrate-dependent effects of BSA were observed, resulting in decreased total activity of UGT1A1, UGT1A3, and UGT2B17 and increased total UGT1A9 and UGT2B7 activity. The inclusion of BSA did not significantly reduce the between-subject variability of UGT activity. Future in vitro UGT profiling studies under the proposed optimized experimental conditions would allow high-quality positive control data to be generated across laboratories, with effective control of a high degree of between-donor variability for UGT activity and for chemical optimization toward lower-clearance drug molecules in a pharmaceutical drug discovery setting.
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Affiliation(s)
- Justine Badée
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
| | - Nahong Qiu
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
| | - Neil Parrott
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
| | - Abby C Collier
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
| | - Stephan Schmidt
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
| | - Stephen Fowler
- Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, University of Florida at Lake Nona, Orlando, Florida (J.B., S.S.); Pharmaceutical Sciences, Roche Pharma Research and Early Development, Roche Innovation Centre Basel, Basel, Switzerland (N.Q., N.P., S.F.); and Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada (A.C.C.)
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