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Li Q, Guan Y, Xia C, Wu L, Zhang H, Wang Y. Physiologically-based pharmacokinetic modeling and dosing optimization of cefotaxime in preterm and term neonates. J Pharm Sci 2024:S0022-3549(24)00086-8. [PMID: 38460573 DOI: 10.1016/j.xphs.2024.03.002] [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: 11/02/2023] [Revised: 03/02/2024] [Accepted: 03/02/2024] [Indexed: 03/11/2024]
Abstract
BACKGROUND Cefotaxime is commonly used in treating bacterial infections in neonates. To characterize the pharmacokinetic process in neonates and evaluate different recommended dosing schedules of cefotaxime, a physiologically-based pharmacokinetic (PBPK) model of cefotaxime was established in adults and scaled to neonates. METHODS A whole-body PBPK model was built in PK-SIM® software. Three elimination pathways are composed of enzymatic metabolism in the liver, passive filtration through glomerulus, and active tubular secretion mediated by renal transporters. The ontogeny information was applied to account for age-related changes in cefotaxime pharmacokinetics. The established models were verified with realistic clinical data in adults and pediatric populations. Simulations in neonates were conducted and 100% of the dosing interval where the unbound concentration in plasma was above the minimum inhibitory concentration (fT>MIC) was selected as the target index for dosing regimen evaluation. RESULTS The developed PBPK models successfully described the pharmacokinetic process of cefotaxime in adults and were scaled to the pediatric population. Good verification results were achieved in both adults' and neonates' PBPK models, indicating a good predictive performance. The optimal dosage regimen of cefotaxime was proposed according to the postnatal age (PNA) and gestational age (GA) of neonates. For preterm neonates (GA < 36 weeks), dosages of 25 mg/kg every 8 hours in PNA 0-6 days and 25 mg/kg every 6 hours in PNA 7-28 days were suggested. For term neonates (GA ≥ 36 weeks), dosages of 33 mg/kg every 8 hours in PNA 0-6 days and 33 mg/kg every 6 hours in PNA 7-28 days were recommended. CONCLUSIONS Our study may provide useful experience in practicing PBPK model-informed precision dosing in the pediatric population.
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Affiliation(s)
- Qiaoxi Li
- Department of pharmacy, the first people's hospital of Foshan, Foshan, China
| | - Yanping Guan
- Institute of clinical pharmacology, school of pharmaceutical sciences, Sun Yat-sen University, Guangzhou, China
| | - Chen Xia
- Department of pharmacy, the first people's hospital of Foshan, Foshan, China
| | - Lili Wu
- Department of pharmacy, the first people's hospital of Foshan, Foshan, China
| | - Hongyu Zhang
- Department of pharmacy, the first people's hospital of Foshan, Foshan, China
| | - Yan Wang
- Department of pharmacy, the first people's hospital of Foshan, Foshan, China.
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Zamir A, Alqahtani F, Rasool MF. Chronic kidney disease and physiologically based pharmacokinetic modeling: a critical review of existing models. Expert Opin Drug Metab Toxicol 2024; 20:95-105. [PMID: 38270999 DOI: 10.1080/17425255.2024.2311154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 01/24/2024] [Indexed: 01/27/2024]
Abstract
INTRODUCTION Physiologically based pharmacokinetic (PBPK) modeling is a paradigm shift in this era for determining the exposure of drugs in pediatrics, geriatrics, and patients with chronic diseases where clinical trials are difficult to conduct. AREAS COVERED This review has collated data regarding published PBPK models on chronic kidney disease (CKD), including the drug and system-specific input model parameters and model evaluation criteria. Four databases were used from 13th June 2023 to 10th July 2023 for identifying the relevant studies that met the inclusion/exclusion criteria. Alterations in plasma protein (albumin/alpha-1 acid glycoprotein), gastric emptying time, hematocrit, small intestinal transit time, the abundance of cytochrome (CYP) 450 enzymes, glomerular filtration rate, and physicochemical parameters for different drugs were explicitly elaborated from earlier reported studies. Moreover, model evaluation depicted that models in CKD for most of the included drugs were within the allowed two-fold error range. EXPERT OPINION This review will provide insights for researchers on applying PBPK models in managing patients with different levels of CKD to prevent undesirable side effects and increase the effectiveness of drug therapy.
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Affiliation(s)
- Ammara Zamir
- Department of Pharmacy Practice, Pharmacy, Bahauddin Zakariya University, Multan, Pakistan
| | - Faleh Alqahtani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud Universi-ty, Riyadh, Saudi Arabia
| | - Muhammad Fawad Rasool
- Department of Pharmacy Practice, Pharmacy, Bahauddin Zakariya University, Multan, Pakistan
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3
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Jacobs TG, de Hoop-Sommen MA, Nieuwenstein T, van der Heijden JEM, de Wildt SN, Burger DM, Colbers A, Freriksen JJM. Lamivudine and Emtricitabine Dosing Proposal for Children with HIV and Chronic Kidney Disease, Supported by Physiologically Based Pharmacokinetic Modelling. Pharmaceutics 2023; 15:pharmaceutics15051424. [PMID: 37242665 DOI: 10.3390/pharmaceutics15051424] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/04/2023] [Accepted: 05/05/2023] [Indexed: 05/28/2023] Open
Abstract
Dose recommendations for lamivudine or emtricitabine in children with HIV and chronic kidney disease (CKD) are absent or not supported by clinical data. Physiologically based pharmacokinetic (PBPK) models have the potential to facilitate dose selection for these drugs in this population. Existing lamivudine and emtricitabine compound models in Simcyp® (v21) were verified in adult populations with and without CKD and in non-CKD paediatric populations. We developed paediatric CKD population models reflecting subjects with a reduced glomerular filtration and tubular secretion, based on extrapolation from adult CKD population models. These models were verified using ganciclovir as a surrogate compound. Then, lamivudine and emtricitabine dosing strategies were simulated in virtual paediatric CKD populations. The compound and paediatric CKD population models were verified successfully (prediction error within 0.5- to 2-fold). The mean AUC ratios in children (GFR-adjusted dose in CKD population/standard dose in population with normal kidney function) were 1.15 and 1.23 for lamivudine, and 1.20 and 1.30 for emtricitabine, with grade-3- and -4-stage CKD, respectively. With the developed paediatric CKD population PBPK models, GFR-adjusted lamivudine and emtricitabine dosages in children with CKD resulted in adequate drug exposure, supporting paediatric GFR-adjusted dosing. Clinical studies are needed to confirm these findings.
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Affiliation(s)
- Tom G Jacobs
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Marika A de Hoop-Sommen
- Department of Pharmacology and Toxicology, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Thomas Nieuwenstein
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Joyce E M van der Heijden
- Department of Pharmacology and Toxicology, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Saskia N de Wildt
- Department of Pharmacology and Toxicology, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Department of Pediatrics, Erasmus MC-Sophia's Children's Hospital, 3015 CN Rotterdam, The Netherlands
| | - David M Burger
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Angela Colbers
- Department of Pharmacy, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Jolien J M Freriksen
- Department of Pharmacology and Toxicology, Research Institute for Medical Innovation, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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Khalid S, Rasool MF, Masood I, Imran I, Saeed H, Ahmad T, Alqahtani NS, Alshammari FA, Alqahtani F. Application of a physiologically based pharmacokinetic model in predicting captopril disposition in children with chronic kidney disease. Sci Rep 2023; 13:2697. [PMID: 36792681 PMCID: PMC9931704 DOI: 10.1038/s41598-023-29798-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 02/10/2023] [Indexed: 02/17/2023] Open
Abstract
Over the last several decades, angiotensin-converting enzyme inhibitors (ACEIs) have been a staple in the treatment of hypertension and renovascular disorders in children. One of the ACEIs, captopril, is projected to have all the benefits of traditional vasodilators. However, conducting clinical trials for determining the pharmacokinetics (PK) of a drug is challenging, particularly in pediatrics. As a result, modeling and simulation methods have been developed to identify the safe and effective dosages of drugs. The physiologically based pharmacokinetic (PBPK) modeling is a well-established method that permits extrapolation from adult to juvenile populations. By using SIMCYP simulator, as a modeling platform, a previously developed PBPK drug-disease model of captopril was scaled to renally impaired pediatrics population for predicting captopril PK. The visual predictive checks, predicted/observed ratios (ratiopred/obs), and the average fold error of PK parameters were used for model evaluation. The model predictions were comparable with the reported PK data of captopril in mild and severe chronic kidney disease (CKD) patients, as the mean ratiopred/obs Cmax and AUC0-t were 1.44 (95% CI 1.07 - 1.80) and 1.26 (95% CI 0.93 - 1.59), respectively. The successfully developed captopril-CKD pediatric model can be used in suggesting drug dosing in children diagnosed with different stages of CKD.
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Affiliation(s)
- Sundus Khalid
- grid.411501.00000 0001 0228 333XDepartment of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800 Pakistan
| | - Muhammad Fawad Rasool
- Department of Pharmacy Practice, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800, Pakistan.
| | - Imran Masood
- grid.412496.c0000 0004 0636 6599Department of Pharmacy Practice, Faculty of Pharmacy, The Islamia University of Bahawalpur, Bahawalpur, 63100 Pakistan
| | - Imran Imran
- grid.411501.00000 0001 0228 333XDepartment of Pharmacology, Faculty of Pharmacy, Bahauddin Zakariya University, Multan, 60800 Pakistan
| | - Hamid Saeed
- grid.11173.350000 0001 0670 519XSection of Pharmaceutics, University College of Pharmacy, Allama Iqbal Campus, University of the Punjab, Lahore, 54000 Pakistan
| | - Tanveer Ahmad
- grid.450307.50000 0001 0944 2786Institute for Advanced Biosciences (IAB), CNRS UMR5309, INSERM U1209, Grenoble Alpes University, 38700 La Tronche, France
| | - Nawaf Shalih Alqahtani
- grid.56302.320000 0004 1773 5396Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451 Saudi Arabia
| | - Fahad Ali Alshammari
- grid.56302.320000 0004 1773 5396Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451 Saudi Arabia
| | - Faleh Alqahtani
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, 11451, Saudi Arabia.
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Evaluation of Renal Impairment Influence on Metabolic Drug Clearance using a Modelling Approach. Clin Pharmacokinet 2023; 62:307-319. [PMID: 36631686 DOI: 10.1007/s40262-022-01205-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/18/2022] [Indexed: 01/13/2023]
Abstract
BACKGROUND AND OBJECTIVE Chronic kidney disease (CKD) may alter drug renal elimination but is also known for interacting with hepatic metabolism via multiple uremic components. However, few global models, considering the five major cytochromes, have been published, and none specifically address the decrease in cytochrome P450 (CYP450) activity. The aim of our study was to estimate the possibility of quantifying residual cytochrome activity as a function of filtration rate, according to the data available in the literature. METHODS For each drug in the DDI-predictor database, we collected available pharmacokinetic data comparing drug exposition in the healthy patient and in various stages of CKD, before building a model capable of predicting the variation of exposure according to the degree of renal damage. We followed an In vivo Mechanistic Static Model (IMSM) approach, previously validated for predicting change in liver clearance. We estimated the remaining fraction parameters at glomerular filtration rate (GFR) = 0 and the alpha value of GFR to 50% impairment for the 5 major cytochromes using a non-linear constrained regression using Matlab software. RESULTS Thirty-one compounds had usable pharmacokinetic data, with 51 AUC ratios between healthy and renal impaired patients. The remaining CYP3A4 activity was estimated to be 0.4 when CYP2D6, 2C9, 2C19 and 1A2 activity was estimated to be 0.43; 1; 0.73 and 0.7, respectively. The alpha value was estimated to be at 6.62; 25; 9.8; 1.38 and 11.04 for each cytochrome. In comparison with published data, all estimates but one were correctly predicted in the range of 0.5-2. CONCLUSION Our approach was able to describe the impact of CKD on metabolic elimination. Modelling this process makes it possible to anticipate changes in clearance and drug exposure in CKD patients, with the advantage of greater simplicity than approaches based on physiologically-based pharmacokinetic modelling. However, a precise estimation of the impact of renal failure is not possible with an IMSM approach due to the large variability of the published data, and thus should rely on specific pharmacokinetic modelling for narrow therapeutic margin drugs.
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Zhou X, Dun J, Chen X, Xiang B, Dang Y, Cao D. Predicting the correct dose in children: Role of computational Pediatric Physiological-based pharmacokinetics modeling tools. CPT Pharmacometrics Syst Pharmacol 2022; 12:13-26. [PMID: 36330677 PMCID: PMC9835135 DOI: 10.1002/psp4.12883] [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: 07/15/2022] [Revised: 10/12/2022] [Accepted: 10/16/2022] [Indexed: 11/06/2022] Open
Abstract
The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling. We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.
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Affiliation(s)
- Xu Zhou
- College of PharmacyHebei Medical UniversityShijiazhuangChina
| | - Jiening Dun
- College of PharmacyHebei Medical UniversityShijiazhuangChina
| | - Xiao Chen
- College of PharmacyHebei Medical UniversityShijiazhuangChina
| | - Bai Xiang
- College of PharmacyHebei Medical UniversityShijiazhuangChina
| | - Yunjie Dang
- College of PharmacyHebei Medical UniversityShijiazhuangChina
| | - Deying Cao
- College of PharmacyHebei Medical UniversityShijiazhuangChina
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Zhou J, You X, Guo G, Ke M, Xu J, Ye L, Wu W, Huang P, Lin C. Ceftaroline Dosage Optimized for Pediatric Patients With Renal Impairment Using Physiologically Based Pharmacokinetic Modeling. J Clin Pharmacol 2021; 61:1646-1656. [PMID: 34329494 DOI: 10.1002/jcph.1944] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 07/26/2021] [Indexed: 11/07/2022]
Abstract
Ceftaroline fosamil is a fifth-generation cephalosporin approved as a treatment for adults and children with community-acquired bacterial pneumonia and acute bacterial skin and skin structure infections. However, its pharmacokinetics have not been fully evaluated in children with renal impairment. This study aimed to propose proper ceftaroline dosages optimized for the renally impaired pediatric population using physiologically based pharmacokinetic (PBPK) modeling. A PBPK model of ceftaroline was established and verified to simulate its disposition in the healthy population and renally impaired adults and to predict the exposure in renally impaired pediatric patients. Consistency was confirmed between simulated and observed data after intravenous administration of various ceftaroline regimens; fold errors were within the 2-fold error range. Among 6-year-old children, healthy subjects had 1.5-fold, 2-fold, and 2.6-fold lower areas under the plasma concentration-time curve (AUCs) than the moderate, severe, and end-stage renally impaired patient groups, respectively; among 1-year-old children, healthy subjects had 1.5-fold, 2.1-fold, and 2.5-fold lower AUCs than the respective renally impaired patient groups; among 1-month-old children, healthy subjects had 1.5-fold, 1.8-fold, and 2.2-fold lower AUCs than the respective renally impaired patient groups. The proposed dosage should be adjusted to 8, 6, and 5 mg/kg every 8 hours for patients aged ≥2 years to <18 years (≤33 kg) with moderate, severe, and end-stage renal impairment, respectively; 5, 4, and 3 mg/kg every 8 hours for patients aged 2 months to <2 years with moderate, severe, and end-stage renal impairment, respectively; 4, 3.5, and 2.5 mg/kg every 8 hours for patients 0 to <2 months of age with moderate, severe, and end-stage renal impairment, respectively. Furthermore, pharmacodynamic investigations demonstrated that adequate antimicrobial effects were attained at the proposed doses in 3 age groups. Hence, our PBPK model can be an effective tool to support ceftaroline dosage proposals for renally impaired pediatric patients.
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Affiliation(s)
- Jie Zhou
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Xiang You
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Guimu Guo
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Meng Ke
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Jianwen Xu
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Lingling Ye
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Wanhong Wu
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Pinfang Huang
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Cuihong Lin
- Department of Pharmacy, The First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
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Xu J, Lin R, Chen Y, You X, Huang P, Lin C. Physiologically Based Pharmacokinetic Modeling and Dose Adjustment of Teicoplanin in Pediatric Patients With Renal Impairment. J Clin Pharmacol 2021; 62:620-630. [PMID: 34761398 DOI: 10.1002/jcph.2000] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 11/07/2021] [Indexed: 12/29/2022]
Abstract
The pharmacokinetics of teicoplanin differs in children as compared with adults, and especially in renally impaired pediatric patients. Inappropriate empirical antibacterial therapy may lead to treatment-related antibacterial resistance and increased toxicity, making adjustment of the dosage regimen essential. In the present study, physiologically based pharmacokinetic (PBPK) models were developed to define the appropriate dosage regimen for pediatric patients with differing renal function. Our PBPK models accurately predicted teicoplanin exposures in both adult and pediatric subjects after single and multiple intravenous infusions, with a <1.36-fold error between predicted and observed data, and all observed data were within minimal and maximal data of the corresponding population simulation. The area under the plasma concentration-time curve was predicted to increase 1.25-fold, 1.95-fold, and 2.82-fold in pediatric patients with mild, moderate, and severe renal impairment, respectively, relative to that of healthy children. Subsequently, the results of Monte Carlo simulations indicated that the recommended dosing of 12, 9.5, 6, and 4 mg/kg at 12-hour intervals would be appropriate in pediatric patients with normal renal function and in those with mild, moderate, and severe renal impairment, respectively, at a susceptible minimum inhibitory concentration <2 mg/L. In conclusion, our PBPK model with an incorporated Monte Carlo simulation can provide improved guidance on dosing in pediatric patients with differing renal function and provide a basis for precision therapy with teicoplanin.
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Affiliation(s)
- Jianwen Xu
- Department of Pharmacy, the First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Rongfang Lin
- Department of Pharmacy, the First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Yong Chen
- Department of Pharmacy, Fuzhou Children's Hospital of Fujian Medical University, Fuzhou, 350005, People's Republic of China
| | - Xiang You
- Department of Pharmacy, the First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Pinfang Huang
- Department of Pharmacy, the First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
| | - Cuihong Lin
- Department of Pharmacy, the First Affiliated Hospital of Fujian Medical University, Fuzhou, People's Republic of China
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Development of Physiologically Based Pharmacokinetic Model for Pregabalin to Predict the Pharmacokinetics in Pediatric Patients with Renal Impairment and Adjust Dosage Regimens: PBPK Model of Pregabalin in Pediatric Patients with Renal Impairment. J Pharm Sci 2021; 111:542-551. [PMID: 34706283 DOI: 10.1016/j.xphs.2021.10.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 10/15/2021] [Accepted: 10/15/2021] [Indexed: 12/17/2022]
Abstract
Pregabalin (PGB) is widely used clinically; however, its pharmacokinetics (PK) has not been studied in pediatric patients with renal impairment (RI). To design optimized PGB regimens for pediatric patients with varying degrees of RI and predict exposure to PGB, physiologically based pharmacokinetic (PBPK) models of PGB were developed and verified, and its disposition was simulated in the healthy population and adults with RI. The simulated results from the PBPK models after single-dose and multi-dose administrations of PGB were consistent with the corresponding observed data based on the fold error values of less than 2. The area under curve ratios were 1.23 ± 0.06, 2.02 ± 0.10, 3.86 ± 0.21, and 9.92 ± 0.79 in pediatric patients with mild, moderate, severe, and end-stage RI, respectively. Based on the predictions for pediatric patients with moderate, severe, and end-stage RI, the maximum dose should not exceed 7, 3.5, and 1.4 mg/kg/day, respectively, among those weighing < 30 kg, and it should not exceed 5, 2.5, and 1 mg/kg/day, respectively, among those weighing > 30 kg. In conclusion, the developed PBPK model is a valuable tool for predicting PGB dosage for pediatric patients with RI.
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Li X, Qi H, Jin F, Yao BF, Wu YE, Qi YJ, Kou C, Wu XR, Luo XJ, Shen YH, Zheng X, Wang YH, Xu F, Jiao WW, Li JQ, Xiao J, Dong YN, Du B, Shi HY, Xu BP, Shen AD, Zhao W. Population pharmacokinetics-pharmacodynamics of ceftazidime in neonates and young infants: Dosing optimization for neonatal sepsis. Eur J Pharm Sci 2021; 163:105868. [PMID: 33951483 DOI: 10.1016/j.ejps.2021.105868] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 03/01/2021] [Accepted: 04/25/2021] [Indexed: 01/22/2023]
Abstract
Ceftazidime is a third-generation cephalosporin with high activity against many pathogens. But the ambiguity and diversity of the dosing regimens in neonates and young infants impair access to effective treatment. Thus, we conducted a population pharmacokinetic study of ceftazidime in this vulnerable population and recommended a model-based dosage regimen to optimize sepsis therapy. Totally 146 neonates and young infants (gestational age (GA): 36-43.4 weeks, postnatal age (PNA): 1-81 days, current weight (CW): 900-4500 g) were enrolled based on inclusion and exclusion criteria. Ceftazidime bloods samples (203) were obtained using the opportunistic sampling strategy and determined by the high-performance liquid chromatography. The population pharmacokinetic-pharmacodynamic analysis was conducted by nonlinear mixed effects model (NONMEM). A one-compartment model with first-order elimination best described the pharmacokinetic data. Covariate analysis showed the significance of GA, PNA, and CW on developmental pharmacokinetics. Monte Carlo simulation was performed based on above covariates and minimum inhibitory concentration (MIC). In the newborns with PNA ≤ 3 days (MIC=8 mg/L), the dose regimen was 25 mg/kg twice daily (BID). For the newborns with PNA > 3 days (MIC=16 mg/L), the optimal dose was 30 mg/kg three times daily (TID) for those with GA ≤ 37 weeks and 40 mg/kg TID for those with GA > 37 weeks. Overall, on the basis of the developmental population pharmacokinetic-pharmacodynamic analysis covering the whole range of neonates and young infants, the evidence-based ceftazidime dosage regimens were proposed to optimize neonatal early-onset and late-onset sepsis therapy.
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Affiliation(s)
- Xue Li
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Hui Qi
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Fei Jin
- Neonatal intensive care unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Bu-Fan Yao
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Yue-E Wu
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Yu-Jie Qi
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Chen Kou
- Department of Neonatology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing 100045, China
| | - Xi-Rong Wu
- Department of Respiratory Diseases, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Xiao-Jing Luo
- Neonatal intensive care unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Yan-Hua Shen
- Neonatal intensive care unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Xu Zheng
- Neonatal intensive care unit, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Yong-Hong Wang
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Fang Xu
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Wei-Wei Jiao
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Jie-Qiong Li
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Jing Xiao
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - Yi-Ning Dong
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Bin Du
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China
| | - Hai-Yan Shi
- Department of Clinical Pharmacy, Clinical Trial Center, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China
| | - Bao-Ping Xu
- Department of Respiratory Diseases, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China
| | - A-Dong Shen
- Beijing Key Laboratory of Pediatric Respiratory Infection Diseases, Key Laboratory of Major Diseases in Children, Ministry of Education, National Clinical Research Center for Respiratory Diseases, National Key Discipline of Pediatrics (Capital Medical University), Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing 100045, China.
| | - Wei Zhao
- Department of Clinical Pharmacy, Key Laboratory of Chemical Biology (Ministry of Education), School of Pharmaceutical Sciences, Cheeloo College of Medicine, Shandong University, Jinan 250012, China; Department of Clinical Pharmacy, Clinical Trial Center, The First Affiliated Hospital of Shandong First Medical University & Shandong Provincial Qianfoshan Hospital, Shandong Engineering and Technology Research Center for Pediatric Drug Development, Shandong Medicine and Health Key Laboratory of Clinical Pharmacy, Jinan 250014, China.
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