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Losada IB, Terranova N. Bridging pharmacology and neural networks: A deep dive into neural ordinary differential equations. CPT Pharmacometrics Syst Pharmacol 2024. [PMID: 38992975 DOI: 10.1002/psp4.13149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/28/2024] [Accepted: 04/08/2024] [Indexed: 07/13/2024] Open
Abstract
The advent of machine learning has led to innovative approaches in dealing with clinical data. Among these, Neural Ordinary Differential Equations (Neural ODEs), hybrid models merging mechanistic with deep learning models have shown promise in accurately modeling continuous dynamical systems. Although initial applications of Neural ODEs in the field of model-informed drug development and clinical pharmacology are becoming evident, applying these models to actual clinical trial datasets-characterized by sparse and irregularly timed measurements-poses several challenges. Traditional models often have limitations with sparse data, highlighting the urgent need to address this issue, potentially through the use of assumptions. This review examines the fundamentals of Neural ODEs, their ability to handle sparse and irregular data, and their applications in model-informed drug development.
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Affiliation(s)
- Idris Bachali Losada
- Quantitative Pharmacology, Ares Trading S.A. (An Affiliate of Merck KGaA, Darmstadt, Germany), Lausanne, Switzerland
| | - Nadia Terranova
- Quantitative Pharmacology, Ares Trading S.A. (An Affiliate of Merck KGaA, Darmstadt, Germany), Lausanne, Switzerland
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Blouin M, Métras MÉ, El Hassani M, Yaliniz A, Marsot A. Optimization of Vancomycin Initial Dosing Regimen in Neonates Using an Externally Evaluated Population Pharmacokinetic Model. Ther Drug Monit 2024:00007691-990000000-00235. [PMID: 38857472 DOI: 10.1097/ftd.0000000000001226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 03/27/2024] [Indexed: 06/12/2024]
Abstract
BACKGROUND Vancomycin therapeutic monitoring guidelines were revised in March 2020, and a population pharmacokinetics-guided Bayesian approach to estimate the 24-hour area under the concentration-time curve to the minimum inhibitory concentration ratio has since been recommended instead of trough concentrations. To comply with these latest guidelines, we evaluated published population pharmacokinetic models of vancomycin using an external dataset of neonatal patients and selected the most predictive model to develop a new initial dosing regimen. METHODS The models were identified from the literature and tested using a retrospective dataset of Canadian neonates. Their predictive performance was assessed using prediction- and simulation-based diagnostics. Monte Carlo simulations were performed to develop the initial dosing regimen with the highest probability of therapeutic target attainment. RESULTS A total of 144 vancomycin concentrations were derived from 63 neonates in the external population. Five of the 28 models retained for evaluation were found predictive with a bias of 15% and an imprecision of 30%. Overall, the Grimsley and Thomson model performed best, with a bias of -0.8% and an imprecision of 20.9%; therefore, it was applied in the simulations. A novel initial dosing regimen of 15 mg/kg, followed by 11 mg/kg every 8 hours should favor therapeutic target attainment. CONCLUSIONS A predictive population pharmacokinetic model of vancomycin was identified after an external evaluation and used to recommend a novel initial dosing regimen. The implementation of these model-based tools may guide physicians in selecting the most appropriate initial vancomycin dose, leading to improved clinical outcomes.
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Affiliation(s)
- Mathieu Blouin
- STP Laboratory, Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
| | - Marie-Élaine Métras
- Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Department of Pharmacy, Centre Hospitalier Universitaire Sainte-Justine, Montréal (QC), Canada; and
| | - Mehdi El Hassani
- STP Laboratory, Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
| | - Aysenur Yaliniz
- STP Laboratory, Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
| | - Amélie Marsot
- STP Laboratory, Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Faculty of Pharmacy, Université de Montréal, Montréal (QC), Canada
- Research Center, Centre Hospitalier Universitaire Sainte-Justine, Montréal (QC), Canada
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3
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Soeorg H, Kalamees R, Lutsar I, Metsvaht T. Subgroup identification-based model selection to improve the predictive performance of individualized dosing. J Pharmacokinet Pharmacodyn 2024; 51:253-263. [PMID: 38400995 DOI: 10.1007/s10928-024-09909-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 02/13/2024] [Indexed: 02/26/2024]
Abstract
Currently, model-informed precision dosing uses one population pharmacokinetic model that best fits the target population. We aimed to develop a subgroup identification-based model selection approach to improve the predictive performance of individualized dosing, using vancomycin in neonates/infants as a test case. Data from neonates/infants with at least one vancomycin concentration was randomly divided into training and test dataset. Population predictions from published vancomycin population pharmacokinetic models were calculated. The single best-performing model based on various performance metrics, including median absolute percentage error (APE) and percentage of predictions within 20% (P20) or 60% (P60) of measurement, were determined. Clustering based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm was used to group neonates/infants according to their best-performing model. Subsequently, classification trees to predict the best-performing model using clinical and demographic characteristics were developed. A total of 208 vancomycin treatment episodes in training and 88 in test dataset was included. Of 30 identified models from the literature, the single best-performing model for training dataset had P20 26.2-42.6% in test dataset. The best-performing clustering approach based on median APEs or clinical and demographic characteristics and model selection by genetic algorithm had P20 44.1-45.5% in test dataset, whereas P60 was comparable. Our proof-of-concept study shows that the prediction of the best-performing model for each patient according to the proposed model selection approaches has the potential to improve the predictive performance of model-informed precision dosing compared with the single best-performing model approach.
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Affiliation(s)
- Hiie Soeorg
- Department of Microbiology, University of Tartu, Ravila 19, Tartu, 50411, Estonia.
| | - Riste Kalamees
- Department of Microbiology, University of Tartu, Ravila 19, Tartu, 50411, Estonia
| | - Irja Lutsar
- Department of Microbiology, University of Tartu, Ravila 19, Tartu, 50411, Estonia
| | - Tuuli Metsvaht
- Department of Microbiology, University of Tartu, Ravila 19, Tartu, 50411, Estonia
- Pediatric Intensive Care Unit, Tartu University Hospital, Puusepa 8, Tartu, 50406, Estonia
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Population Pharmacokinetics and Dosage Optimization of Vancomycin in Pediatric Patients with Skin and Soft Tissue Infections, Bone, and Joint Infections. Antimicrob Agents Chemother 2023; 67:e0162422. [PMID: 36622172 PMCID: PMC9879599 DOI: 10.1128/aac.01624-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
Abstract
Vancomycin is recommended for the treatment of skin and soft tissue infections (SSTI) and bone and joint infections (BJI). However, a detailed investigation of the pharmacokinetic profile and optimal dosing regimens of vancomycin in pediatric patients with SSTI and BJI is lacking. We successfully developed a new PopPK model of vancomycin in this population by using scavenged blood samples with the typical values for clearance (CL) of 0.14 L/h/kg and volume of distribution (V) of 0.5 L/kg. Body weight was confirmed as the significant covariate on CL and V. The optimal dosing regimens of 75 mg/kg/day and 80 mg/kg/day were recommended for this specific population.
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Weng XH, Zhu CQ, Duan LF, Li L, Yang ZM, Wang SN, Cai Y, Li JJ, Yu YX, Feng ZT, Tang L. Vancomycin in neonatal sepsis: predictive performance of a Chinese neonatal population pharmacokinetic model and clinical efficacy evaluation. Eur J Hosp Pharm 2022; 29:101-108. [PMID: 33472817 PMCID: PMC8899688 DOI: 10.1136/ejhpharm-2020-002479] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 11/26/2020] [Accepted: 12/01/2020] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND In the neonatal population, individual calculation and adjustment of vancomycin (VCM) doses has been recommended based on population pharmacokinetics (PPK) methods. OBJECTIVE Our previous study established a Chinese neonatal VCM PPK model. The main goal of this study was to evaluate the predictive performance of this PPK model for VCM trough concentration. METHODS The data on neonatal severe infection patients treated with VCM were retrospectively collected. The predictive performance of this PPK model was expressed using mean prediction error (MPE), mean absolute prediction error (MAPE), sensitivity and specificity. Linear regression analysis was used to compare predicted and measured VCM concentrations. We drew the receiver operating characteristic (ROC) curve to evaluate the predictive efficacy of the ratio of area under the concentration-time curve over 24 hours to minimum inhibitory concentration (AUC0-24/MIC) and trough concentration for clinical efficacy. RESULTS A total of 40 neonates with Gram-positive bacterial sepsis were included. After VCM treatment, 32 (80%) neonates were clinically cured. Eight cases were a clinical failure: the trough concentrations and AUC0-24 were lower than that of the clinical cure patients (8.70±4.30 vs 14.30±4.50 mg/L, p=0.003; 404.30±122.80 vs 515.40±131.70, p=0.037). The measured and predicted trough concentration were 11.16 (5.96, 16.53) mg/L and 10.13 (6.61, 15.73) mg/L, respectively. The MPE and MAPE were 4.62% and 13.26% (5.30%, 25.88%), respectively. The proportion of MAPE <30% in the adjusted regimen was higher than the initial regimen (89.66% vs 65.00%, p=0.039). Predictions of sensitivity and specificity by this PPK model were 88.24% and 94.29%, respectively. The coefficients of determination of linear regression analysis were 0.9171 and 0.9009 for the initial and adjusted regimen, respectively. The AUC0-24 was correlated with the trough concentration (r=0.587, p<0.001). The ROC curve indicated that the optimal cut-off points for predicting clinical efficacy were AUC0-24/MIC >425.47 and trough concentration >9.45 mg/L. CONCLUSION This PPK model has good predictive performance in Chinese neonatal patients. Both AUC0-24/MIC and trough concentration can predict the clinical efficacy of antibacterial treatment.
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Affiliation(s)
- Xiao-Hong Weng
- Education department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Chen-Qi Zhu
- Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Lu-Fen Duan
- Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Lan Li
- Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Zu-Ming Yang
- Neonatology Department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - San-Nan Wang
- Neonatology Department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Yan Cai
- Neonatology Department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Jing-Jing Li
- Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Yan-Xia Yu
- GCP office, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Zong-Tai Feng
- Neonatology Department, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
| | - Lian Tang
- Department of Pharmacy, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, Jiangsu, China
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Xu J, Zhu Y, Niu P, Liu Y, Li D, Jiang L, Shi D. Establishment and application of population pharmacokinetics model of vancomycin in infants with meningitis. Pediatr Neonatol 2022; 63:57-65. [PMID: 34544677 DOI: 10.1016/j.pedneo.2021.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 06/09/2021] [Accepted: 06/11/2021] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND To establish a population pharmacokinetics (PPK) model of vancomycin (VCM) for dose individualization in Chinese infants with meningitis. METHODS We collected the data of 82 children with meningitis in hospital from July 2014 to June 2016. The initial vancomycin dosage regimen for children was 10 or 15 mg/kg for q12 h, q8 h or q6 h. Serum concentrations were determined by Viva-E Analyzer before and after the fifth administration. The PPK model was developed by nonlinear mixed-effect model software, assessed by the bootstrap method and then tested in 20 infant patients. RESULTS The VCM clearance (CL) was increased by body weight (WT) and decreased by blood urea nitrogen (BUN). Pharmacokinetic parameters of VCM were not influenced by co-administered drugs. The trough concentrations of VCM were accurately predicted by the PPK model, with the prediction errors less than 32%. CONCLUSION A new individual strategy for VCM regimens was proposed and validated by the PPK model.
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Affiliation(s)
- Jianwen Xu
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China; Department of Pharmacy, Affiliated First Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Yanting Zhu
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Peiguang Niu
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Ying Liu
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Danyun Li
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Li Jiang
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China
| | - Daohua Shi
- Department of Pharmacy, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, Fujian, 350001, China.
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Liu S, Wang Z, Chen R, Huang H, Wang X, Peng C, Guan Y, Fang X, Guan S, Huang H, Liu T, Lin T, Huang M. Rituximab exposure-response in triweekly R-CHOP treatment in DLBCL: A loading dose is recommended to improve clinical outcomes. Clin Transl Sci 2021; 15:680-690. [PMID: 34729920 PMCID: PMC8932720 DOI: 10.1111/cts.13186] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/09/2021] [Accepted: 10/16/2021] [Indexed: 11/28/2022] Open
Abstract
Previous exposure-response analyses for rituximab suggest that higher rituximab concentrations were associated with an improvement in efficacy, however, clinical studies investigating a higher rituximab dose had mixed results. To further explore the exposure-response relationship of rituximab, a prospective observational analysis was performed involving 121 newly diagnosed patients with diffuse large B-cell lymphoma treated with triweekly rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). The trough concentration in the first cycle (C1-trough ) was significantly higher in patients achieving complete response (CR) compared with patients that did not achieve CR (22.00 μg/ml vs. 16.62 μg/ml, p = 0.0016), however, this difference between the two groups disappeared in later cycles. The relationship between rituximab C1-trough and achieving a CR was confirmed by matched-pair logistic regression analysis (odds ratio, 0.79; p = 0.0020). In addition, a higher C1-trough (≥18.40 μg/ml) was associated with longer progression-free survival (p < 0.0001) and overall survival (p = 0.0038). The percentages of patients that did not achieve a CR and had recurrence after CR within 24 months were 35% and 22.50%, respectively, for patients with a C1-trough less than or equal to 18.40 μg/ml, compared with 12.35% and 6.17% for patients with C1-trough greater than 18.40 μg/ml. Disease stage was found to be the most significant influencing factor of C1-trough , with 51.02% of patients at stage IV with an observed C1-trough less than 18.40 μg/ml. For these advanced patients, population pharmacokinetic simulations using an established model suggest that a loading dose of 800 mg/m2 may help to improve clinical outcomes.
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Affiliation(s)
- Shu Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.,Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhao Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Rongxin Chen
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - He Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Xueding Wang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Chen Peng
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.,NanJing Pukou Central Hospital, Pukou Branch Hospital of Jiangsu Province Hospital, Jiangsu, China
| | - Yanping Guan
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.,Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China
| | - Xiaojie Fang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Shaoxing Guan
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Hongbing Huang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Tao Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Tongyu Lin
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China.,Sichuan Cancer Hospital and Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, Sichuan, China
| | - Min Huang
- Institute of Clinical Pharmacology, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China
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Aljutayli A, El-Haffaf I, Marsot A, Nekka F. An Update on Population Pharmacokinetic Analyses of Vancomycin, Part II: In Pediatric Patients. Clin Pharmacokinet 2021; 61:47-70. [PMID: 34671937 DOI: 10.1007/s40262-021-01050-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/09/2021] [Indexed: 10/20/2022]
Abstract
Vancomycin is widely used in pediatric patients, however, large inter- and intraindividual variability are observed in vancomycin pharmacokinetics, affecting proper therapeutic monitoring. This review aimed at providing a comprehensive synthesis of the population pharmacokinetic models of vancomycin in pediatric patients and identifying potential factors responsible for the variability observed in various subpopulations. We conducted a literature search of the PubMed and EMBASE databases to obtain population pharmacokinetic studies for vancomycin published between January 2011 and January 2020, which resulted in a total of 33 studies. Vancomycin pharmacokinetics were generally characterized using a one-compartment model (n = 27), while a two-compartment model was used in six studies. The median (interquartile range) of the typical vancomycin clearance (CL) and the total volume of distribution adjusted to the median or mean body weight of the respective study was 0.103 L/h/kg (0.071-0.125) and 0.64 L/kg (0.59-1.03), respectively. Median weight-adjusted CL between different child age groups, such as infants and adolescents, did not appear to vary significantly, although the sample size for many age groups was very small. Examples of the conditions with relatively abnormal vancomycin pharmacokinetic values include renal insufficiency, sepsis, hematological and solid malignancy, and hypothermia treatment. Factors influencing pediatric vancomycin pharmacokinetics after adjusting for size and maturation include various renal function descriptors and some case-specific variables such as dialysate flow rate, ultrafiltrate output, and hypothermia. This review was able to document possible variables explaining the high variability observed in certain subpopulations and contrast vancomycin pharmacokinetics in different pediatric subpopulations.
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Affiliation(s)
- Abdullah Aljutayli
- Faculty of Pharmacy, Université de Montréal, 2940 chemin de polytechnique, Montreal, H3T 1J4, Canada.,Laboratoire de Pharmacométrie, Faculté de Pharmacie, Université de Montréal, 2940 chemin de polytechnique, Montreal, QC, H3T 1J4, Canada
| | - Ibrahim El-Haffaf
- Faculty of Pharmacy, Université de Montréal, 2940 chemin de polytechnique, Montreal, H3T 1J4, Canada.,Laboratoire de suivi thérapeutique pharmacologique et pharmacocinétique, Faculté de Pharmacie, Université de Montréal, 2940 chemin de polytechnique, Montreal, QC, H3T 1J4, Canada
| | - Amélie Marsot
- Faculty of Pharmacy, Université de Montréal, 2940 chemin de polytechnique, Montreal, H3T 1J4, Canada. .,Laboratoire de suivi thérapeutique pharmacologique et pharmacocinétique, Faculté de Pharmacie, Université de Montréal, 2940 chemin de polytechnique, Montreal, QC, H3T 1J4, Canada. .,Centre de recherche, CHU Sainte-Justine, 175 Chemin de la Côte-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada.
| | - Fahima Nekka
- Faculty of Pharmacy, Université de Montréal, 2940 chemin de polytechnique, Montreal, H3T 1J4, Canada.,Laboratoire de Pharmacométrie, Faculté de Pharmacie, Université de Montréal, 2940 chemin de polytechnique, Montreal, QC, H3T 1J4, Canada.,Centre de recherches mathématiques, Université de Montréal, 2900 Boulevard Edouard-Montpetit, Montreal, QC, Canada, H3T 1J4
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Population pharmacokinetics of diethylcarbamazine in patients with lymphatic filariasis and healthy individuals. Antimicrob Agents Chemother 2021; 65:e0031721. [PMID: 34310218 DOI: 10.1128/aac.00317-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Diethylcarbamazine (DEC) is a drug of choice to treat lymphatic filariasis (LF) either used alone or in combination as mass drug administration (MDA) preventive strategies. The objective of this study was to develop a population pharmacokinetic model for DEC in subjects infected with lymphatic filariasis (LF) compared to healthy individuals, and to evaluate the effect of covariates on the volume of distribution (V/F) and oral clearance (CL/F) of DEC. This was an open-label cohort study of treatment naïve Wuchereria bancrofti-infected (n=32) and uninfected (n=24) adults residing in the Agboville district of Côte d'Ivoire. The population pharmacokinetic model for DEC was built using Phoenix NLME 8.0 software. The covariates included in the model building process were age, gender, bodyweight, infection status, creatinine clearance (CrCl), aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels. A total of 56 adults were enrolled in the study and a total of 728 samples were obtained over 168 hours. A one-compartment linear pharmacokinetic model with first-order absorption with an absorption lag-time (Tlag) best described the data. After determining the pharmacokinetics (PK) parameters of DEC, body weight and gender were found to be the significant covariates for DEC V/F. The final population pharmacokinetic model adequately described the pharmacokinetics of DEC in the studied population. Model-based simulation indicated that the body weight significantly impacted the exposure in both the male and female population. This analysis may further support the drug-drug interaction model development of DEC with different co-administered drugs/agents in disease control programs.
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10
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Population Pharmacokinetic Models of Vancomycin in Paediatric Patients: A Systematic Review. Clin Pharmacokinet 2021; 60:985-1001. [PMID: 34002357 DOI: 10.1007/s40262-021-01027-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Vancomycin is commonly used to treat gram-positive bacterial infections in the paediatric population, but dosing can be challenging. Population pharmacokinetic (popPK) modelling can improve individualization of dosing regimens. The primary objective of this study was to describe popPK models of vancomycin and factors that influence pharmacokinetic (PK) variability in paediatric patients. METHODS Systematic searches were conducted in the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, International Pharmaceutical Abstracts and the grey literature without language or publication status restrictions from inception to 17 August 2020. Observational studies that described the development of popPK models of vancomycin in paediatric patients (< 18 years of age) were included. Risk of bias was assessed using the National Heart, Lung and Blood Institute Study Quality Assessment Tool for Case Series Studies. RESULTS Sixty-four observational studies (1 randomized controlled trial, 13 prospective studies and 50 retrospective studies of 9019 patients with at least 25,769 serum vancomycin concentrations) were included. The mean age was 2.5 years (range 1 day-18 years), serum creatinine was 47.1 ± 33.6 µmol/L, and estimated creatinine clearance was 97.4 ± 76 mL/min/1.73m2. Most studies found that vancomycin PK was best described by a one-compartment model (71.9%). There was a wide range of clearance and volume of distribution (Vd) values (range 0.014-0.27 L/kg/h and 0.43-1.46 L/kg, respectively) with interindividual variability as high as 49.7% for clearance and 136% for Vd, proportional residual variability up to 37.5% and additive residual variability up to 17.5 mg/L. The most significant covariates for clearance were weight, age, and serum creatinine or creatinine clearance, and weight for Vd. Variable dosing recommendations were suggested. CONCLUSION Numerous popPK models of vancomycin were derived, however external validation of suggested dosing regimens and analyses in subgroup paediatric populations such as dialysis patients are still needed before a popPK model with best predictive performance can be applied for dosing recommendations. Significant intraindividual and interindividual PK variability was present, which demonstrated the need for ongoing therapeutic drug monitoring and derivation of PK models for vancomycin for certain subgroup populations, such as dialysis patients.
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Yao X, Liu X, Tu S, Li X, Lei Z, Hou Z, Yu Z, Cui C, Dong Z, Salem F, Li H, Liu D. Development of a Virtual Chinese Pediatric Population Physiological Model Targeting Specific Metabolism and Kidney Elimination Pathways. Front Pharmacol 2021; 12:648697. [PMID: 34045960 PMCID: PMC8145459 DOI: 10.3389/fphar.2021.648697] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Accepted: 03/23/2021] [Indexed: 12/18/2022] Open
Abstract
Background: Physiologically based pharmacokinetic (PBPK) modeling and simulating may be a powerful tool in predicting drug behaviors in specific populations. It is a mathematical model that relates the pharmacokinetic (PK) profile of a compound with human anatomical characteristics, physiological characteristics, and biochemical parameters. Predictions using PBPK models offer a promising way to guide drug development and can be used to optimize clinical dosing regimens. However, PK data of new drugs in the pediatric population are too limited to guide clinical therapy, which may lead to frequent adverse events or insufficient efficacy for pediatric patients, particularly in neonates and infants. Objective: The objective of this study was to establish a virtual Chinese pediatric population based on the physiological parameters of Chinese children that could be utilized in PBPK models. Methods: A Chinese pediatric PBPK model was developed in Simcyp Simulator by collecting published Chinese pediatric physiological and anthropometric data to use as system parameters. This pediatric population model was then evaluated in the Chinese pediatric population by predicting the pharmacokinetic characteristics of four probe drugs: theophylline (major CYP1A2 substrate), fentanyl (major CYP3A4 substrate), vancomycin, and ceftazidime (renal-eliminated). Results: The predicted maximum concentration (Cmax), area under the curve of concentration-time (AUC), and clearance (CL) for theophylline (CYP1A2 metabolism pathway) and fentanyl (CYP3A4 metabolism pathway) were within two folds of the observed data. For drugs mainly eliminated by renal clearance (vancomycin and ceftazidime) in the Chinese pediatric population, the ratio of prediction to observation for major PK parameters was within a 2-fold error range. Conclusion: The model is a supplement to the previous Chinese population PBPK model. We anticipate the model to be a better representative of the pediatric Chinese population for drugs PK, offering greater clinical precision for medication given to the pediatric population, ultimately advancing clinical development of pediatric drugs. We can refine this model further by collecting more physiological parameters of Chinese children.
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Affiliation(s)
- Xueting Yao
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Xuanlin Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Tsinghua University, Beijing, China
| | - Siqi Tu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Peking University Health Science Center, Peking University, Beijing, China
| | - Xiaobei Li
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Pharmaceutical Sciences, Peking University Health Science Center, Peking University, Beijing, China
| | - Zihan Lei
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Zhe Hou
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Zhiheng Yu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | - Cheng Cui
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
| | | | - Farzaneh Salem
- Certara UK Limited, Simcyp Division, Sheffield, United Kingdom
| | - Haiyan Li
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China.,Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Beijing, China
| | - Dongyang Liu
- Drug Clinical Trial Center, Peking University Third Hospital, Beijing, China
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12
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Mechanistic Modelling Identifies and Addresses the Risks of Empiric Concentration-Guided Sorafenib Dosing. Pharmaceuticals (Basel) 2021; 14:ph14050389. [PMID: 33919091 PMCID: PMC8143107 DOI: 10.3390/ph14050389] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Revised: 04/14/2021] [Accepted: 04/19/2021] [Indexed: 12/12/2022] Open
Abstract
The primary objective of this study is to evaluate the capacity of concentration-guided sorafenib dosing protocols to increase the proportion of patients that achieve a sorafenib maximal concentration (Cmax) within the range 4.78 to 5.78 μg/mL. A full physiologically based pharmacokinetic model was built and validated using Simcyp® (version 19.1). The model was used to simulate sorafenib exposure in 1000 Sim-Cancer subjects over 14 days. The capacity of concentration-guided sorafenib dose adjustment, with/without model-informed dose selection (MIDS), to achieve a sorafenib Cmax within the range 4.78 to 5.78 μg/mL was evaluated in 500 Sim-Cancer subjects. A multivariable linear regression model incorporating hepatic cytochrome P450 (CYP) 3A4 abundance, albumin concentration, body mass index, body surface area, sex and weight provided robust prediction of steady-state sorafenib Cmax (R2 = 0.883; p < 0.001). These covariates identified subjects at risk of failing to achieve a sorafenib Cmax ≥ 4.78 μg/mL with 95.0% specificity and 95.2% sensitivity. Concentration-guided sorafenib dosing with MIDS achieved a sorafenib Cmax within the range 4.78 to 5.78 μg/mL for 38 of 52 patients who failed to achieve a Cmax ≥ 4.78 μg/mL with standard dosing. In a simulation setting, concentration-guided dosing with MIDS was the quickest and most effective approach to achieve a sorafenib Cmax within a designated range.
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13
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Low initial trough concentration of rituximab is associated with unsatisfactory response of first-line R-CHOP treatment in patients with follicular lymphoma with grade 1/2. Acta Pharmacol Sin 2021; 42:641-647. [PMID: 32737470 DOI: 10.1038/s41401-020-0479-2] [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] [Received: 04/23/2020] [Accepted: 07/07/2020] [Indexed: 12/27/2022] Open
Abstract
For follicular lymphoma (FL) with grade 1/2, the complete response (CR) rate of the first-line R-CHOP treatment was significantly low. In this study, we assessed the rationality of the administration of rituximab for FL patients with grade 1/2 based on concentration-response relationship analyses. Thus, we conducted a prospective pharmacokinetic (PK) study in 68 FL patients with grades 1-3 treated with R-CHOP at 21-day intervals. Plasma rituximab concentrations were quantified using ELISA and the population PK modeling was established with Phoenix® NLMETM. The first cycle trough concentration (C1-trough) of rituximab was a significant independent risk factor for achieving CR in matched-pair logistic regression analysis, rather than the concentrations in later cycles; the recommendatory minimum optimal C1-trough was 13.60 μg/mL. Patients with grade 1/2 had significantly lower C1-trough compared with grade 3 (12.21 μg/mL vs. 23.45 μg/mL, P < 0.001), only 30% patients with grade 1/2 could reach 13.60 μg/mL, compared with 91.67% in patients with grade 3, which was in accord with its unsatisfactory CR rates (43.33% vs. 76.32%). The stage indicating the tumor burden (the target) was a crucial influence factor for C1-trough, accounting for 40.70% of its variability, 70% patients with grade 1/2 were stage IV in this study, since the systemic therapy only started at the disseminated disease stage. The initial dose of 1800 mg was recommended by Monte Carlo simulation for patients with grade 1/2. In summary, low C1-trough accounted for low-grade FL's unsatisfactory CR rate, designing the first dosage of rituximab should be a very important component of individualized therapy for FL.
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Liu YX, Wen H, Niu WJ, Li JJ, Li ZL, Jiao Z. External Evaluation of Vancomycin Population Pharmacokinetic Models at Two Clinical Centers. Front Pharmacol 2021; 12:623907. [PMID: 33897418 PMCID: PMC8058705 DOI: 10.3389/fphar.2021.623907] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 01/15/2021] [Indexed: 01/19/2023] Open
Abstract
Background: Numerous vancomycin population pharmacokinetic models in neonates have been published; however, their predictive performances remain unknown. This study aims to evaluate their external predictability and explore the factors that might affect model performance. Methods: Published population pharmacokinetic models in neonates were identified from the literature and evaluated using datasets from two clinical centers, including 171 neonates with a total of 319 measurements of vancomycin levels. Predictive performance was assessed by prediction- and simulation-based diagnostics and Bayesian forecasting. Furthermore, the effect of model structure and a number of identified covariates was also investigated. Results: Eighteen published pharmacokinetic models of vancomycin were identified after a systematic literature search. Using prediction-based diagnostics, no model had a median prediction error of ≤ ± 15%, a median absolute prediction error of ≤30%, and a percentage of prediction error that fell within ±30% of >50%. A simulation-based visual predictive check of most models showed there were large deviations between observations and simulations. After Bayesian forecasting with one or two prior observations, the predicted performance improved significantly. Weight, age, and serum creatinine were identified as the most important covariates. Moreover, employing a maturation model based on weight and age as well as nonlinear model to incorporate serum creatinine level significantly improved predictive performance. Conclusion: The predictability of the pharmacokinetic models for vancomycin is closely related to the approach used for modeling covariates. Bayesian forecasting can significantly improve the predictive performance of models.
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Affiliation(s)
- Yi-Xi Liu
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
- Department of Pharmacy, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Haini Wen
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Wan-Jie Niu
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Jing-Jing Li
- Department of Pharmacy, Suzhou Hospital Affiliated to Nanjing Medical University, Suzhou, China
| | - Zhi-Ling Li
- Department of Pharmacy, Shanghai Children’s Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
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15
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Li DY, Li L, Li GZ, Hu YH, Guo HL, Jing X, Chen F, Ji X, Xu J, Dai HR. Population Pharmacokinetics Modeling of Vancomycin Among Chinese Infants With Normal and Augmented Renal Function. Front Pediatr 2021; 9:713588. [PMID: 34616698 PMCID: PMC8489377 DOI: 10.3389/fped.2021.713588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 08/06/2021] [Indexed: 11/29/2022] Open
Abstract
There have been good amounts of population pharmacokinetics (PPK) models of vancomycin for Chinese pediatric patients, but none of them had a special focus on modeling infant population with different levels of renal function. Since renal function variability is prominent among infant population and the clearance (CL) of vancomycin is heavily related to renal excretion, it is important to establish precise PPK models based on individual renal function levels. We employed a PPK approach to develop three models of vancomycin in parallel for Chinese pediatric patients with normal renal function [estimated glomerular filtration rate (eGFR) between 30 and 86 ml/min/1.73 m2, Model 1], with augmented renal function (eGFR ≥ 86 ml/min/1.73 m2, Model 2), or with all levels of renal function (Model 3). Three one-compartment models with first-order elimination kinetics were established. The predictive ability of Model 1 and Model 2 among each certain population is comparable with that of Model 3 with no statistical difference. Our study revealed that among the infant population with augmented renal function, only body weight was included as a covariate, which indicated that for an infant whose eGFR ≥ 86 ml/min/1.73 m2, taking blood sample is not compulsory for predicting vancomycin blood concentration, which avoids unnecessary injury to vulnerable infants.
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Affiliation(s)
- De-Yi Li
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Ling Li
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Gui-Zhou Li
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Ya-Hui Hu
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Hong-Li Guo
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Xia Jing
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Feng Chen
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Xing Ji
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Jing Xu
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Hao-Ran Dai
- Pharmaceutical Sciences Research Center, Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China.,School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
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16
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Germovsek E, Osborne L, Gunaratnam F, Lounis SA, Busquets FB, Standing JF, Sinha AK. Development and external evaluation of a population pharmacokinetic model for continuous and intermittent administration of vancomycin in neonates and infants using prospectively collected data. J Antimicrob Chemother 2020; 74:1003-1011. [PMID: 30668696 DOI: 10.1093/jac/dky525] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 11/05/2018] [Accepted: 11/16/2018] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Vancomycin is commonly used for nosocomial bacterial pathogens causing late-onset septicaemia in preterm infants. We prospectively collected pharmacokinetic data aiming to describe pharmacokinetics and determine covariates contributing to the variability in neonatal vancomycin pharmacokinetics. Further, we aimed to use the model to compare the ratio of AUC24 at steady-state to the MIC (AUC24,ss/MIC) of several intermittent and continuous dosing regimens. METHODS Newborns receiving vancomycin for suspected or confirmed late-onset sepsis were included. Peak and trough concentrations for intermittent vancomycin dosing and steady-state concentrations for continuous vancomycin dosing were measured. NONMEM 7.3 was used for population pharmacokinetic analysis. Monte Carlo simulations were performed to compare dosing schemes. RESULTS Data from 54 infants were used for model development and from 34 infants for the model evaluation {corrected gestational age [median (range)] = 29 (23.7-41.9) weeks and 28 (23.4-41.7) weeks, respectively}. The final model was a one-compartment model. Weight and postmenstrual age were included a priori, and then no additional covariate significantly improved the model fit. Final model parameter estimates [mean (SEM)]: CL = 5.7 (0.3) L/h/70 kg and V = 39.3 (3.7) L/70 kg. Visual predictive check of the evaluation dataset confirmed the model can predict external data. Simulations using MIC of 1 mg/L showed that for neonates with gestational age ≤25 weeks and postnatal age ≤2 weeks AUC24,ss/MIC was lower with the intermittent regimen (median 482 versus 663). CONCLUSIONS A population pharmacokinetic model for continuous and intermittent vancomycin administration in infants was developed. Continuous administration might be favourable for treating infections caused by resistant microorganisms in very young and immature infants.
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Affiliation(s)
- Eva Germovsek
- Inflammation, Infection and Rheumatology Section, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, UK.,Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden
| | - Leanne Osborne
- Neonatal Unit, Royal London Hospital, Barts Health NHS Trust, Whitechapel Road, Whitechapel, London, UK
| | - Flora Gunaratnam
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, UK
| | - Shehrazed A Lounis
- Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, UK
| | - Ferran Bossacoma Busquets
- Inflammation, Infection and Rheumatology Section, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, UK.,Hospital Sant Joan de Deu, Passeig Hospital Sant Joan de Deu 2, Barcelona, Spain
| | - Joseph F Standing
- Inflammation, Infection and Rheumatology Section, UCL Great Ormond Street Institute of Child Health, University College London, 30 Guilford Street, London, UK
| | - Ajay K Sinha
- Neonatal Unit, Royal London Hospital, Barts Health NHS Trust, Whitechapel Road, Whitechapel, London, UK.,Centre for Genomics and Child Health, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London, UK
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17
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Dinu V, Lu Y, Weston N, Lithgo R, Coupe H, Channell G, Adams GG, Torcello Gómez A, Sabater C, Mackie A, Parmenter C, Fisk I, Phillips-Jones MK, Harding SE. The antibiotic vancomycin induces complexation and aggregation of gastrointestinal and submaxillary mucins. Sci Rep 2020; 10:960. [PMID: 31969624 PMCID: PMC6976686 DOI: 10.1038/s41598-020-57776-3] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 12/19/2019] [Indexed: 01/14/2023] Open
Abstract
Vancomycin, a branched tricyclic glycosylated peptide antibiotic, is a last-line defence against serious infections caused by staphylococci, enterococci and other Gram-positive bacteria. Orally-administered vancomycin is the drug of choice to treat pseudomembranous enterocolitis in the gastrointestinal tract. However, the risk of vancomycin-resistant enterococcal infection or colonization is significantly associated with oral vancomycin. Using the powerful matrix-free assay of co-sedimentation analytical ultracentrifugation, reinforced by dynamic light scattering and environmental scanning electron microscopy, and with porcine mucin as the model mucin system, this is the first study to demonstrate strong interactions between vancomycin and gastric and intestinal mucins, resulting in very large aggregates and depletion of macromolecular mucin and occurring at concentrations relevant to oral dosing. In the case of another mucin which has a much lower degree of glycosylation (~60%) - bovine submaxillary mucin - a weaker but still demonstrable interaction is observed. Our demonstration - for the first time - of complexation/depletion interactions for model mucin systems with vancomycin provides the basis for further study on the implications of complexation on glycopeptide transit in humans, antibiotic bioavailability for target inhibition, in situ generation of resistance and future development strategies for absorption of the antibiotic across the mucus barrier.
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Affiliation(s)
- Vlad Dinu
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
- Division of Food Science, School of Biosciences, Sutton Bonington, LE12 5RD, UK
| | - Yudong Lu
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
| | - Nicola Weston
- Nottingham Nanoscale and Microscale Research Centre, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ryan Lithgo
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
| | - Hayley Coupe
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
| | - Guy Channell
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
- Division of Food Science, School of Biosciences, Sutton Bonington, LE12 5RD, UK
| | - Gary G Adams
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK
- School of Health Sciences, University of Nottingham, Nottingham, NG7 2HA, UK
| | | | - Carlos Sabater
- School of Food Science & Nutrition, University of Leeds, Leeds, LS2 9JT, UK
- Department of Bioactivity and Food Analysis, Institute of Food Science Research (CSIC-UAM), Nicolás Cabrera 9, 28049, Madrid, Spain
| | - Alan Mackie
- School of Food Science & Nutrition, University of Leeds, Leeds, LS2 9JT, UK
| | - Christopher Parmenter
- Nottingham Nanoscale and Microscale Research Centre, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
| | - Ian Fisk
- Division of Food Science, School of Biosciences, Sutton Bonington, LE12 5RD, UK
| | - Mary K Phillips-Jones
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK.
| | - Stephen E Harding
- National Centre for Macromolecular Hydrodynamics, School of Biosciences, University of Nottingham, Sutton Bonington, LE12 5RD, UK.
- Kulturhistorisk Museum, Universitetet i Oslo, Postboks 6762, St. Olavs plass, 0130, Oslo, Norway.
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18
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Revising Pediatric Vancomycin Dosing Accounting for Nephrotoxicity in a Pharmacokinetic-Pharmacodynamic Model. Antimicrob Agents Chemother 2019; 63:AAC.00067-19. [PMID: 30833429 DOI: 10.1128/aac.00067-19] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Accepted: 02/20/2019] [Indexed: 12/14/2022] Open
Abstract
This study aimed to suggest an initial pediatric vancomycin dose regimen through population pharmacokinetic-pharmacodynamic modeling. A population pharmacokinetic approach was used to analyze vancomycin concentration-time data from a large pediatric cohort. Pharmacokinetic target attainment for patients with bloodstream isolates was compared with clinical outcome using logistic regression and classification and regression trees. Change in serum creatinine during treatment was used as an indicator of acute nephrotoxicity. Probability of acute kidney injury (50% increase from baseline) or kidney failure (75% increase from baseline) was evaluated using logistic regression. An initial dosing regimen was derived, personalized by age, weight, and serum creatinine, using stochastic simulations. Data from 785 hospitalized pediatric patients (1 day to 21 years of age) with suspected Gram-positive infections were collected. Estimated (relative standard error) typical clearance, volume of distribution 1, intercompartmental clearance, and volume of distribution 2 were (standardized to 70 kg) 4.84 (2.38) liters/h, 39.9 (8.15) liters, 3.85 (17.3) liters/h, and 37.8 (10.2) liters, respectively. While cumulative vancomycin exposure correlated positively with the development of nephrotoxicity (713 patients), no clear relationship between vancomycin area under the plasma concentration-time curve and efficacy was found (102 patients). Predicted probability of acute kidney injury and kidney failure with the optimized dosing regimen at day 5 was 10 to 15% and 5 to 10%, increasing by approximately 50% on day 7 and roughly 100% on day 10 across all age groups. This study presents the first data-driven pediatric dose selection to date accounting for nephrotoxicity, and it indicates that cumulative vancomycin exposure best describes risk of acute kidney injury and acute kidney failure.
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Fan S, Li A, Chen A. Perception of Lexical Neutral Tone Among Adults and Infants. Front Psychol 2018; 9:322. [PMID: 29628900 PMCID: PMC5876512 DOI: 10.3389/fpsyg.2018.00322] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Accepted: 02/26/2018] [Indexed: 11/13/2022] Open
Abstract
Neutral tone (T0) is a special tone form in Mandarin that contains tonal and stress information. Compared with canonical tones, T0 has a much shorter duration and reduced pitch contour. Its tonal contour is determined by the preceding canonical tone. However, not much is known about the perception of tonal and stress information in T0. In the current study, we investigate (1) whether T0 can be perceived as lexically unstressed by stress-language listeners; and (2) how Mandarin (tone language)- and Dutch (stress language)-learning infants perceive T0. Three experiments were conducted. In Experiment 1, Dutch adults identified T0 as unstressed when presented with disyllabic sequences ending in T0. In Experiment 2, we used the visual fixation paradigm to test 4- to 6-month-old and 10- to 12-month-old Dutch and Mandarin infants on pseudoword discrimination (/pan1san4/ [high-level + high-falling] and /pan1san0/ [high-level + mid-falling]). T4 and T0 each exhibit a similar falling contour. The results show that (1) after being habituated to neutral tone sequences (/pan1san0/), Dutch infants discriminated the T1T0-T1T4 contrast; and (2) neither age groups of Mandarin infants discriminated the tone contrast. Assuming Mandarin infants' lack of discrimination might be due to the similar F0 contours, we tested Mandarin infants in Experiment 3 using a more salient contrast, /pan1san2/ (high-level + mid-rising) and /pan1san0/. While no overall discrimination was observed, those who were habituated to /pan1san0/ demonstrated discrimination. The continuous discrimination of Dutch infants suggests that they might process neutral-canonical tone contrast as lexical stress rather than as tonal information. Overall, Mandarin infants' failure implies that the representation of T0 is not complete during their 1st year of life; the acquisition of tonal categories may therefore take longer than we expected.
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Affiliation(s)
- Shanshan Fan
- School of Preparatory Education, Beijing Language and Culture University, Beijing, China
- Institute of Linguistics, Chinese Academy of Social Sciences, Beijing, China
| | - Aijun Li
- Institute of Linguistics, Chinese Academy of Social Sciences, Beijing, China
| | - Ao Chen
- School of Communication Science, Beijing Language and Culture University, Beijing, China
- Utrecht Institute of Linguistics OTS, Utrecht University, Utrecht, Netherlands
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