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Mao J, Zeng F, Qin W, Hu M, Xu L, Cheng F, Zhong M, Zhang Y. A joint population pharmacokinetic model to assess the high variability of whole-blood and intracellular tacrolimus in early adult renal transplant recipients. Int Immunopharmacol 2024; 137:112535. [PMID: 38908078 DOI: 10.1016/j.intimp.2024.112535] [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: 04/22/2024] [Revised: 06/17/2024] [Accepted: 06/18/2024] [Indexed: 06/24/2024]
Abstract
Tacrolimus (TAC) has high pharmacokinetic (PK) variability during the early transplantation period. The relationships between whole-blood and intracellular TAC concentrations and clinical outcomes remain controversial. This study identifies the factors affecting the PK variability of TAC and characterizes the relationships between whole-blood and intracellular TAC concentrations. Data regarding whole-blood TAC concentrations of 1,787 samples from 215 renal transplant recipients (<90 days postoperative) across two centers and intracellular TAC concentrations (648 samples) digitized from previous studies were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were screened, and the distribution of whole-blood to intracellular TAC concentration ratios (RWB:IC) was estimated. The final model was evaluated using bootstrap, goodness of fit, and prediction-corrected visual predictive checks. The optimal dosing regimens and target ranges for each type of immune cell subsets were determined using Monte Carlo simulations. A two-compartment model adequately described the data, and the estimated mean TAC CL/F was 23.6 L·h-1 (relative standard error: 11.5 %). The hematocrit level, CYP3A5*3 carrier status, co-administration with Wuzhi capsules, and tapering prednisolone dose may contribute to the high variability of TAC PK variability during the early post-transplant period. The estimated RWB:IC of all TAC concentrations in peripheral blood mononuclear cells (PBMCs) was 4940, and inter-center variability of PBMCs was observed. The simulated TAC target range in PBMCs was 20.2-85.9 pg·million cells-1. Inter-center variability in intracellular concentrations should be taken into account in further analyses. TAC dosage adjustments can be guided based on PK/PD variability and simulated intracellular concentrations.
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Affiliation(s)
- Junjun Mao
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai 200040, China.
| | - Fang Zeng
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jie Fang Road, Wuhan, Hubei 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, 1277 Jie Fang Road, Wuhan, Hubei 430022, China
| | - Weiwei Qin
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai 200040, China
| | - Min Hu
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jie Fang Road, Wuhan, Hubei 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, 1277 Jie Fang Road, Wuhan, Hubei 430022, China
| | - Luyang Xu
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai 200040, China
| | - Fang Cheng
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jie Fang Road, Wuhan, Hubei 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, 1277 Jie Fang Road, Wuhan, Hubei 430022, China
| | - Mingkang Zhong
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai 200040, China.
| | - Yu Zhang
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1277 Jie Fang Road, Wuhan, Hubei 430022, China; Hubei Province Clinical Research Center for Precision Medicine for Critical Illness, 1277 Jie Fang Road, Wuhan, Hubei 430022, China.
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McCann S, Helfer VE, Balevic SJ, Hornik CD, Goldstein SL, Autmizguine J, Meyer M, Al-Uzri A, Anderson SG, Payne EH, Turdalieva S, Gonzalez D. Using Real-World Data to Externally Evaluate Population Pharmacokinetic Models of Dexmedetomidine in Children and Infants. J Clin Pharmacol 2024; 64:963-974. [PMID: 38545761 DOI: 10.1002/jcph.2434] [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: 12/22/2023] [Accepted: 03/04/2024] [Indexed: 07/30/2024]
Abstract
Dexmedetomidine is a sedative used in both adults and off-label in children with considerable reported pharmacokinetic (PK) interindividual variability affecting drug exposure across populations. Several published models describe the population PKs of dexmedetomidine in neonates, infants, children, and adolescents, though very few have been externally evaluated. A prospective PK dataset of dexmedetomidine plasma concentrations in children and young adults aged 0.01-19.9 years was collected as part of a multicenter opportunistic PK study. A PubMed search of studies reporting dexmedetomidine PK identified five population PK models developed with data from demographically similar children that were selected for external validation. A total of 168 plasma concentrations from 102 children were compared with both population (PRED) and individualized (IPRED) predicted values from each of the five published models by quantitative and visual analyses using NONMEM (v7.3) and R (v4.1.3). Mean percent prediction errors from observed values ranged from -1% to 120% for PRED, and -24% to 60% for IPRED. The model by James et al, which was developed using similar "real-world" data, nearly met the generalizability criteria from IPRED predictions. Other models developed using clinical trial data may have been limited by inclusion/exclusion criteria and a less racially diverse population than this study's opportunistic dataset. The James model may represent a useful, but limited tool for model-informed dosing of hospitalized children.
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Affiliation(s)
- Sean McCann
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Victória E Helfer
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Stephen J Balevic
- Department of Pediatrics, Duke University Medical Center, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | - Chi D Hornik
- Department of Pediatrics, Duke University Medical Center, Durham, NC, USA
- Duke Clinical Research Institute, Durham, NC, USA
| | | | - Julie Autmizguine
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine, Montreal, Quebec, Canada
| | - Marisa Meyer
- Critical Care Medicine, Nemours Children's Hospital, Delaware, Wilmington, DE, USA
| | - Amira Al-Uzri
- Oregon Health and Science University, Portland, OR, USA
| | | | | | | | - Daniel Gonzalez
- Duke Clinical Research Institute, Durham, NC, USA
- Division of Clinical Pharmacology, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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Komenkul V, Sukarnjanaset W, Komolmit P, Wattanavijitkul T. External validation of population pharmacokinetic models of tacrolimus in Thai adult liver transplant recipients. Eur J Clin Pharmacol 2024; 80:1229-1240. [PMID: 38695888 DOI: 10.1007/s00228-024-03692-8] [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: 01/09/2024] [Accepted: 04/17/2024] [Indexed: 07/06/2024]
Abstract
OBJECTIVE Several population pharmacokinetic models of tacrolimus in liver transplant patients were built, and their predictability was evaluated in their settings. However, the extrapolation in the prediction was unclear. This study aimed to evaluate the predictive performance of published tacrolimus models in adult liver transplant recipients using data from the Thai population as an external dataset. METHODS The selected published models were systematically searched and evaluated for their quality. The external dataset of patients who underwent the first liver transplant and received immediate-release tacrolimus was used to assess the predictive performance of each selected model. Trough concentrations between 3 and 6 months were retrospectively collected to evaluate the predictability of each model using prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. RESULTS Sixty-seven patients with 360 trough concentrations and eight selected published models were included in this study. None of the models met the predictive precision criteria in prediction-based diagnostics. Meanwhile, four published population pharmacokinetic models showed a normal distribution in NPDE testing. Regarding Bayesian forecasting, all models improved their forecasts with at least one prior information data point. CONCLUSION Bayesian forecasting is more accurate and precise than other testing methods for predicting drug concentrations. However, none of the evaluated models provides satisfactory predictive performance for generalization to Thai liver transplant patients. This underscores the need for future research to develop population PK models tailored to the Thai population. Such efforts should consider the inclusion of nonlinear pharmacokinetics and region-specific factors, including genetic variability, to improve model accuracy and applicability.
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Affiliation(s)
- Virunya Komenkul
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Waroonrat Sukarnjanaset
- Department of Pharmaceutical Care, College of Pharmacy, Rangsit University, Pathum Thani, Thailand
| | - Piyawat Komolmit
- Division of Gastro-enterology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Liver Diseases, King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand
| | - Thitima Wattanavijitkul
- Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Chulalongkorn University, Bangkok, Thailand.
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Kirubakaran R, Singh RM, Carland JE, Day RO, Stocker SL. Evaluation of Published Population Pharmacokinetic Models to Inform Tacrolimus Therapy in Adult Lung Transplant Recipients. Ther Drug Monit 2024; 46:434-445. [PMID: 38723160 DOI: 10.1097/ftd.0000000000001210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 02/15/2024] [Indexed: 07/12/2024]
Abstract
BACKGROUND The applicability of currently available tacrolimus population pharmacokinetic models in guiding dosing for lung transplant recipients is unclear. In this study, the predictive performance of relevant tacrolimus population pharmacokinetic models was evaluated for adult lung transplant recipients. METHODS Data from 43 lung transplant recipients (1021 tacrolimus concentrations) administered an immediate-release oral formulation of tacrolimus were used to evaluate the predictive performance of 17 published population pharmacokinetic models for tacrolimus. Data were collected from immediately after transplantation up to 90 days after transplantation. Model performance was evaluated using (1) prediction-based assessments (bias and imprecision) of individual predicted tacrolimus concentrations at the fourth dosing based on 1 to 3 previous dosings and (2) simulation-based assessment (prediction-corrected visual predictive check; pcVPC). Both assessments were stratified based on concomitant azole antifungal use. Model performance was clinically acceptable if the bias was within ±20%, imprecision was ≤20%, and the 95% confidence interval of bias crossed zero. RESULTS In the presence of concomitant antifungal therapy, no model showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33), and pcVPC plots displayed poor model fit to the data set. However, this fit slightly improved in the absence of azole antifungal use, where 4 models showed acceptable performance in predicting tacrolimus concentrations at the fourth dosing (n = 33). CONCLUSIONS Although none of the evaluated models were appropriate in guiding tacrolimus dosing in lung transplant recipients receiving concomitant azole antifungal therapy, 4 of these models displayed potential applicability in guiding dosing in recipients not receiving concomitant azole antifungal therapy. However, further model refinement is required before the widespread implementation of such models in clinical practice.
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Affiliation(s)
- Ranita Kirubakaran
- School of Clinical Medicine, St. Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia
- Department of Pharmacy, Ministry of Health, Putrajaya, Malaysia
- School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
| | - Rani M Singh
- School of Clinical Medicine, St. Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia
| | - Jane E Carland
- School of Clinical Medicine, St. Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia
| | - Richard O Day
- School of Clinical Medicine, St. Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia
| | - Sophie L Stocker
- School of Clinical Medicine, St. Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
- Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia
- School of Pharmacy, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia
- Sydney Institute for Infectious Diseases, University of Sydney, Sydney, NSW, Australia ; and
- Sydney Musculoskeletal Health, University of Sydney, Sydney, NSW, Australia
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5
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Li X, Cheng Y, Zhang B, Chen B, Chen Y, Huang Y, Lin H, Zhou L, Zhang H, Liu M, Que W, Qiu H. A systematic evaluation of population pharmacokinetic models for polymyxin B in patients with liver and/or kidney dysfunction. J Pharmacokinet Pharmacodyn 2024:10.1007/s10928-024-09916-9. [PMID: 38625507 DOI: 10.1007/s10928-024-09916-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 03/21/2024] [Indexed: 04/17/2024]
Abstract
Polymyxin B (PMB) is considered a last-line treatment for multidrug-resistant (MDR) gram-negative bacterial infections. Model-informed precision dosing with population pharmacokinetics (PopPK) models could help to individualize PMB dosing regimens and improve therapy. However, the external prediction ability of the established PopPK models has not been fully elaborated. This study aimed to systemically evaluate eleven PMB PopPK models from ten published literature based on a new independent population, which was divided into four different populations, patients with liver dysfunction, kidney dysfunction, liver and kidney dysfunction, and normal liver and kidney function. The whole data set consisted of 146 patients with 391 PMB concentrations. The prediction- and simulation-based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. In the overall evaluation process, none of the models exhibited satisfactory predictive ability in both prediction- and simulation-based diagnostic simultaneously. However, the evaluation of the models in the subgroup of patients with normal liver and kidney function revealed improved predictive performance compared to those with liver and/or kidney dysfunction. Bayesian forecasting demonstrated enhanced predictability with the incorporation of two to three prior observations. The external evaluation highlighted a lack of consistency between the prediction results of published models and the external validation dataset. Nonetheless, Bayesian forecasting holds promise in improving the predictive performance of the models, and feedback from therapeutic drug monitoring is crucial in optimizing individual dosing regimens.
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Affiliation(s)
- Xueyong Li
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China
| | - Yu Cheng
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China
| | - Bingqing Zhang
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China
| | - Bo Chen
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China
| | - Yiying Chen
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China
| | - Yingbing Huang
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China
| | - Hailing Lin
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China
| | - Lili Zhou
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou, 350001, People's Republic of China
| | - Hui Zhang
- Department of Critical Care Medicine, Fujian Medical University Union Hospital, Fuzhou, 350001, People's Republic of China
| | - Maobai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China
| | - Wancai Que
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China.
| | - Hongqiang Qiu
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Rd, Fuzhou, 350001, Fujian, People's Republic of China.
- College of Pharmacy, Fujian Medical University, Fuzhou, 350004, People's Republic of China.
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6
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Chen S, Huang L, Huang W, Zheng Y, Shen L, Liu M, Chen W, Wu X. External Evaluation of Population Pharmacokinetic Models for High-Dose Methotrexate in Adult Patients with Hematological Tumors. J Clin Pharmacol 2024; 64:437-448. [PMID: 38081138 DOI: 10.1002/jcph.2392] [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: 08/22/2023] [Accepted: 12/05/2023] [Indexed: 01/13/2024]
Abstract
Currently, numerous population pharmacokinetic (popPK) models for methotrexate (MTX) have been published for estimating PK parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high-dose MTX (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The software package NONMEM was used to perform an external evaluation for each model, including prediction-based diagnosis, simulation-based diagnosis, and Bayesian forecasting. The simulation-based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, 7 candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. The published popPK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our data set. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.
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Affiliation(s)
- Shengyang Chen
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Lifeng Huang
- National Drug Clinical Trial Institution, Shanghai University of Medicine & Health Sciences Affiliated Zhoupu Hospital, Pudong New District, Shanghai, China
| | - Weikun Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - You Zheng
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Li Shen
- Department of Pharmacy, Suzhou Hospital, Affiliated Hospital of Medical School, Nanjing University, Suzhou, Jiangsu, China
| | - Maobai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Wansheng Chen
- Department of Pharmacy, Second Affiliated Hospital of Naval Medical University, Shanghai, China
- Traditional Chinese Medicine Resource and Technology Center, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xuemei Wu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
- School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
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Alsultan A, Dasuqi SA, Almohaizeie A, Aljutayli A, Aljamaan F, Omran RA, Alolayan A, Hamad MA, Alotaibi H, Altamimi S, Alghanem SS. External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese. J Clin Pharmacol 2024; 64:353-361. [PMID: 37862131 DOI: 10.1002/jcph.2375] [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: 07/27/2023] [Accepted: 10/17/2023] [Indexed: 10/22/2023]
Abstract
Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.
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Affiliation(s)
- Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Shereen A Dasuqi
- Department of Pharmacy, King Khalid University Hospital, King Saud University Medical City, Riyadh, Saudi Arabia
| | - Abdullah Almohaizeie
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Abdullah Aljutayli
- Department of Pharmaceutics, Faculty of Pharmacy, Qassim University, Riyadh, Saudi Arabia
| | - Fadi Aljamaan
- College of Medicine, King Saud University, Riyadh, Saudi Arabia
- Critical Care Department, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
| | - Rasha A Omran
- Department of Pharmaceutics and Pharmaceutical Technology, School of Pharmacy, University of Jordan, Amman, Jordan
| | - Abdulaziz Alolayan
- Pharmacy Department, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia, Riyadh, Saudi Arabia
| | - Mohammed A Hamad
- Critical Care Department, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia
- Department of Acute Medicine, Wirral University Teaching Hospital NHS Foundation Trust, Arrowe Park Hospital, Wirral, UK
| | - Haifa Alotaibi
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sarah Altamimi
- Pharmaceutical Care Division, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Sarah S Alghanem
- Department of Pharmacy Practice, College of Pharmacy at Kuwait University, Safat, Kuwait
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Leino AD, Magee JC, Kershaw DB, Pai MP, Park JM. A Comprehensive Mixed-Method Approach to Characterize the Source of Diurnal Tacrolimus Exposure Variability in Children: Systematic Review, Meta-analysis, and Application to an Existing Data Set. J Clin Pharmacol 2024; 64:334-344. [PMID: 37740566 DOI: 10.1002/jcph.2352] [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: 06/29/2023] [Accepted: 09/13/2023] [Indexed: 09/24/2023]
Abstract
Tacrolimus is widely reported to display diurnal variation in pharmacokinetic parameters with twice-daily dosing. However, the contribution of chronopharmacokinetics versus food intake is unclear, with even less evidence in the pediatric population. The objectives of this study were to summarize the existing literature by meta-analysis and evaluate the impact of food composition on 24-hour pharmacokinetics in pediatric kidney transplant recipients. For the meta-analysis, 10 studies involving 253 individuals were included. The pooled effect sizes demonstrated significant differences in area under the concentration-time curve from time 0 to 12 hours (standardized mean difference [SMD], 0.27; 95% confidence interval [CI], 0.03-0.52) and maximum concentration (SMD, 0.75; 95% CI, 0.35-1.15) between morning and evening dose administration. However, there was significant between-study heterogeneity that was explained by food exposure. The effect size for minimum concentration was not significantly different overall (SMD, -0.09; 95% CI, -0.27 to 0.09) or across the food exposure subgroups. A 2-compartment model with a lag time, linear clearance, and first-order absorption best characterized the tacrolimus pharmacokinetics in pediatric participants. As expected, adding the time of administration and food composition covariates reduced the unexplained within-subject variability for the first-order absorption rate constant, but only caloric composition significantly reduced variability for lag time. The available data suggest food intake is the major driver of diurnal variation in tacrolimus exposure, but the associated changes are not reflected by trough concentrations alone.
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Affiliation(s)
- Abbie D Leino
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA
| | - John C Magee
- Department of Surgery, Medical School, University of Michigan, Ann Arbor, MI, USA
| | - David B Kershaw
- Department of Pediatrics, C.S. Mott Children's Hospital, Ann Arbor, MI, USA
| | - Manjunath P Pai
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA
| | - Jeong M Park
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, USA
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9
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Nguyen TVA, Le BH, Nguyen MT, Le VT, Tran VT, Le DT, Vu DAM, Truong QK, Le TH, Nguyen HTL. Pharmacogenomic Analysis of CYP3A5*3 and Tacrolimus Trough Concentrations in Vietnamese Renal Transplant Outcomes. Pharmgenomics Pers Med 2024; 17:53-64. [PMID: 38332855 PMCID: PMC10850765 DOI: 10.2147/pgpm.s439400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/18/2024] [Indexed: 02/10/2024] Open
Abstract
Purpose CYP3A5 polymorphisms have been associated with variations in the pharmacokinetics of tacrolimus (Tac) in kidney transplant patients. Our study aims to quantify how the CYP3A5 genotype influences tacrolimus trough concentrations (C0) in a Vietnamese outpatient population by selecting an appropriate population pharmacokinetic model of Tac for our patients. Patients and Methods The external dataset was obtained prospectively from 54 data of adult kidney transplant recipients treated at the 103 Military Hospital. All published Tac population pharmacokinetic models were systematically screened from PubMed and Scopus databases and were selected based on our patient's available characteristics. Mean absolute prediction error (MAPE), mean prediction error, and goodness-of-fit plots were used to identify the appropriate model for finding the formula that identifies the influence of CYP3A5 genotype on the pharmacokinetic data of Vietnamese patients. Results The model of Zhu et al had a good predictive ability with MAPE of 19.29%. The influence of CYP3A5 genotype on tacrolimus clearance was expressed by the following formulas: CL/F=27 , 2 × [ ( WT/70 ) 0 , 75 ] × [ ( HCT/0 , 35 ) -0 , 501 ] × [ ( POD/180 ) 0 , 0306 ] × CYP3A5 ( L/h ) . The simulation result showed that Tac C0 was significantly higher in patients not expressing CYP3A5 (p< 0.001). Conclusion The incorporation of the CYP3A5 phenotype into Zhu's structural model has significantly enhanced our ability to predict Tacrolimus trough levels in the Vietnamese population. This study's results underscore the valuable role of CYP3A5 phenotype in optimizing the forecast of Tac concentrations, offering a promising avenue to assist health-care practitioners in their clinical decision-making and ultimately advance patient care outcomes.
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Affiliation(s)
| | - Ba Hai Le
- Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - Minh Thanh Nguyen
- Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - Viet Thang Le
- Department of Nephrology and Dialysis, 103 Military Hospital, Hanoi, Vietnam
| | - Viet Tien Tran
- Department of Infectious Diseases, 103 Military Hospital, Hanoi, Vietnam
| | - Dinh Tuan Le
- Department of Rheumatology and Endocrinology, 103 Military Hospital, Hanoi, Vietnam
| | - Duong Anh Minh Vu
- Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam
| | - Quy Kien Truong
- Department of Nephrology and Dialysis, 103 Military Hospital, Hanoi, Vietnam
| | - Trong Hieu Le
- Department of Clinical Pharmacy, Hanoi University of Pharmacy, Hanoi, Vietnam
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Abderahmene A, Francke MI, Andrews LM, Hesselink DA, Amor D, Sahtout W, Ajmi M, Mastouri H, Bouslama A, Zellama D, Omezzine A, De Winter BCM. A Population Pharmacokinetic Model to Predict the Individual Starting Dose of Tacrolimus for Tunisian Adults after Renal Transplantation. Ther Drug Monit 2024; 46:57-66. [PMID: 38018879 DOI: 10.1097/ftd.0000000000001147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 07/23/2023] [Indexed: 11/30/2023]
Abstract
BACKGROUND Tacrolimus is the most frequently used immunosuppressive drug for preventing renal rejection. However, its use is hampered by its narrow therapeutic index and large intra and interpatient variability in pharmacokinetics. The objective of this study was to externally validate a tacrolimus population pharmacokinetic model developed for the Dutch population and adjust the model for the Tunisian population for use in predicting the starting dose requirement after kidney transplantation. METHODS Data on tacrolimus exposure were obtained from kidney transplant recipients (KTRs) during the first 3 months post-transplantation. External validation of the Dutch model and its adjustment for the Tunisian population was performed using nonlinear mixed-effects modeling. RESULTS In total, 1901 whole-blood predose tacrolimus concentrations from 196 adult KTRs were analyzed. According to a visual predictive check, the Dutch model underestimated the starting dose for the Tunisian adult population. The effects of age, together with the CYP3A5*3 and CYP3A4*22 genotypes on tacrolimus clearance were significantly different in the Tunisian population than in the Dutch population. Based on a bodyweight-based dosing, only 21.9% of tacrolimus concentrations were within the target range, whereas this was estimated to be 54.0% with the newly developed model-based dosing. After adjustment, the model was successfully validated internally in a Tunisian population. CONCLUSIONS A starting-dose population pharmacokinetic model of tacrolimus for Tunisian KTRs was developed based on a previously published Dutch model. Using this starting dose could potentially increase the percentage of patients achieving target tacrolimus concentrations after the initial starting dose.
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Affiliation(s)
- Amani Abderahmene
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
- Rotterdam Clinical Pharmacometrics Group, Rotterdam, the Netherlands
| | - Marith I Francke
- Rotterdam Clinical Pharmacometrics Group, Rotterdam, the Netherlands
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Erasmus MC Transplant Institute, Rotterdam, the Netherlands
| | - Louise M Andrews
- Department of Hospital Pharmacy, Meander MC, Amersfoort, the Netherlands
| | - Dennis A Hesselink
- Division of Nephrology and Transplantation, Department of Internal Medicine, Erasmus MC, University Medical Center, Rotterdam, the Netherlands
- Erasmus MC Transplant Institute, Rotterdam, the Netherlands
| | - Dorra Amor
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
| | - Wissal Sahtout
- Department of Nephrology, Sahloul University Hospital, Sousse, Tunisia; and
| | - Marwa Ajmi
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
| | - Hayfa Mastouri
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
| | - Ali Bouslama
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
| | - Dorsaf Zellama
- Department of Nephrology, Sahloul University Hospital, Sousse, Tunisia; and
| | - Asma Omezzine
- Department of Biochemistry , LR12SP11, Sahloul University Hospital, Sousse, University of Monastir Faculty of Pharmacy of Monastir, Monastir, Tunisia
| | - Brenda C M De Winter
- Rotterdam Clinical Pharmacometrics Group, Rotterdam, the Netherlands
- Erasmus MC Transplant Institute, Rotterdam, the Netherlands
- Department of Hospital Pharmacy, Erasmus MC, University Medical Center Rotterdam, the Netherlands
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Yue Z, Pan C, Wang S, N Tse A, Sheng Y. Clinical pharmacokinetics and pharmacodynamics of ivosidenib in Chinese patients with relapsed or refractory IDH1-mutated acute myeloid leukemia. Eur J Clin Pharmacol 2024; 80:105-113. [PMID: 37917187 DOI: 10.1007/s00228-023-03591-4] [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: 09/14/2023] [Accepted: 10/26/2023] [Indexed: 11/04/2023]
Abstract
PURPOSE This study aimed to assess the pharmacokinetics (PK) and pharmacodynamics (PD) of ivosidenib in Chinese patients with relapsed or refractory acute myeloid leukemia (R/R AML) carrying the mIDH1 mutation. METHODS A bridging study (NCT04176393) was conducted involving 29 Chinese patients who received a daily dose of ivosidenib 500 mg in 28-day cycles. Plasma concentrations of ivosidenib and D-2-hydroxyglutarate (2-HG) were measured before and after treatment. Non-compartmental analysis (NCA) was employed to evaluate the PK, and an established population pharmacokinetic (popPK) model developed from non-Chinese patients was externally validated. RESULTS The findings revealed comparable PD effects of ivosidenib in Chinese patients with mIDH1 R/R AML. After adjusting for concomitant drug effects, PK characteristics were similar between Chinese and non-Chinese patients. Furthermore, the popPK model offered additional insights into the possible causes of the apparent ethnic difference in PK exposure. CONCLUSION The study indicates that ivosidenib can be used effectively in Chinese patients, and the observed ethnic differences in PK exposure can be explained by concomitant drug effects. The popPK model contributes to a better understanding and optimization of personalized dosing in Chinese patients with mIDH1 R/R AML.
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Affiliation(s)
- Zenglian Yue
- CStone Pharmaceuticals (Suzhou) Co. Ltd., Suzhou, China
| | - Chaohsuan Pan
- CStone Pharmaceuticals (Suzhou) Co. Ltd., Suzhou, China
| | - Siyuan Wang
- CStone Pharmaceuticals (Suzhou) Co. Ltd., Suzhou, China
| | - Archie N Tse
- CStone Pharmaceuticals (Suzhou) Co. Ltd., Suzhou, China
| | - Yucheng Sheng
- CStone Pharmaceuticals (Suzhou) Co. Ltd., Suzhou, China.
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El-Khateeb E, Chinnadurai R, Al Qassabi J, Scotcher D, Darwich AS, Kalra PA, Rostami-Hodjegan A. Using Prior Knowledge on Systems Through PBPK to Gain Further Insight into Routine Clinical Data on Trough Concentrations: The Case of Tacrolimus in Chronic Kidney Disease. Ther Drug Monit 2023; 45:743-753. [PMID: 37315152 PMCID: PMC10635338 DOI: 10.1097/ftd.0000000000001108] [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: 01/11/2023] [Accepted: 03/23/2023] [Indexed: 06/16/2023]
Abstract
BACKGROUND Routine therapeutic drug monitoring (TDM) relies heavily on measuring trough drug concentrations. Trough concentrations are affected not only by drug bioavailability and clearance, but also by various patient and disease factors and the volume of distribution. This often makes interpreting differences in drug exposure from trough data challenging. This study aimed to combine the advantages of top-down analysis of therapeutic drug monitoring data with bottom-up physiologically-based pharmacokinetic (PBPK) modeling to investigate the effect of declining renal function in chronic kidney disease (CKD) on the nonrenal intrinsic metabolic clearance ( CLint ) of tacrolimus as a case example. METHODS Data on biochemistry, demographics, and kidney function, along with 1167 tacrolimus trough concentrations for 40 renal transplant patients, were collected from the Salford Royal Hospital's database. A reduced PBPK model was developed to estimate CLint for each patient. Personalized unbound fractions, blood-to-plasma ratios, and drug affinities for various tissues were used as priors to estimate the apparent volume of distribution. Kidney function based on the estimated glomerular filtration rate ( eGFR ) was assessed as a covariate for CLint using the stochastic approximation of expectation and maximization method. RESULTS At baseline, the median (interquartile range) eGFR was 45 (34.5-55.5) mL/min/1.73 m 2 . A significant but weak correlation was observed between tacrolimus CLint and eGFR (r = 0.2, P < 0.001). The CLint declined gradually (up to 36%) with CKD progression. Tacrolimus CLint did not differ significantly between stable and failing transplant patients. CONCLUSIONS Kidney function deterioration in CKD can affect nonrenal CLint for drugs that undergo extensive hepatic metabolism, such as tacrolimus, with critical implications in clinical practice. This study demonstrates the advantages of combining prior system information (via PBPK) to investigate covariate effects in sparse real-world datasets.
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Affiliation(s)
- Eman El-Khateeb
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
- Clinical Pharmacy Department, Faculty of Pharmacy, Tanta University, Tanta, Egypt
| | - Rajkumar Chinnadurai
- Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Jokha Al Qassabi
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
- University of Technology and Applied Sciences, Muscat, Oman; and
| | - Daniel Scotcher
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
| | - Adam S. Darwich
- Logistics and Informatics in Health Care, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Philip A. Kalra
- Northern Care Alliance NHS Foundation Trust, Salford, United Kingdom
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Amin Rostami-Hodjegan
- Certara UK Limited (Simcyp Division), Sheffield, United Kingdom
- Centre for Applied Pharmacokinetic Research, University of Manchester, Manchester, United Kingdom
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13
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Wang CB, Zhang YJ, Zhao MM, Zhao L. Dosage optimization of tacrolimus based on the glucocorticoid dose and pharmacogenetics in adult patients with systemic lupus erythematosus. Int Immunopharmacol 2023; 124:110866. [PMID: 37678026 DOI: 10.1016/j.intimp.2023.110866] [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: 06/26/2023] [Revised: 08/25/2023] [Accepted: 08/26/2023] [Indexed: 09/09/2023]
Abstract
BACKGROUND The purpose of the study was to develop a genotype-incorporated population pharmacokinetic (PPK) model of tacrolimus (TAC) in adults with systemic lupus erythematosus (SLE) to investigate the factors influencing TAC pharmacokinetics and to develop an individualized dosing regimen based on the model. In addition, a non-genotype-incorporated model was also established to assess its predictive performance compared to the genotype-incorporated model. METHODS A total of 365 trough concentrations from 133 adult SLE patients treated with TAC were collected to develop a genotype-incorporated PPK model and a non-genotype-incorporated PPK model of TAC using a nonlinear mixed-effects model (NONMEM). External validation of the two models was performed using data from an additional 29 patients. Goodness-of-fit diagnostic plots, bootstrap method, and normalized predictive distribution error test were used to validate the predictive performance and stability of the final models. The goodness-of-fit of the two final models was compared using the Akaike information criterion (AIC). The dosing regimen was optimized using Monte Carlo simulations based on the developed optimal model. RESULTS The typical value of the apparent clearance (CL/F) of TAC estimated in the final genotype-incorporated model was 14.3 L h-1 with inter-individual variability of 27.6%. CYP3A5 polymorphism and coadministered medication were significant factors affecting TAC-CL/F. CYP3A5 rs776746 GG genotype carriers had only 77.3% of the TAC-CL/F of AA or AG genotype carriers. Omeprazole reduced TAC-CL/F by 3.7 L h-1 when combined with TAC, while TAC-CL/F increased nonlinearly as glucocorticoid dose increased. Similar findings were demonstrated in the non-genotype-incorporated PPK model. Comparing these two models, the genotype-incorporated PPK model was superior to the non-genotype-incorporated PPK model (AIC = 643.19 vs. 657.425). Monte Carlo simulation based on the genotype-incorporated PPK model indicated that CYP3A5 rs776746 AA or AG genotype carriers required a 1/2-1 fold higher dose of TAC than GG genotype carriers to achieve the target concentration. And as the daily dose of prednisone increases, the dose of TAC required to reach the target concentration increases appropriately. CONCLUSIONS We developed the first pharmacogenetic-based PPK model of TAC in adult patients with SLE and proposed a dosing regimen based on glucocorticoid dose and CYP3A5 genotype according to the model, which could facilitate individualized dosing for TAC.
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Affiliation(s)
- Cheng-Bin Wang
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Yu-Jia Zhang
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China
| | - Ming-Ming Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
| | - Limei Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China.
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Zhang L, Liu M, Qin W, Shi D, Mao J, Li Z. Modeling the protein binding non-linearity in population pharmacokinetic model of valproic acid in children with epilepsy: a systematic evaluation study. Front Pharmacol 2023; 14:1228641. [PMID: 37869748 PMCID: PMC10587682 DOI: 10.3389/fphar.2023.1228641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 09/19/2023] [Indexed: 10/24/2023] Open
Abstract
Background: Several studies have investigated the population pharmacokinetics (popPK) of valproic acid (VPA) in children with epilepsy. However, the predictive performance of these models in the extrapolation to other clinical environments has not been studied. Hence, this study evaluated the predictive abilities of pediatric popPK models of VPA and identified the potential effects of protein binding modeling strategies. Methods: A dataset of 255 trough concentrations in 202 children with epilepsy was analyzed to assess the predictive performance of qualified models, following literature review. The evaluation of external predictive ability was conducted by prediction- and simulation-based diagnostics as well as Bayesian forecasting. Furthermore, five popPK models with different protein binding modeling strategies were developed to investigate the discrepancy among the one-binding site model, Langmuir equation, dose-dependent maximum effect model, linear non-saturable binding equation and the simple exponent model on model predictive ability. Results: Ten popPK models were identified in the literature. Co-medication, body weight, daily dose, and age were the four most commonly involved covariates influencing VPA clearance. The model proposed by Serrano et al. showed the best performance with a median prediction error (MDPE) of 1.40%, median absolute prediction error (MAPE) of 17.38%, and percentages of PE within 20% (F20, 55.69%) and 30% (F30, 76.47%). However, all models performed inadequately in terms of the simulation-based normalized prediction distribution error, indicating unsatisfactory normality. Bayesian forecasting enhanced predictive performance, as prior observations were available. More prior observations are needed for model predictability to reach a stable state. The linear non-saturable binding equation had a higher predictive value than other protein binding models. Conclusion: The predictive abilities of most popPK models of VPA in children with epilepsy were unsatisfactory. The linear non-saturable binding equation is more suitable for modeling non-linearity. Moreover, Bayesian forecasting with prior observations improved model fitness.
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Affiliation(s)
- Lina Zhang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Maochang Liu
- Department of Pharmacy, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Weiwei Qin
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Dandan Shi
- Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Junjun Mao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Zeyun Li
- Department of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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15
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Wei S, Chen J, Zhao Z, Mei S. External validation of population pharmacokinetic models of vancomycin in postoperative neurosurgical patients. Eur J Clin Pharmacol 2023; 79:1031-1042. [PMID: 37261482 DOI: 10.1007/s00228-023-03511-6] [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: 02/26/2023] [Accepted: 05/19/2023] [Indexed: 06/02/2023]
Abstract
OBJECTIVE Vancomycin is commonly used in the prevention and treatment of intracranial infections in postoperative neurosurgical patients with narrow therapeutic window and large pharmacokinetic variations. Several population pharmacokinetic (PPK) models of vancomycin have been established for neurosurgical patients. But comprehensive external evaluation has not been performed for almost all models. The objective of this study was to evaluate the predictive ability of published vancomycin PPK models in adult postoperative neurosurgical patients using an independent dataset. METHOD PubMed, Embase and China National Knowledge Internet databases were searched to identify published vancomycin PPK models in adult postoperative neurosurgical patients. Prediction-based and simulation-based diagnostics were used to evaluate model predictability. Bayesian forecasting was used to assess the influence of prior concentration on model prediction performance. RESULT A total of 763 vancomycin plasma concentrations from 493 postoperative neurosurgical patients were included in the external dataset. Eight population pharmacokinetic models of vancomycin in postoperative neurosurgical patients were included and evaluated. The model by Zhang et al. exhibited the best predictive performance in prediction-based diagnostics and prediction-corrected visual predictive checks, followed by the model by Shen et al. The predictive performance of other models was not satisfactory. The normalized predictive distribution error test shows that none of the models is suitable to describe our data. The predictive performance of vancomycin models was obviously improved by maximum a posteriori Bayesian forecasting. CONCLUSION The published PPK models for adult postoperative neurosurgical patients show extensive variation in predictive performance in our patients. Although it is challenging to recommend initial doses of vancomycin from these predictive models, the combination of model-based prediction and therapeutic drug monitoring can be used for dose optimization.
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Affiliation(s)
- Shifeng Wei
- Department of Pharmacy, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Beijing, 100070, People's Republic of China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Jingcheng Chen
- Department of Pharmacy, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Beijing, 100070, People's Republic of China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China
| | - Zhigang Zhao
- Department of Pharmacy, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Beijing, 100070, People's Republic of China.
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.
| | - Shenghui Mei
- Department of Pharmacy, Fengtai District, Beijing Tiantan Hospital, Capital Medical University, 119 Nansihuan West Road, Beijing, 100070, People's Republic of China.
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, 100069, People's Republic of China.
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Rower JE, McKnite A, Hong B, Daly KP, Hope KD, Cabrera AG, Molina KM. External assessment and refinement of a population pharmacokinetic model to guide tacrolimus dosing in pediatric heart transplant. Pharmacotherapy 2023; 43:650-658. [PMID: 37328271 PMCID: PMC10527671 DOI: 10.1002/phar.2836] [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: 11/02/2022] [Revised: 05/03/2023] [Accepted: 05/03/2023] [Indexed: 06/18/2023]
Abstract
STUDY OBJECTIVE The immunosuppressant tacrolimus is a first-line agent to prevent graft rejection following pediatric heart transplant; however, it suffers from extensive inter-patient variability and a narrow therapeutic window. Personalized tacrolimus dosing may improve transplant outcomes by more efficiently achieving and maintaining therapeutic tacrolimus concentrations. We sought to externally validate a previously published population pharmacokinetic (PK) model that was constructed with data from a single site. DATA SOURCE Data were collected from Seattle, Texas, and Boston Children's Hospitals, and assessed using standard population PK modeling techniques in NONMEMv7.2. MAIN RESULTS While the model was not successfully validated for use with external data, further covariate searching identified weight (p < 0.0001 on both volume and elimination rate) as a model-significant covariate. This refined model acceptably predicted future tacrolimus concentrations when guided by as few as three concentrations (median prediction error = 7%; median absolute prediction error = 27%). CONCLUSION These findings support the potential clinical utility of a population PK model to provide personalized tacrolimus dosing guidance.
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Affiliation(s)
- Joseph E. Rower
- Department of Pharmacology and Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
- Center for Human Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
| | - Autumn McKnite
- Department of Pharmacology and Toxicology, University of Utah College of Pharmacy, Salt Lake City, Utah, USA
| | - Borah Hong
- Division of Pediatric Cardiology, University of Washington and Seattle Children’s Hospital, Seattle, Washington, USA
| | - Kevin P. Daly
- Department of Pediatric Cardiology, Harvard Medical School/Boston Children’s Hospital, Boston, Massachusetts, USA
| | - Kyle D. Hope
- Lillie Frank Abercrombie Division of Pediatric Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, Texas, USA
| | - Antonio G. Cabrera
- Lillie Frank Abercrombie Division of Pediatric Cardiology, Department of Pediatrics, Texas Children’s Hospital, Baylor College of Medicine, Houston, Texas, USA
- Division of Pediatric Cardiology, University of Utah/Intermountain Primary Children’s Hospital, Salt Lake City, Utah, USA
| | - Kimberly M. Molina
- Division of Pediatric Cardiology, University of Utah/Intermountain Primary Children’s Hospital, Salt Lake City, Utah, USA
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Chen D, Yao Q, Chen W, Yin J, Hou S, Tian X, Zhao M, Zhang H, Yang L, Zhou T, Jin P. Population PK/PD model of tacrolimus for exploring the relationship between accumulated exposure and quantitative scores in myasthenia gravis patients. CPT Pharmacometrics Syst Pharmacol 2023; 12:963-976. [PMID: 37060188 PMCID: PMC10349186 DOI: 10.1002/psp4.12966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 04/16/2023] Open
Abstract
Tacrolimus is an important immunosuppressant used in the treatment of myasthenia gravis (MG). However, the population pharmacokinetic (PK) characteristics together with the exposure-response of tacrolimus in the treatment of MG remain largely unknown. In this study, we aimed to develop a population PK/pharmacodynamic (PK/PD) model of tacrolimus in patients with MG, in order to explore the relationships among tacrolimus dose, exposure, and its therapeutic efficacy. The genotype of CYP3A5, Osserman's classification, and status of thymus, as well as demographic characteristics and other biomarkers from laboratory testing were tested as covariate, and simulations were performed based on the final model. The population PK model was described using a one-compartment model with first-order elimination and fixed absorption parameters. CYP3A5 genotype significantly influenced the apparent clearance, and total protein (TP) influenced the apparent volume of distribution as covariates. The quantitative MG scores were characterized by the cumulated area under curve of tacrolimus in a maximum effect function. Osserman's classification was a significant covariate on the initial score of patients with MG. The simulations demonstrated that tacrolimus showed an unsatisfying effect possibly due to insufficient exposure in some patients with MG. A starting dose of 2 mg/d and even higher dose for patients with CYP3A5 *1/*1 and *1/*3 and lower TP level were required for the rapid action of tacrolimus. The population PK/PD model quantitatively described the relationships among tacrolimus dose, exposure, and therapeutic efficacy in patients with MG, which could provide reference for the optimization of tacrolimus dosing regimen at the individual patient level.
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Affiliation(s)
- Di Chen
- Department of PharmacyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical ScienceBeijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital)BeijingChina
| | - Qingyu Yao
- Department of PharmaceuticsSchool of Pharmaceutical SciencesPeking UniversityBeijingChina
| | - Wenjun Chen
- Department of PharmaceuticsSchool of Pharmaceutical SciencesPeking UniversityBeijingChina
| | - Jian Yin
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesBeijingChina
| | - Shifang Hou
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesBeijingChina
| | - Xiaoxin Tian
- Department of PharmacyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical ScienceBeijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital)BeijingChina
| | - Ming Zhao
- Department of PharmacyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical ScienceBeijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital)BeijingChina
| | - Hua Zhang
- Department of NeurologyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical SciencesBeijingChina
| | - Liping Yang
- Department of PharmacyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical ScienceBeijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital)BeijingChina
| | - Tianyan Zhou
- Department of PharmaceuticsSchool of Pharmaceutical SciencesPeking UniversityBeijingChina
| | - Pengfei Jin
- Department of PharmacyBeijing HospitalNational Center of GerontologyInstitute of Geriatric MedicineChinese Academy of Medical ScienceBeijing Key Laboratory of Assessment of Clinical Drugs Risk and Individual Application (Beijing Hospital)BeijingChina
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18
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Wang CB, Zhang YJ, Zhao MM, Zhao LM. Population pharmacokinetic analyses of tacrolimus in non-transplant patients: a systematic review. Eur J Clin Pharmacol 2023:10.1007/s00228-023-03503-6. [PMID: 37261481 DOI: 10.1007/s00228-023-03503-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 04/30/2023] [Indexed: 06/02/2023]
Abstract
BACKGROUND AND OBJECTIVES Tacrolimus (TAC) has been increasingly used in patients with non-transplant settings. Because of its large between-subject variability, several population pharmacokinetic (PPK) studies have been performed to facilitate individualized therapy. This review summarized published PPK models of TAC in non-transplant patients, aiming to clarify factors affecting PKs of TAC and identify the knowledge gap that may require further research. METHODS The PubMed, Embase databases, and Cochrane Library, as well as related references, were searched from the time of inception of the databases to February 2023, to identify TAC population pharmacokinetic studies modeled in non-transplant patients using a non-linear mixed-effects modeling approach. RESULTS Sixteen studies, all from Asian countries (China and Korea), were included in this study. Of these studies, eleven and four were carried out in pediatric and adult patients, respectively. One-compartment models were the commonly used structural models for TAC. The apparent clearance (CL/F) of TAC ranged from 2.05 to 30.9 L·h-1 (median of 14.9 L·h-1). Coadministered medication, genetic factors, and weight were the most common covariates affecting TAC-CL/F, and variability in the apparent volume of distribution (V/F) was largely explained by weight. Coadministration with Wuzhi capsules reduced CL/F by about 19 to 43%. For patients with CYP3A5*1*1 and *1*3 genotypes, the CL/F was 39-149% higher CL/F than patients with CYP3A5*1*1. CONCLUSION The optimal TAC dosage should be adjusted based on the patient's co-administration, body weight, and genetic information (especially CYP3A5 genotype). Further studies are needed to assess the generalizability of the published models to other ethnic groups. Moreover, external validation should be frequently performed to improve the clinical practicality of the models.
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Affiliation(s)
- Cheng-Bin Wang
- Department of Pharmacy, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, 110004, Liaoning Province, People's Republic of China
| | - Yu-Jia Zhang
- Department of Pharmacy, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, 110004, Liaoning Province, People's Republic of China
| | - Ming-Ming Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, 110004, Liaoning Province, People's Republic of China
| | - Li-Mei Zhao
- Department of Pharmacy, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, 110004, Liaoning Province, People's Republic of China.
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Yang Y, Wang C, Chen Y, Wang X, Jiao Z, Wang Z. External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients. Eur J Pharm Sci 2023; 186:106416. [PMID: 37119861 DOI: 10.1016/j.ejps.2023.106416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 01/26/2023] [Accepted: 02/28/2023] [Indexed: 05/01/2023]
Abstract
Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors. We searched the literature and determined the predictive performance of the selected models using methotrexate concentrations in 721 samples from 60 patients in the First Affiliated Hospital of the Navy Medical University. Prediction-based diagnostics and simulation-based normalized prediction distribution errors (NPDE) were used to evaluate the predictive performance of the models. The influence of prior information was also assessed using Bayesian forecasting, and the potential factors affecting model predictability were investigated. Thirty models extracted from published PPK studies were assessed. Prediction-based diagnostics showed that the number of compartments potentially influenced model transferability, and simulation-based NPDE indicated model misspecification. Bayesian forecasting significantly improved the predictive performance of the models. Various factors, including bioassays, covariates, and population diagnosis, influence model extrapolation. The published models were unsatisfactory for all prediction-based diagnostics, except for the 24 h methotrexate concentration monitoring and simulation-based diagnostics, making them inappropriate for direct extrapolation. Moreover, Bayesian forecasting combined therapeutic drug monitoring could improve the predictive performance of the models.
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Affiliation(s)
- Yunyun Yang
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China; Department of Pharmacy, Shanghai Changhai Hospital, First Affiliated Hospital of Navy Medical University, Shanghai 200433, China
| | - Chenyu Wang
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yueting Chen
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Xuebin Wang
- Department of Pharmacy, Shanghai Changhai Hospital, First Affiliated Hospital of Navy Medical University, Shanghai 200433, China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai 200030, China.
| | - Zhuo Wang
- Department of Pharmacy, Shanghai Changhai Hospital, First Affiliated Hospital of Navy Medical University, Shanghai 200433, China.
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Agema BC, Buijs SM, Sassen SDT, Mürdter TE, Schwab M, Koch BCP, Jager A, van Schaik RHN, Mathijssen RHJ, Koolen SLW. Toward model-informed precision dosing for tamoxifen: A population-pharmacokinetic model with a continuous CYP2D6 activity scale. Biomed Pharmacother 2023; 160:114369. [PMID: 36753957 DOI: 10.1016/j.biopha.2023.114369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 02/01/2023] [Accepted: 02/03/2023] [Indexed: 02/09/2023] Open
Abstract
BACKGROUND Tamoxifen is important in the adjuvant treatment of breast cancer. A plasma concentration of the active metabolite endoxifen of > 16 nM is associated with a lower risk of breast cancer-recurrence. Since inter-individual variability is high and > 20 % of patients do not reach endoxifen levels > 16 nM with the standard dose tamoxifen, therapeutic drug monitoring is advised. However, ideally, the correct tamoxifen dose should be known prior to start of therapy. Our aim is to develop a population pharmacokinetic (POP-PK) model incorporating a continuous CYP2D6 activity scale to support model informed precision dosing (MIPD) of tamoxifen to determine the optimal tamoxifen starting dose. METHODS Data from eight different clinical studies were pooled (539 patients, 3661 samples) and used to develop a POP-PK model. In this model, CYP2D6 activity per allele was estimated on a continuous scale. After inclusion of covariates, the model was subsequently validated using an independent external dataset (378 patients). Thereafter, dosing cut-off values for MIPD were determined. RESULTS A joint tamoxifen/endoxifen POP-PK model was developed describing the endoxifen formation rate. Using a continuous CYP2D6 activity scale, variability in predicting endoxifen levels was decreased by 37 % compared to using standard CYP2D6 genotype predicted phenotyping. After external validation and determination of dosing cut-off points, MIPD could reduce the proportion of patients with subtherapeutic endoxifen levels at from 22.1 % toward 4.8 %. CONCLUSION Implementing MIPD from the start of tamoxifen treatment with this POP-PK model can reduce the proportion of patients with subtherapeutic endoxifen levels at steady-state to less than 5 %.
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Affiliation(s)
- Bram C Agema
- Dept. of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center; Rotterdam, the Netherlands; Dept. of Clinical Pharmacy, Erasmus University Medical Center; Rotterdam, the Netherlands.
| | - Sanne M Buijs
- Dept. of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center; Rotterdam, the Netherlands
| | - Sebastiaan D T Sassen
- Dept. of Clinical Pharmacy, Erasmus University Medical Center; Rotterdam, the Netherlands; Rotterdam Clinical Pharmacometrics Group; Rotterdam, the Netherlands
| | - Thomas E Mürdter
- Margarete Fischer-Bosch-Institute of Clinical Pharmacology; Stuttgart, Germany; University of Tübingen; Tübingen, Germany
| | - Mathias Schwab
- Margarete Fischer-Bosch-Institute of Clinical Pharmacology; Stuttgart, Germany; Dept. of Clinical Pharmacology, University Hospital Tübingen; Tübingen, Germany; iFIT Cluster of Excellence (EXC2180) "Image Guided and Functionally Instructed Tumor Therapies", University of Tübingen, Tübingen, Germany
| | - Birgit C P Koch
- Dept. of Clinical Pharmacy, Erasmus University Medical Center; Rotterdam, the Netherlands; Rotterdam Clinical Pharmacometrics Group; Rotterdam, the Netherlands
| | - Agnes Jager
- Dept. of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center; Rotterdam, the Netherlands
| | - Ron H N van Schaik
- Dept. of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ron H J Mathijssen
- Dept. of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center; Rotterdam, the Netherlands
| | - Stijn L W Koolen
- Dept. of Medical Oncology, Erasmus MC Cancer Institute, Erasmus University Medical Center; Rotterdam, the Netherlands; Dept. of Clinical Pharmacy, Erasmus University Medical Center; Rotterdam, the Netherlands
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El Hassani M, Marsot A. External Evaluation of Population Pharmacokinetic Models for Precision Dosing: Current State and Knowledge Gaps. Clin Pharmacokinet 2023; 62:533-540. [PMID: 37004650 DOI: 10.1007/s40262-023-01233-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/27/2023] [Indexed: 04/04/2023]
Abstract
Predicting drug exposures using population pharmacokinetic models through Bayesian forecasting software can improve individual pharmacokinetic/pharmacodynamic target attainment. However, selecting the most adapted model to be used is challenging due to the lack of guidance on how to design and interpret external evaluation studies. The confusion around the choice of statistical metrics and acceptability criteria emphasises the need for further research to fill this methodological gap as there is an urgent need for the development of standards and guidelines for external evaluation studies. Herein we discuss the scientific challenges faced by pharmacometric researchers and opportunities for future research with a focus on antibiotics.
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Affiliation(s)
- Mehdi El Hassani
- Faculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada.
- Laboratoire de suivi thérapeutique pharmacologique et pharmacocinétique, Faculté de pharmacie, Université de Montréal, Montréal, Canada.
| | - Amélie Marsot
- Faculté de pharmacie, Université de Montréal, 2940 chemin de Polytechnique, Montréal, QC, H3T 1J4, Canada
- Laboratoire de suivi thérapeutique pharmacologique et pharmacocinétique, Faculté de pharmacie, Université de Montréal, Montréal, Canada
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Zuo M, Shang Y, Guo Y, Sun Y, Xu G, Chen J, Zhu L. Population Pharmacokinetics of Tacrolimus in Pediatric Patients With Umbilical Cord Blood Transplant. J Clin Pharmacol 2023; 63:298-306. [PMID: 36196568 DOI: 10.1002/jcph.2162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 09/27/2022] [Indexed: 11/11/2022]
Abstract
Tacrolimus was frequently used in pediatric patients with umbilical cord blood transplant for the prevention of graft-versus-host disease. The aim of the present study was to evaluate the population pharmacokinetics of tacrolimus among pediatric patients with umbilical cord blood transplant and find potential influenced factors. A total of 275 concentrations from 13 pediatric patients were used to build a polulation pharmacokinetic model using a nonlinear mixed-effects modeling approach. The impact of demographic features, biological characteristics, and concomitant medications, including sex, age, body weight, postoperative day, white blood cell count, red blood cell count, hemoglobin, platelets, hematocrit, blood urea nitrogen, creatinine, aspartate transaminase, alanine transaminase, total bilirubin, albumin, and total protein were investigated. The pharmacokinetics of tacrolimus were best described by a 1-compartment model with first- and zero-order mixed absorption and first-order elimination. The clearance and volume of distribution of tacrolimus were 1.93 L/h and 75.1 L, respectively. A covariate analysis identified that postoperative day and co-administration with trimethoprim-sulfamethoxazole were significant covariates influencing clearance of tacrolimus. Frequent blood monitoring and dose adjustment might be needed with the prolongation of postoperative day and coadministration with trimethoprim-sulfamethoxazole.
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Affiliation(s)
- Meiling Zuo
- Pharmaceutical College, Tianjin Medical University, Tianjin, China
| | - Yue Shang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Ye Guo
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China
| | - Yuxuan Sun
- Pharmaceutical College, Tianjin Medical University, Tianjin, China
| | - Gaoqi Xu
- The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Jingtao Chen
- School of Statistics and Data Science, Nankai University, Tianjin, China
| | - Liqin Zhu
- Pharmaceutical College, Tianjin Medical University, Tianjin, China.,Department of Pharmacy, Tianjin First Central Hospital, Tianjin, China
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Wang C, Chen J, Yang B, Li S, Zhang Y, Chen L, Wang T, Dong Y. Determination of vancomycin exposure target and individualized dosing recommendations for critically ill patients undergoing continuous renal replacement therapy. Pharmacotherapy 2023; 43:180-188. [PMID: 36714991 DOI: 10.1002/phar.2771] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 12/18/2022] [Accepted: 12/25/2022] [Indexed: 01/31/2023]
Abstract
STUDY OBJECTIVE Few studies have been conducted to quantify the exposure target of vancomycin in intensive care unit (ICU) patients undergoing continuous renal replacement therapy (CRRT) and provide optimized dosage regimens. We aimed to determine vancomycin exposure target and dosing recommendations using data from an open database in critically ill patients undergoing CRRT. DESIGN A retrospective observational cohort study. DATA SOURCE A large public database. PATIENTS The adult patients who received intravenous vancomycin and CRRT treatment in the database between 2017 and 2019 were reviewed to determine eligibility. A total of 180 patients with 1186 observations were included in the population pharmacokinetic (PPK) model development. The clinical efficacy of vancomycin was analyzed in 159 eligible patients. METHODS A PPK model was developed to estimate individual pharmacokinetic (PK) parameters. The area under the concentration-time curve (AUC) was estimated by a Bayesian approach based on individual vancomycin concentrations. Multivariate logistic regression analyses were performed to identify the factors of clinical outcomes. Threshold of vancomycin exposure in predicting efficacy was identified via receiver operating characteristic (ROC) curve. Dosing recommendations were designed using Monte Carlo Simulations (MCS) based on the optimized exposure target. MEASUREMENTS AND MAIN RESULTS On covariate analysis, CRRT intensity significantly affected vancomycin PK. The AUC above 427 mg*h/L was the only significant predictor of clinical efficacy (adjusted odds ratio (aOR): 1.008, 95% confidence interval (CI): 1.004-1.011, p = 0.000). MCS indicated that vancomycin dosage regimens of 5 mg/kg q12h or 7.5 mg/kg q12h were recommended for patients with CRRT intensities of 20-25 mL/kg/h or 25.1-45 mL/kg/h, respectively. CONCLUSIONS An AUC threshold of 427 mg*h/L (assuming the minimal inhibitory concentration (MIC) = 1 mg/L) was a recommended efficacy exposure target of vancomycin for critically ill patients undergoing CRRT. Vancomycin 5-7.5 mg/kg q12h is recommended as the initial dosage regimens for ICU patients undergoing CRRT.
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Affiliation(s)
- Chuhui Wang
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Jiaojiao Chen
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Bo Yang
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Sihan Li
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yiran Zhang
- School of Pharmacy, Xi'an Jiaotong University, Xi'an, China
| | - Lei Chen
- Department of Hemodialysis, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Taotao Wang
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Yalin Dong
- Department of Pharmacy, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
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Song X, Liu F, Gao H, Yan M, Zhang F, Zhao J, Qin Y, Li Y, Zhang Y. Compare the performance of multiple machine learning models in predicting tacrolimus concentration for infant patients with living donor liver transplantation. Pediatr Transplant 2023; 27:e14379. [PMID: 36039686 DOI: 10.1111/petr.14379] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 07/20/2022] [Accepted: 08/02/2022] [Indexed: 01/24/2023]
Abstract
BACKGROUND This study aims to establish multiple ML models and compare their performance in predicting tacrolimus concentration for infant patients who received LDLT within 3 months after transplantation. METHODS Retrospectively collected basic information and relevant biochemical indicators of included infant patients. CMIA was used to determine tacrolimus C0 . PCR was used to determine the donors' and recipients' CYP3A5 genotypes. Multivariate stepwise regression analysis and stepwise elimination covariates were used for covariates selection. Thirteen machine learning algorithms were applied for the development of prediction models. APE, the ratio of the APE ≤3 ng ml-1 and ideal rate (the proportion of the predicted value with a relative error of 30% or less) were used to evaluate the predictive performance of the model. RESULTS A total of 163 infant patients were included in this study. In the case of the optimal combination of covariates, the Ridge model had the lowest APE, 2.01 (0.85, 3.35 ng ml-1 ). The highest ratio of the APE ≤3 ng ml-1 was the LAR model (71.77%). And the Ridge model showed the highest ideal rate (55.05%). For the Ridge model, GRWR was the most important predictor. CONCLUSIONS Compared with other ML models, the Ridge model had good predictive performance and potential clinical application.
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Affiliation(s)
- XueWu Song
- First Central Clinical College of Tianjin Medical University, Tianjin, China
| | - FangHao Liu
- College of Computer Science, Tianjin Key Laboratory of Network and Data Security Technology, Nankai University, Tianjin, China
| | - HuiEr Gao
- Department of Pharmacy, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - MeiLing Yan
- Department of Pharmacy, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - FeiYu Zhang
- First Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Jia Zhao
- First Central Clinical College of Tianjin Medical University, Tianjin, China
| | - YinPeng Qin
- Department of Pharmacy, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yue Li
- College of Computer Science, KLMDASR, Key Laboratory for Medical Data Analysis and Statistical Research, Nankai University, Tianjin, China
| | - Yi Zhang
- Department of Pharmacy, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
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25
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Cai XJ, Li RD, Li JH, Tao YF, Zhang QB, Shen CH, Zhang XF, Wang ZX, Jiao Z. Prospective population pharmacokinetic study of tacrolimus in adult recipients early after liver transplantation: A comparison of Michaelis-Menten and theory-based pharmacokinetic models. Front Pharmacol 2022; 13:1031969. [DOI: 10.3389/fphar.2022.1031969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 10/17/2022] [Indexed: 11/11/2022] Open
Abstract
Background and Objective: Tacrolimus, a calcineurin inhibitor widely used as a potent immunosuppressant to prevent graft rejection, exhibits nonlinear kinetics in patients with kidney transplantation and nephrotic syndrome. However, whether nonlinear drug metabolism occurs in adult patients undergoing liver transplantation remains unclear, as do the main underlying mechanisms. Therefore, here we aimed to further confirm the characteristics of nonlinearity through a large sample size, and determine the potential influence of nonlinearity and its possible mechanisms.Methods: In total, 906 trough concentrations from 176 adult patients (150 men/26 women; average age: 50.68 ± 9.71 years, average weight: 64.54 ± 11.85 kg after first liver transplantation) were included in this study. Population pharmacokinetic analysis was performed using NONMEM®. Two modeling strategies, theory-based linear compartmental and nonlinear Michaelis–Menten (MM) models, were evaluated and compared. Potential covariates were screened using a stepwise approach. Bootstrap, prediction-, and simulation-based diagnostics (prediction-corrected visual predictive checks) were performed to determine model stability and predictive performance. Finally, Monte Carlo simulations based on the superior model were conducted to design dosing regimens.Results: Postoperative days (POD), Aspartate aminotransferase (AST), daily tacrolimus dose, triazole antifungal agent (TAF) co-therapy, and recipient CYP3A5*3 genotype constituted the main factors in the theory-based compartmental final model, whereas POD, Total serum bilirubin (TBIL), Haematocrit (HCT), TAF co-therapy, and recipient CYP3A5*3 genotype were important in the nonlinear MM model. The theory-based final model exhibited 234 L h−1 apparent plasma clearance and 11,000 L plasma distribution volume. The maximum dose rate (Vmax) of the nonlinear MM model was 6.62 mg day−1; the average concentration at steady state at half-Vmax (Km) was 6.46 ng ml−1. The nonlinear MM final model was superior to the theory-based final model and used to propose dosing regimens based on simulations.Conclusion: Our findings demonstrate that saturated tacrolimus concentration-dependent binding to erythrocytes and the influence of daily tacrolimus dose on metabolism may partly contribute to nonlinearity. Further investigation is needed is need to explore the causes of nonlinear pharmacokinetic of tacrolimus. The nonlinear MM model can provide reliable support for tacrolimus dosing optimization and adjustment in adult patients undergoing liver transplantation.
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Evaluation and Validation of the Limited Sampling Strategy of Polymyxin B in Patients with Multidrug-Resistant Gram-Negative Infection. Pharmaceutics 2022; 14:pharmaceutics14112323. [PMID: 36365141 PMCID: PMC9698835 DOI: 10.3390/pharmaceutics14112323] [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: 08/31/2022] [Revised: 10/18/2022] [Accepted: 10/24/2022] [Indexed: 11/30/2022] Open
Abstract
Polymyxin B (PMB) is the final option for treating multidrug-resistant Gram-negative bacterial infections. The acceptable pharmacokinetic/pharmacodynamic target is an area under the concentration–time curve across 24 h at a steady state (AUCss,24h) of 50–100 mg·h/L. The limited sampling strategy (LSS) is useful for predicting AUC values. However, establishing an LSS is a time-consuming process requiring a relatively dense sampling of patients. Further, given the variability among different centers, the predictability of LSSs is frequently questioned when it is extrapolated to other clinical centers. Currently, limited data are available on a reliable PMB LSS for estimating AUCss,24h. This study assessed and validated the practicability of LSSs established in the literature based on data from our center to provide reliable and ready-made PMB LSSs for laboratories performing therapeutic drug monitoring (TDM) of PMB. The influence of infusion and sampling time errors on predictability was also explored to obtain the optimal time points for routine PMB TDM. Using multiple regression analysis, PMB LSSs were generated from a model group of 20 patients. A validation group (10 patients) was used to validate the established LSSs. PMB LSSs from two published studies were validated using a dataset of 30 patients from our center. A population pharmacokinetic model was established to simulate the individual plasma concentration profiles for each infusion and sampling time error regimen. Pharmacokinetic data obtained from the 30 patients were fitted to a two-compartment model. Infusion and sampling time errors observed in real-world clinical practice could considerably affect the predictability of PMB LSSs. Moreover, we identified specific LSSs to be superior in predicting PMB AUCss,24h based on different infusion times. We also discovered that sampling time error should be controlled within −10 to 15 min to obtain better predictability. The present study provides validated PMB LSSs that can more accurately predict PMB AUCss,24h in routine clinical practice, facilitating PMB TDM in other laboratories and pharmacokinetics/pharmacodynamics-based clinical studies in the future.
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Implementation and Cross-Validation of a Pharmacokinetic Model for Precision Dosing of Busulfan in Hematopoietic Stem Cell Transplanted Children. Pharmaceutics 2022; 14:pharmaceutics14102107. [PMID: 36297541 PMCID: PMC9611936 DOI: 10.3390/pharmaceutics14102107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 09/20/2022] [Accepted: 09/22/2022] [Indexed: 11/16/2022] Open
Abstract
Busulfan, a drug used in conditioning prior to hematopoietic stem cell transplantation (HSCT) in children, has a narrow therapeutic margin. The model-informed precision dosing (MIPD) of busulfan is desirable, but there is a lack of validated tools. The objective of this study was to implement and cross-validate a population pharmacokinetic (PK) model in the Tucuxi software for busulfan MIPD in HSCT children. A search of the literature was performed to identify candidate population PK models. The goodness of fit of three selected models was assessed in a dataset of 178 children by computing the mean error (ME) and root-mean-squared error of prediction (RMSE). The best model was implemented in Tucuxi. The individual predicted concentrations, the area under the concentration-time curve (AUC), and dosage requirements were compared between the Tucuxi model and a reference model available in the BestDose software in a subset of 61 children. The model from Paci et al. best fitted the data in the full dataset. In a subset of 61 patients, the predictive performance of Tucuxi and BestDose models was comparable with ME values of 6.4% and -2.5% and RMSE values of 11.4% and 13.6%, respectively. The agreement between the estimated AUC and the predicted dose was good, with 6.6% and 4.9% of the values being out of the 95% limits of agreement, respectively. To conclude, a PK model for busulfan MIPD was cross-validated and is now available in the Tucuxi software.
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Huang S, Ding Q, Yang N, Sun Z, Cheng Q, Liu W, Li Y, Chen X, Wu C, Pei Q. External evaluation of published population pharmacokinetic models of posaconazole. Front Pharmacol 2022; 13:1005348. [PMID: 36249756 PMCID: PMC9561726 DOI: 10.3389/fphar.2022.1005348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 09/13/2022] [Indexed: 11/13/2022] Open
Abstract
Population pharmacokinetic (PopPK) models of posaconazole have been established to promote the precision dosing. However, the performance of these models extrapolated to other centers has not been evaluated. This study aimed to conduct an external evaluation of published posaconazole PopPK models to evaluate their predictive performance. Posaconazole PopPK models screened from the PubMed and MEDLINE databases were evaluated using an external dataset of 213 trough concentration samples collected from 97 patients. Their predictive performance was evaluated by prediction-based diagnosis (prediction error), simulation-based diagnosis (visual predictive check), and Bayesian forecasting. In addition, external cohorts with and without proton pump inhibitor were used to evaluate the models respectively. Ten models suitable for the external dataset were finally included into the study. In prediction-based diagnostics, none of the models met pre-determined criteria for predictive indexes. Only M4, M6, and M10 demonstrated favorable simulations in visual predictive check. The prediction performance of M5, M7, M8, and M9 evaluated using the cohort without proton pump inhibitor showed a significant improvement compared to that evaluated using the whole cohort. Consistent with our expectations, Bayesian forecasting significantly improved the predictive per-formance of the models with two or three prior observations. In general, the applicability of these published posaconazole PopPK models extrapolated to our center was unsatisfactory. Prospective studies combined with therapeutic drug monitoring are needed to establish a PopPK model for posaconazole in the Chinese population to promote individualized dosing.
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Affiliation(s)
- Shuqi Huang
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Qin Ding
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Nan Yang
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Zexu Sun
- Xiangya School of Pharmaceutical Sciences, Central South University, Changsha, China
| | - Qian Cheng
- Department of Hematology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Wei Liu
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Yejun Li
- Center of Clinical Pharmacology, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Xin Chen
- Department of Pharmacy, Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Cuifang Wu
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Cuifang Wu, ; Qi Pei,
| | - Qi Pei
- Department of Pharmacy, The Third Xiangya Hospital, Central South University, Changsha, China
- *Correspondence: Cuifang Wu, ; Qi Pei,
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Huang H, Liu Q, Zhang X, Xie H, Liu M, Chaphekar N, Wu X. External Evaluation of Population Pharmacokinetic Models of Busulfan in Chinese Adult Hematopoietic Stem Cell Transplantation Recipients. Front Pharmacol 2022; 13:835037. [PMID: 35873594 PMCID: PMC9300831 DOI: 10.3389/fphar.2022.835037] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 05/17/2022] [Indexed: 11/30/2022] Open
Abstract
Objective: Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing. Methods: The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed. Results: A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F20 of 57.27% and F30 of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration. Conclusion: This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.
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Affiliation(s)
- Huiping Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - Qingxia Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
- School of Pharmacy, Fujian Medical University, Fuzhou, China
| | - Xiaohan Zhang
- College of Arts and Sciences, University of Virginia, Charlottesville, VA, United States
| | - Helin Xie
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
| | - Maobai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
- *Correspondence: Xuemei Wu, ; Maobai Liu,
| | - Nupur Chaphekar
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, United States
| | - Xuemei Wu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, China
- *Correspondence: Xuemei Wu, ; Maobai Liu,
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30
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Huang W, Zheng Y, Huang H, Cheng Y, Liu M, Chaphekar N, Wu X. External evaluation of population pharmacokinetic models for voriconazole in Chinese adult patients with hematological malignancy. Eur J Clin Pharmacol 2022; 78:1447-1457. [PMID: 35764817 DOI: 10.1007/s00228-022-03359-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 06/19/2022] [Indexed: 12/01/2022]
Abstract
OBJECTIVES Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities. METHODS The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations. RESULTS A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given. CONCLUSIONS The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice.
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Affiliation(s)
- Weikun Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - You Zheng
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Huiping Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Yu Cheng
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China
| | - Maobai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China
| | - Nupur Chaphekar
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Xuemei Wu
- Department of Pharmacy, Fujian Medical University Union Hospital, Gulou District, 29 Xinquan Rd., Fuzhou, 350001, Fujian, China. .,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China.
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Barraclough KA, Metz D, Staatz CE, Gorham G, Carroll R, Majoni SW, Cherian S, Swaminathan R, Holford N. Important lack of difference in tacrolimus and mycophenolic acid pharmacokinetics between Aboriginal and Caucasian kidney transplant recipients. Nephrology (Carlton) 2022; 27:771-779. [PMID: 35727904 DOI: 10.1111/nep.14080] [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: 02/09/2022] [Revised: 06/01/2022] [Accepted: 06/15/2022] [Indexed: 11/26/2022]
Abstract
AIM To examine whether differences in tacrolimus and mycophenolic acid (MPA) pharmacokinetics contribute to the poorer kidney transplant outcomes experienced by Aboriginal Australians. METHODS Concentration-time profiles for tacrolimus and MPA were prospectively collected from 43 kidney transplant recipients: 27 Aboriginal and 16 Caucasian. Apparent clearance (CL/F) and distribution volume (V/F) for each individual were derived from concentration-time profiles combined with population pharmacokinetic priors, with subsequent assessment for between-group difference in pharmacokinetics. In addition, population pharmacokinetic models were developed using the prospective dataset supplemented by previously developed structural models for tacrolimus and MPA. The change in NONMEM objective function was used to assess improvement in goodness of model fit. RESULTS No differences were found between Aboriginal and Caucasian groups or empirical Bayes estimates, for CL/F or V/F of MPA or tacrolimus. However, a higher prevalence of CYP3A5 expressers (26% compared with 0%) and wider between-subject variability in tacrolimus CL/F (SD = 5.00 compared with 3.25 L/h/70 kg) were observed in the Aboriginal group, though these differences failed to reach statistical significance (p = .07 and p = .08). CONCLUSION There were no differences in typical tacrolimus or MPA pharmacokinetics between Aboriginal and Caucasian kidney transplant recipients. This means that Bayesian dosing tools developed to optimise tacrolimus and MPA dosing in Caucasian recipients may be applied to Aboriginal recipients. In turn, this may improve drug exposure and thereby transplant outcomes in this group. Aboriginal recipients appeared to have greater between-subject variability in tacrolimus CL/F and a higher prevalence of CYP3A5 expressers, attributes that have been linked with inferior outcomes.
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Affiliation(s)
- Katherine A Barraclough
- Department of Nephrology, Royal Melbourne Hospital, Melbourne, Victoria, Australia.,School of Medicine, University of Melbourne, Melbourne, Victoria, Australia
| | - David Metz
- Department of Paediatrics, Monash University, Melbourne, Victoria, Australia.,Department of Nephrology, Royal Children's Hospital, Melbourne, Victoria, Australia.,Murdoch Children's Research Institute, Melbourne, Victoria, Australia
| | - Christine E Staatz
- School of Pharmacy, University of Queensland, Brisbane, Queensland, Australia
| | - Gillian Gorham
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia
| | - Robert Carroll
- Department of Nephrology, Central Northern Adelaide Renal Transplantation Services, Adelaide, South Australia, Australia.,Clinical and Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Sandawana William Majoni
- Menzies School of Health Research, Charles Darwin University, Darwin, Northern Territory, Australia.,Department of Nephrology, Northern Territory Renal Services, Darwin, Northern Territory, Australia.,School of Medicine, Flinders University Northern Territory Medical Program, Darwin, Northern Territory, Australia
| | - Sajiv Cherian
- Renal Services, Alice Springs Hospital, Alice Springs, Northern Territory, Australia
| | | | - Nick Holford
- Pharmacology and Clinical Pharmacology, University of Auckland, Auckland, New Zealand
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Population Pharmacokinetic Evaluation with External Validation of Tacrolimus in Chinese Primary Nephrotic Syndrome Patients. Pharm Res 2022; 39:1907-1920. [PMID: 35650450 DOI: 10.1007/s11095-022-03273-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 04/22/2022] [Indexed: 10/18/2022]
Abstract
PURPOSE The generalizability of numerous tacrolimus population pharmacokinetic (popPK) models constructed to promote optimal tacrolimus dosing in patients with primary nephrotic syndrome (PNS) is unclear. This study aimed to evaluate the predictive performance of published tacrolimus popPK models for PNS patients with an external data set. METHODS We prospectively collected 223 concentrations from 50 Chinese adult patients with PNS who were undergoing tacrolimus treatment. Data on published tacrolimus popPK models for adults and children with PNS were extracted from the literature. Model predictability was evaluated with prediction-based and simulation-based diagnostics and Bayesian forecasting. RESULTS In prediction-based evaluation, none of the 11 identified published popPK models of tacrolimus had met a predefined criteria of a mean prediction error ≤ ± 20%, and the prediction error within ± 30% of the identified models didn't exceed 50%. Simulation-based diagnostics also indicated unsatisfactory predictability. Bayesian forecasting demonstrated amelioration in the model predictability with the inclusion of 2-3 prior observations. Moreover, the predictive performance of nonlinear models was not better than that of one-compartment models. CONCLUSIONS The prediction of tacrolimus concentrations for patients with PNS remains challenging; published models are not applicable for extrapolation to other hospitals. Bayesian forecasting significantly improved model predictability and thereby helped to individualize tacrolimus dosing.
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Zang YN, Guo W, Dong F, Li AN, de Leon J, Ruan CJ. Published population pharmacokinetic models of valproic acid in adult patients: a systematic review and external validation in a Chinese sample of inpatients with bipolar disorder. Expert Rev Clin Pharmacol 2022; 15:621-635. [PMID: 35536685 DOI: 10.1080/17512433.2022.2075849] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
BACKGROUND This study reviewed all published valproic acid (VPA) population pharmacokinetic (PPK) models in adult patients and assessed them using external validation methods to determine predictive performance. METHODS Thirteen published PPK models (labeled with letters A to M) not restricted to children were identified in PubMed, Embase, and Web of Science databases. They were evaluated in a sample totaling 411 serum concentrations from 146 adult inpatients diagnosed with bipolar disorder in a Chinese hospital. Serum concentrations of VPA were analyzed by validated ultra-performance liquid chromatography-tandem mass spectrometry. Performance was assessed by 4 tests (prediction-based diagnostics, visual predictive checks, normalized prediction distribution error, and Bayesian forecasting). RESULTS Models K and L, developed in large samples of Chinese and Thai patients, showed good performance in our Chinese dataset. Models H and J demonstrated good performance in Tests 2 and 3 of the 4 tests, respectively. Another 7 models exhibited intermediate performance. The models with the worst performance, F and M, could not be improved by Bayesian forecasting. CONCLUSION In our validation study the most important factors contributing to good performance were absence of children, Asian ethnicity, one-compartment models and inclusion of body weight and VPA dose in previously published models.
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Affiliation(s)
- Yan-Nan Zang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wei Guo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fang Dong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - An-Ning Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Jose de Leon
- Mental Health Research Center at Eastern State Hospital, 1350 Bull Lea Road, Lexington, KY 40511, USA.,Biomedical Research Centre in Mental Health Net (CIBERSAM), Santiago Apóstol Hospital, University of the Basque Country, Vitoria, Spain
| | - Can-Jun Ruan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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Du Y, Song W, Xiong XF, Ge WH, Huai-Jun Z. Population pharmacokinetics and dosage optimization of tacrolimus coadministration with Wuzhi capsule in adult liver transplant patients. Xenobiotica 2022; 52:274-283. [PMID: 35502774 DOI: 10.1080/00498254.2022.2073851] [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] [Indexed: 10/18/2022]
Abstract
1. This study aimed to establish a population pharmacokinetic model of tacrolimus coadministration with Wuzhi capsule and optimize the dosage regimen in adult liver transplant patients.2. Totally 1327 tacrolimus trough concentrations from 116 adult liver transplant patients were obtained for model development. A one-compartment model with first-order absorption and elimination was used to analyse the data, and the final model was internally verified using a goodness-of-fit diagnostic plot, bootstrap methods, and visual prediction test. A total of 29 patients with 250 tacrolimus trough concentrations was used for external validation via prediction-based diagnostics. Additionally, the simulation was used to optimize the recommended dose of tacrolimus and Wuzhi capsules.3. The estimated apparent clearance and volume of the distribution of tacrolimus were 15.4 L/h and 1210 L, respectively. The tacrolimus daily dose, Wuzhi capsule daily dose, postoperative time, alanine transaminase, haemoglobin, total bilirubin, direct bilirubin, estimated glomerular filtration rate, and urea, concomitant with voriconazole and fluconazole, were identified as significant covariates affecting the pharmacokinetic parameters. Internal and external validation showed that the final model was stable and reliable for predicting performance.4. The final model could provide guidance for dosage optimization of tacrolimus coadministered with Wuzhi capsules in adult liver transplantation patients.
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Affiliation(s)
- Yao Du
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.,Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Wei Song
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Xiao-Fu Xiong
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China
| | - Wei-Hong Ge
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.,Nanjing Medical Center for Clinical Pharmacy, Nanjing, China
| | - Zhu Huai-Jun
- Department of Pharmacy, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.,Nanjing Medical Center for Clinical Pharmacy, Nanjing, China.,Department of Pharmacology, School of Pharmacy, Fudan University, Shanghai, China
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35
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Zhang SF, Tang BH, An-Hua W, Du Y, Guan ZW, Li Y. Effect of drug combination on tacrolimus target dose in renal transplant patients with different CYP3A5 genotypes. Xenobiotica 2022; 52:312-321. [PMID: 35395919 DOI: 10.1080/00498254.2022.2064252] [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: 10/18/2022]
Abstract
Various factors, including genetic polymorphisms, drug-drug interactions, and patient characteristics influence the blood concentrations of tacrolimus in renal transplant patients. In the present study, we established a population pharmacokinetic model to explore the effect of combined use of Wuzhi capsules/echinocandins and the patients' biochemical parameters such as hematocrit on blood concentrations and target doses of tacrolimus in renal transplant patients with different CYP3A5 genotypes. The aim of the study was to propose an individualized tacrolimus administration regimen for early renal transplant recipients.In this retrospective cohort study, we included 240 renal transplant recipients within 21 days of surgery (174 males and 66 females, mean age 39.4 years), who received tacrolimus alone (n = 54), in combination with Wuzhi capsules (99) or caspofungin (57) or micafungin (30). We collected demographic characteristics, clinical indicators, CYP3A5 genotypes, and 1950 steady-state trough concentrations of tacrolimus and included them in population pharmacokinetic model. An additional 110 renal transplant recipients and 625 steady-state trough concentrations of tacrolimus were included for external validation of the model. The population pharmacokinetic model was established and Monte Carlo was used to simulate probabilities for achieving the target concentration for individual tacrolimus administration.A two-compartment model of first-order absorption and elimination was developed to describe the population pharmacokinetics of tacrolimus. CYP3A5 genotypes and co-administration of Wuzhi capsules, as well as time after renal transplantation and hematocrit, were important factors affecting the clearance of tacrolimus. We found no obvious change in trend in the scatter plot of tacrolimus clearance rate vs. hematocrit. The Monte Carlo simulation indicated the following recommended doses of tacrolimus alone: 0.14 mg·kg-1·d-1 for genotype CYP3A5*1*1, 0.12 mg·kg-1·d-1 for CYP3A5*1*3, and 0.10 mg·kg-1·d-1 for CYP3A5*3*3. For patients receiving the combination with Wuzhi capsules, the recommended doses of tacrolimus were 0.10 mg·kg-1·d-1 for CYP3A5*1*1, 0.08 mg·kg-1·d-1 for CYP3A5*1*3, and 0.06 mg·kg-1·d-1 for CYP3A5*3*3 genotypes. Caspofungin or micafungin had no effect on the clearance of tacrolimus in renal transplant recipients.The population pharmacokinetics of tacrolimus in renal transplant patients was evaluated and the individual administration regimen of tacrolimus was simulated. For early kidney transplant recipients receiving tacrolimus treatment, not only body weight, but also CYP3A5 genotypes and drugs used in combination should be considered when determining the target dose of tacrolimus.
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Affiliation(s)
- Shu-Fang Zhang
- School of Pharmacy, Shandong First Medical University, Tai'an, China.,Department of Pharmacy, Tai'an City Central Hospital, Tai'an, China
| | - Bo-Hao Tang
- School of Pharmaceutical Science, Shandong University, Ji'nan, China
| | - Wei An-Hua
- Department of Pharmacy, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Du
- School of Pharmacy, Shandong First Medical University, Tai'an, China
| | - Zi-Wan Guan
- School of Pharmaceutical Science, Shandong University, Ji'nan, China
| | - Yan Li
- Department of Clinical Pharmacy, The First Affiliated Hospital of Shandong First Medical University, Ji'nan, China
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Mao J, Li Q, Li P, Qin W, Chen B, Zhong M. Evaluation and Application of Population Pharmacokinetic Models for Identifying Delayed Methotrexate Elimination in Patients With Primary Central Nervous System Lymphoma. Front Pharmacol 2022; 13:817673. [PMID: 35355729 PMCID: PMC8959905 DOI: 10.3389/fphar.2022.817673] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/14/2022] [Indexed: 11/30/2022] Open
Abstract
Objective: Several population pharmacokinetic (popPK) models have been developed to determine the sources of methotrexate (MTX) PK variability. It remains unknown if these published models are precise enough for use or if a new model needs to be built. The aims of this study were to 1) assess the predictability of published models and 2) analyze the potential risk factors for delayed MTX elimination. Methods: A total of 1458 MTX plasma concentrations, including 377 courses (1–17 per patient), were collected from 77 patients who were receiving high-dose MTX for the treatment of primary central nervous system lymphoma in Huashan Hospital. PopPK analysis was performed using the NONMEM® software package. Previously published popPK models were selected and rebuilt. A new popPK model was then constructed to screen potential covariates using a stepwise approach. The covariates were included based on the combination of theoretical mechanisms and data properties. Goodness-of-fit plots, bootstrap, and prediction- and simulation-based diagnostics were used to determine the stability and predictive performance of both the published and newly built models. Monte Carlo simulations were conducted to qualify the influence of risk factors on the incidence of delayed elimination. Results: Among the eight evaluated published models, none presented acceptable values of bias or inaccuracy. A two-compartment model was employed in the newly built model to describe the PK of MTX. The estimated mean clearance (CL/F) was 4.91 L h−1 (relative standard error: 3.7%). Creatinine clearance, albumin, and age were identified as covariates of MTX CL/F. The median and median absolute prediction errors of the final model were -10.2 and 36.4%, respectively. Results of goodness-of-fit plots, bootstrap, and prediction-corrected visual predictive checks indicated the high predictability of the final model. Conclusions: Current published models are not sufficiently reliable for cross-center use. The elderly patients and those with renal dysfunction, hypoalbuminemia are at higher risk of delayed elimination.
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Affiliation(s)
- Junjun Mao
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Qing Li
- Department of Hematology, Huashan Hospital, Fudan University, Shanghai, China.,Department of Hematology, Huashan Hospital North, Fudan University, Shanghai, China
| | - Pei Li
- Department of Hematology, Huashan Hospital, Fudan University, Shanghai, China
| | - Weiwei Qin
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
| | - Bobin Chen
- Department of Hematology, Huashan Hospital, Fudan University, Shanghai, China.,Department of Hematology, Huashan Hospital North, Fudan University, Shanghai, China
| | - Mingkang Zhong
- Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China
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Huang L, Wang J, Yang J, Zhang H, Hu Y, Miao J, Mao J, Fang L. Impact of Sampling Time Variability on Tacrolimus Dosage Regimen in Pediatric Primary Nephrotic Syndrome: Single-Center, Prospective, Observational Study. Front Pharmacol 2022; 12:726667. [PMID: 35069185 PMCID: PMC8776711 DOI: 10.3389/fphar.2021.726667] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Accepted: 12/16/2021] [Indexed: 01/20/2023] Open
Abstract
Background: Tacrolimus (TAC) is an important immunosuppressant for children with primary nephrotic syndrome (PNS). The relationship between sampling time variability in TAC therapeutic drug monitoring and dosage regimen in such children is unknown. Methods: In this single-center, prospective, observational study, we evaluated the sampling time variability, concentration error (CE), relative CE (RCE), and the impact of the sampling time on TAC dosage regimens in 112 PNS children with 188 blood samples. Nominal concentration (Cnom) at 12-h after last TAC dose was simulated based on observed concentration (Cobs) via previously published pharmacokinetic models, then CE and RCE were calculated. Inappropriate dosing adjustments resulting from deviated sampling time were evaluated based on a target Cnom of 5-10 ng/ml. Results: We found that 32 and 68% of samples were respectively collected early (2-180 min) and delayed (4-315 min). Furthermore, 24, 22, 22, and 32% of blood samples were drawn within deviations of ≤0.5, 0.5-1, 1-2, and >2 h, respectively, and 0.3 ng/ml of CE and 6% RCE per hour of deviation occurred. Within a deviation of >2 h, 25% of Cobs might result in inappropriate dosing adjustments. Early and delayed sampling might result in inappropriate dose holding or unnecessary dose increments, respectively, in patients with Cobs ∼ 5 ng/ml. Conclusions: Variable sampling time might lead to inappropriate dosing adjustment in a minority of children with PNS, particularly those with TAC Cobs ∼ 5 ng/ml collected with a deviation of >2 h.
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Affiliation(s)
- Lingfei Huang
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Junyan Wang
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jufei Yang
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Huifen Zhang
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Yan Hu
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Miao
- Department of Pharmacy, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Jianhua Mao
- Department of Nephrology, The Children's Hospital, National Clinical Research Center for Child Health, Zhejiang University School of Medicine, Hangzhou, China
| | - Luo Fang
- Department of Pharmacy, Institute of Basic Medicine and Cancer (IBMC), Chinese Academy of Sciences, Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), Hangzhou, China
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Zang YN, Guo W, Niu MX, Bao S, Wang Q, Wang Y, Dong F, Li AN, Ruan CJ. Population pharmacokinetics of valproic acid in adult Chinese patients with bipolar disorder. Eur J Clin Pharmacol 2021; 78:405-418. [PMID: 34854947 DOI: 10.1007/s00228-021-03246-2] [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: 08/17/2021] [Accepted: 10/21/2021] [Indexed: 11/25/2022]
Abstract
PURPOSE To develop and validate a population pharmacokinetic (PPK) model of valproic acid (VPA) in adult Chinese patients with bipolar disorder, and provide guidance for individualized therapy in this population. METHODS A total of 1104 serum concentrations from 272 patients were collected in this study. The data analysis was performed using a nonlinear mixed-effects modeling approach. Covariates included demographic parameters, biological characteristics, and concomitant medications. Bootstrap validation (1000 runs), normalized prediction distribution error (NPDE), and external validation of 50 patients were employed to evaluate the final model. RESULTS A one-compartment model with first-order absorption and elimination was developed for VPA extended-release tablets. VPA clearance was significantly influenced by three variables: sex (12% higher in male patients), daily dose (increasing with the 0.13 exponent), and body weight (increasing with the 0.56 exponent). Typical values for the absorption rate constant (Ka), apparent clearance (CL/F), and apparent distribution volume (V/F) for a female patient weighing 70 kg administered VPA 1000 mg/day were 0.18 h-1, 0.46 L/h, and 12.84 L, respectively. The results of model evaluation indicated a good stable and precise performance of the final model. CONCLUSIONS A qualified PPK model of VPA was developed in Chinese patients with bipolar disorder. This model could be used as a suitable tool for the personalization of VPA dosing for bipolar patients.
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Affiliation(s)
- Yan-Nan Zang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Wei Guo
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Meng-Xi Niu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Shuang Bao
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Qian Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Yan Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Fang Dong
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - An-Ning Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
| | - Can-Jun Ruan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China. .,Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China.
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Hanafin PO, Nation RL, Scheetz MH, Zavascki AP, Sandri AM, Kwa AL, Cherng BPZ, Kubin CJ, Yin MT, Wang J, Li J, Kaye KS, Rao GG. Assessing the predictive performance of population pharmacokinetic models for intravenous polymyxin B in critically ill patients. CPT Pharmacometrics Syst Pharmacol 2021; 10:1525-1537. [PMID: 34811968 PMCID: PMC8674003 DOI: 10.1002/psp4.12720] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 07/29/2021] [Accepted: 08/05/2021] [Indexed: 12/23/2022] Open
Abstract
Polymyxin B (PMB) has reemerged as a last‐line therapy for infections caused by multidrug‐resistant gram‐negative pathogens, but dosing is challenging because of its narrow therapeutic window and pharmacokinetic (PK) variability. Population PK (POPPK) models based on suitably powered clinical studies with appropriate sampling strategies that take variability into consideration can inform PMB dosing to maximize efficacy and minimize toxicity and resistance. Here we reviewed published PMB POPPK models and evaluated them using an external validation data set (EVD) of patients who are critically ill and enrolled in an ongoing clinical study to assess their utility. Seven published POPPK models were employed using the reported model equations, parameter values, covariate relationships, interpatient variability, parameter covariance, and unexplained residual variability in NONMEM (Version 7.4.3). The predictive ability of the models was assessed using prediction‐based and simulation‐based diagnostics. Patient characteristics and treatment information were comparable across studies and with the EVD (n = 40), but the sampling strategy was a main source of PK variability across studies. All models visually and statistically underpredicted EVD plasma concentrations, but the two‐compartment models more accurately described the external data set. As current POPPK models were inadequately predictive of the EVD, creation of a new POPPK model based on an appropriately powered clinical study with an informed PK sampling strategy would be expected to improve characterization of PMB PK and identify covariates to explain interpatient variability. Such a model would support model‐informed precision dosing frameworks, which are urgently needed to improve PMB treatment efficacy, limit resistance, and reduce toxicity in patients who are critically ill.
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Affiliation(s)
- Patrick O Hanafin
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Roger L Nation
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Marc H Scheetz
- Department of Pharmacy Practice and Pharmacometric Center of Excellence, Midwestern University Chicago College of Pharmacy, Downers Grove, Illinois, USA
| | - Alexandre P Zavascki
- Department of Internal Medicine, Medical School, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.,Infectious Diseases Service, Hospital Moinhos de Vento, Porto Alegre, Brazil
| | - Ana M Sandri
- Infectious Diseases Service, Hospital São Lucas da Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
| | - Andrea L Kwa
- Department of Pharmacy, Singapore General Hospital, Singapore, Singapore.,Emerging Infectious Diseases, Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Benjamin P Z Cherng
- Department of Infectious Diseases, Singapore General Hospital, Singapore, Singapore
| | - Christine J Kubin
- New York-Presbyterian Hospital/Columbia University Irving Medical Center, New York, New York, USA
| | - Michael T Yin
- Division of Infectious Diseases, Department of Internal Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Jiping Wang
- Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Jian Li
- Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia
| | - Keith S Kaye
- Division of Infectious Diseases, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Gauri G Rao
- Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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Methaneethorn J, Lohitnavy M, Onlamai K, Leelakanok N. Predictive Performance of Published Tacrolimus Population Pharmacokinetic Models in Thai Kidney Transplant Patients. Eur J Drug Metab Pharmacokinet 2021; 47:105-116. [PMID: 34817826 DOI: 10.1007/s13318-021-00735-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND AND OBJECTIVE Tacrolimus is a narrow therapeutic index drug with high pharmacokinetic variability, and several tacrolimus population pharmacokinetic (PopPK) models were developed to guide individualized drug dosing. These models, however, may not perform well in other clinical settings. Therefore, we aimed to assess the predictive ability of published tacrolimus PopPK models using a dataset of Thai kidney transplant patients. METHODS The external dataset was retrospectively collected from medical records of Bhumibol Adulyadej Hospital, Thailand. Published tacrolimus PopPK models were systematically searched from PubMed, Science Direct, CINAHL Complete, and Scopus databases. Models conducted using a nonlinear mixed-effects approach with covariate resemblance to our external dataset were selected. The external dataset consisted of Thai kidney transplant patients receiving oral immediate- or extended-release tacrolimus formulations twice or once daily, respectively. Accuracy and precision of predicted concentrations were evaluated using mean absolute prediction error (MAPE), root mean square error (RMSE), and goodness of fit plots. RESULTS Only three models produced acceptable population predictions with the MAPE of < 50%. By using the Bayesian posthoc estimate of individual pharmacokinetic parameters, all models well performed with the MAPE and RMSE of < 30% and 40%, respectively, except two models; one could not successfully converge and the other substantially underpredicted tacrolimus concentrations. CONCLUSION We evaluated ten tacrolimus PopPK models, and eight models resulted in satisfactorily individual predicted tacrolimus concentrations in Thai kidney transplant patients and may be used to aid tacrolimus dose adjustment along with a clinical judgment.
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Affiliation(s)
- Janthima Methaneethorn
- Pharmacokinetic Research Unit, Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, 65000, Thailand.
- Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, Thailand.
| | - Manupat Lohitnavy
- Pharmacokinetic Research Unit, Department of Pharmacy Practice, Faculty of Pharmaceutical Sciences, Naresuan University, Phitsanulok, 65000, Thailand
- Center of Excellence for Environmental Health and Toxicology, Naresuan University, Phitsanulok, Thailand
| | - Kamonwan Onlamai
- Department of Pharmacy, Bhumibol Adulyadej Hospital, Bangkok, Thailand
| | - Nattawut Leelakanok
- Department of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Burapha University, Chonburi, Thailand
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Mao J, Qiu X, Qin W, Xu L, Zhang M, Zhong M. Factors Affecting Time-Varying Clearance of Cyclosporine in Adult Renal Transplant Recipients: A Population Pharmacokinetic Perspective. Pharm Res 2021; 38:1873-1887. [PMID: 34750720 DOI: 10.1007/s11095-021-03114-9] [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: 05/03/2021] [Accepted: 09/20/2021] [Indexed: 11/27/2022]
Abstract
AIM The pharmacokinetic (PK) properties of cyclosporine (CsA) in renal transplant recipients are patient- and time-dependent. Knowledge of this time-related variability is necessary to maintain or achieve CsA target exposure. Here, we aimed to identify factors explaining variabilities in CsA PK properties and characterize time-varying clearance (CL/F) by performing a comprehensive analysis of CsA PK factors using population PK (popPK) modeling of long-term follow-up data from our institution. METHODS In total, 3674 whole-blood CsA concentrations from 183 patients who underwent initial renal transplantation were analyzed using nonlinear mixed-effects modeling. The effects of potential covariates were selected according to a previous study and well-accepted theoretical mechanisms. Model-informed individualized therapeutic regimens were also evaluated. RESULTS A two-compartment model adequately described the data and the estimated mean CsA CL/F was 32.6 L h-1 (relative standard error: 5%). Allometrically scaled body size, hematocrit (HCT) level, CGC haplotype carrier status, and postoperative time may contribute to CsA PK variability. The CsA bioavailability in patients receiving a prednisolone dose (PD) of 80 mg was 20.6% lower than that in patients receiving 20 mg. A significant decrease (52.6%) in CL/F was observed as the HCT increased from 10.5% to 60.5%. The CL/F of the non-CGC haplotype carrier was 14.4% lower than that of the CGC haplotype carrier at 3 months post operation. CONCLUSIONS By monitoring body size, HCT, PD, and CGC haplotype, changes in CsA CL/F over time could be predicted. Such information could be used to optimize CsA therapy. CsA dose adjustments should be considered in different postoperative periods.
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Affiliation(s)
- Junjun Mao
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Xiaoyan Qiu
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China.
| | - Weiwei Qin
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China.
| | - Luyang Xu
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Ming Zhang
- Department of Nephrology, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
| | - Mingkang Zhong
- Department of Pharmacy, Huashan Hospital, Fudan University, 12 Middle Urumqi Road, Shanghai, 200040, China
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Corral Alaejos Á, Zarzuelo Castañeda A, Jiménez Cabrera S, Sánchez-Guijo F, Otero MJ, Pérez-Blanco JS. External evaluation of population pharmacokinetic models of imatinib in adults diagnosed with chronic myeloid leukaemia. Br J Clin Pharmacol 2021; 88:1913-1924. [PMID: 34705297 DOI: 10.1111/bcp.15122] [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: 07/08/2021] [Revised: 09/29/2021] [Accepted: 10/21/2021] [Indexed: 12/30/2022] Open
Abstract
AIMS Imatinib is considered the standard first-line treatment in newly diagnosed patients with chronic-phase myeloid leukaemia (CML). Several imatinib population pharmacokinetic (popPK) models have been developed. However, their predictive performance has not been well established when extrapolated to different populations. Therefore, this study aimed to perform an external evaluation of available imatinib popPK models developed mainly in adult patients, and to evaluate the improvement in individual model-based predictions through Bayesian forecasting computed by each model at different treatment occasions. METHODS A literature review was conducted through PubMed and Scopus to identify popPK models. Therapeutic drug monitoring data collected in adult CML patients treated with imatinib was used for external evaluation, including prediction- and simulated-based diagnostics together with Bayesian forecasting analysis. RESULTS Fourteen imatinib popPK studies were included for model-performance evaluation. A total of 99 imatinib samples were collected from 48 adult CML patients undergoing imatinib treatment with a minimum of one plasma concentration measured at steady-state between January 2016 and December 2020. The model proposed by Petain et al showed the best performance concerning prediction-based diagnostics in the studied population. Bayesian forecasting demonstrated a significant improvement in predictive performance at the second visit. Inter-occasion variability contributed to reducing bias and improving individual model-based predictions. CONCLUSIONS Imatinib popPK studies developed in Caucasian subjects including α1-acid glycoprotein showed the best model performance in terms of overall bias and precision. Moreover, two imatinib samples from different visits appear sufficient to reach an adequate model-based individual prediction performance trough Bayesian forecasting.
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Affiliation(s)
| | | | | | - Fermín Sánchez-Guijo
- Institute for Biomedical Research of Salamanca, Salamanca, Spain.,Haematology Department, University Hospital of Salamanca, Salamanca, Spain.,Department of Medicine, University of Salamanca, Salamanca, Spain
| | - María José Otero
- Pharmacy Service, University Hospital of Salamanca, Salamanca, Spain.,Institute for Biomedical Research of Salamanca, Salamanca, Spain
| | - Jonás Samuel Pérez-Blanco
- Department of Pharmaceutical Sciences, Pharmacy Faculty, University of Salamanca, Salamanca, Spain.,Institute for Biomedical Research of Salamanca, Salamanca, Spain
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Huang H, Liu M, Ren J, Hu J, Lin S, Li D, Huang W, Chen S, Yang T, Wu X. Can Published Population Pharmacokinetic Models of Busulfan Be Used for Individualized Dosing in Chinese Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation? An External Evaluation. J Clin Pharmacol 2021; 62:609-619. [PMID: 34695225 DOI: 10.1002/jcph.1992] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 10/20/2021] [Indexed: 02/02/2023]
Abstract
Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.
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Affiliation(s)
- Huiping Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Maobai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Jinhua Ren
- Department of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Jianda Hu
- Department of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Shenglu Lin
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Dandan Li
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Weikun Huang
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China.,School of Pharmacy, Fujian Medical University, Fuzhou, Fujian, China
| | - Shaozhen Chen
- Department of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Ting Yang
- Department of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
| | - Xuemei Wu
- Department of Pharmacy, Fujian Medical University Union Hospital, Fuzhou, Fujian, China
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Kirubakaran R, Hennig S, Maslen B, Day RO, Carland JE, Stocker SL. Evaluation of published population pharmacokinetic models to inform tacrolimus dosing in adult heart transplant recipients. Br J Clin Pharmacol 2021; 88:1751-1772. [PMID: 34558092 DOI: 10.1111/bcp.15091] [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: 04/13/2021] [Revised: 08/26/2021] [Accepted: 09/13/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND AND AIM Identification of the most appropriate population pharmacokinetic model-based Bayesian estimation is required prior to its implementation in routine clinical practice to inform tacrolimus dosing decisions. This study aimed to determine the predictive performances of relevant population pharmacokinetic models of tacrolimus developed from various solid organ transplant recipient populations in adult heart transplant recipients, stratified based on concomitant azole antifungal use. Concomitant azole antifungal therapy alters tacrolimus pharmacokinetics substantially, necessitating dose adjustments. METHODS Population pharmacokinetic models of tacrolimus were selected (n = 17) for evaluation from a recent systematic review. The models were transcribed and implemented in NONMEM version 7.4.3. Data from 85 heart transplant recipients (2387 tacrolimus concentrations) administered the oral immediate-release formulation of tacrolimus (Prograf) were obtained up to 391 days post-transplant. The performance of each model was evaluated using: (i) prediction-based assessment (bias and imprecision) of the individual predicted tacrolimus concentration of the fourth dosing occasion (MAXEVAL = 0, FOCE-I) from 1-3 prior dosing occasions; and (ii) simulation-based assessment (prediction-corrected visual predictive check). Both assessments were stratified based on concomitant azole antifungal use. RESULTS Regardless of the number of prior dosing occasions (1-3) and concomitant azole antifungal use, all models demonstrated unacceptable individual predicted tacrolimus concentration of the fourth dosing occasion (n = 152). The prediction-corrected visual predictive check graphics indicated that these models inadequately predicted observed tacrolimus concentrations. CONCLUSION All models evaluated were unable to adequately describe tacrolimus pharmacokinetics in adult heart transplant recipients included in this study. Further work is required to describe tacrolimus pharmacokinetics for our heart transplant recipient cohort.
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Affiliation(s)
- Ranita Kirubakaran
- St. Vincent's Clinical School, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.,Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia.,Ministry of Health, Putrajaya, Malaysia
| | - Stefanie Hennig
- Certara Inc., Princeton, NJ, USA.,School of Clinical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Ben Maslen
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW, Australia
| | - Richard O Day
- St. Vincent's Clinical School, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.,Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia.,Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Jane E Carland
- St. Vincent's Clinical School, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.,Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia.,School of Medical Sciences, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia
| | - Sophie L Stocker
- St. Vincent's Clinical School, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW, Australia.,Department of Clinical Pharmacology and Toxicology, St. Vincent's Hospital, Sydney, NSW, Australia.,Garvan Institute of Medical Research, Sydney, NSW, Australia.,School of Pharmacy, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia
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45
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Population Pharmacokinetic Models of Tacrolimus in Adult Transplant Recipients: A Systematic Review. Clin Pharmacokinet 2021; 59:1357-1392. [PMID: 32783100 DOI: 10.1007/s40262-020-00922-x] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND AND OBJECTIVES Numerous population pharmacokinetic (PK) models of tacrolimus in adult transplant recipients have been published to characterize tacrolimus PK and facilitate dose individualization. This study aimed to (1) investigate clinical determinants influencing tacrolimus PK, and (2) identify areas requiring additional research to facilitate the use of population PK models to guide tacrolimus dosing decisions. METHODS The MEDLINE and EMBASE databases, as well as the reference lists of all articles, were searched to identify population PK models of tacrolimus developed from adult transplant recipients published from the inception of the databases to 29 February 2020. RESULTS Of the 69 studies identified, 55% were developed from kidney transplant recipients and 30% from liver transplant recipients. Most studies (91%) investigated the oral immediate-release formulation of tacrolimus. Few studies (17%) explained the effect of drug-drug interactions on tacrolimus PK. Only 35% of the studies performed an external evaluation to assess the generalizability of the models. Studies related variability in tacrolimus whole blood clearance among transplant recipients to either cytochrome P450 (CYP) 3A5 genotype (41%), days post-transplant (30%), or hematocrit (29%). Variability in the central volume of distribution was mainly explained by body weight (20% of studies). CONCLUSION The effect of clinically significant drug-drug interactions and different formulations and brands of tacrolimus should be considered for any future tacrolimus population PK model development. Further work is required to assess the generalizability of existing models and identify key factors that influence both initial and maintenance doses of tacrolimus, particularly in heart and lung transplant recipients.
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Chen L, Yang Y, Wang X, Wang C, Lin W, Jiao Z, Wang Z. Wuzhi Capsule Dosage Affects Tacrolimus Elimination in Adult Kidney Transplant Recipients, as Determined by a Population Pharmacokinetics Analysis. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:1093-1106. [PMID: 34511980 PMCID: PMC8423491 DOI: 10.2147/pgpm.s321997] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 08/06/2021] [Indexed: 12/19/2022]
Abstract
Purpose In this study, we aimed to establish a tacrolimus population pharmacokinetic model and better understand the drug-drug interaction between Wuzhi capsule and tacrolimus in Chinese renal transplant recipients. Patients and Methods We performed a population pharmacokinetic analysis using a non-linear mixed-effects model to determine the suitable Wuzhi capsule dose in combination with tacrolimus. Data on 1378 tacrolimus steady-state concentrations were obtained from 142 patients who received kidney transplant in Changhai Hospital and Huashan Hospital. Demographic characteristics, laboratory tests, genetic polymorphisms, and co-medications were evaluated. Results The one-compartment model best described data. Our final model identified creatinine clearance rate, hematocrit, Wuzhi capsule dose, CYP3A5*3 genetic polymorphisms, and tacrolimus daily dose as significant covariates for tacrolimus clearance, with the value of 14.4 L h-1, and the between-subject variability (BSV) was 25.4%. The Wuzhi capsule showed a dose-dependent effect on tacrolimus pharmacokinetics, demonstrating a stronger inhibitory effect than inductive effect. Conclusion Our model can accurately describe population pharmacokinetics of tacrolimus when combined with different doses of Wuzhi capsule. Additionally, this model can be used for individualizing tacrolimus dose following kidney transplantation.
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Affiliation(s)
- Lizhi Chen
- Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, 200433, People's Republic of China
| | - Yunyun Yang
- Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, 200433, People's Republic of China.,Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Xuebin Wang
- Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, 200433, People's Republic of China
| | - Chenyu Wang
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China
| | - Weiwei Lin
- Department of Pharmacology, The First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, People's Republic of China.,Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China
| | - Zhuo Wang
- Department of Pharmacy, Shanghai Changhai Hospital, Naval Medical University, Shanghai, 200433, People's Republic of China
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Yang CL, Sheng CC, Liao GY, Su Y, Feng LJ, Xia Q, Jiao Z, Xu DJ. Genetic polymorphisms in metabolic enzymes and transporters have no impact on mycophenolic acid pharmacokinetics in adult kidney transplant patients co-treated with tacrolimus: A population analysis. J Clin Pharm Ther 2021; 46:1564-1575. [PMID: 34312870 DOI: 10.1111/jcpt.13488] [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: 02/21/2021] [Revised: 05/05/2021] [Accepted: 07/01/2021] [Indexed: 12/17/2022]
Abstract
WHAT IS KNOWN AND OBJECTIVE Mycophenolate mofetil, an ester prodrug of mycophenolic acid (MPA), is widely used to prevent graft rejection after kidney transplantation. The pharmacokinetic (PK) of MPA has been extensively studied, which revealed a high degree of variability. An integrated population PK (PopPK) model of MPA and its main metabolite mycophenolic acid glucuronide (MPAG) was developed using the adult patients who underwent kidney transplant and were administered oral mycophenolate mofetil combined with tacrolimus. METHODS In total, 917 MPA and 740 MPAG concentrations in191 adult patients were analysed via nonlinear mixed-effects modelling. The concentration-time data were adequately described using a chain compartment model, including central and peripheral compartments for MPA and a central compartment for MPAG. Stepwise forward inclusion and backward elimination procedures were used to investigate the effects of genetic polymorphisms, including in UGT1A8, UGT1A9, UGT2B7, ABCB1, ABCC2, ABCG2, SLCO1B1, SLCO1B3, and HNF1α. RESULTS AND DISCUSSION These genetic polymorphisms in metabolic enzymes and transporters have no obvious impact on the PK of MPA in adult patients who underwent kidney transplant and were co-treated with tacrolimus. The post-transplant time, serum albumin, and creatinine clearance were identified as significant covariates affecting the PK of MPA and MPAG, which should be considered in the clinical use of mycophenolate mofetil. WHAT IS NEW AND CONCLUSION We established a PopPK model of MPA and MPAG in Chinese adult patients who underwent kidney transplant and were co-treated with tacrolimus. Genetic polymorphisms in metabolic enzymes and transporters showed no obvious impact on MMF PK. A model-informed dosing strategy was proposed by the established model, and MMF dose adjustment should be based on ALB levels and the post-transplantation time.
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Affiliation(s)
- Chun-Lan Yang
- Department of Pharmacy, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Chang-Cheng Sheng
- Department of Pharmacy, Guizhou Provincial People's Hospital, Guiyang, China
| | - Gui-Yi Liao
- Department of Urology, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Yong Su
- Department of Pharmacy, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Li-Juan Feng
- Department of Pharmacy, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Quan Xia
- Department of Pharmacy, the First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, China
| | - Du-Juan Xu
- Department of Pharmacy, the First Affiliated Hospital of Anhui Medical University, Hefei, China
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48
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Li L, Zhu M, Li DY, Guo HL, Hu YH, Xu ZY, Jing X, Chen F, Zhao F, Li YM, Xu J, Jiao Z. Dose tailoring of tacrolimus based on a non-linear pharmacokinetic model in children with refractory nephrotic syndrome. Int Immunopharmacol 2021; 98:107827. [PMID: 34284341 DOI: 10.1016/j.intimp.2021.107827] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 05/13/2021] [Accepted: 05/25/2021] [Indexed: 10/20/2022]
Abstract
The population pharmacokinetics (PPK) of tacrolimus (TAC) in children with refractory nephrotic syndrome (RNS) have not been well-characterized. This study aimed to investigate the significant factors affecting the TAC PPK characteristics of children with RNS and to optimize the dosing regimen. A total of 494 concentrations from 108 children were obtained from routine therapeutic drug monitoring between 2016 and 2018. Information regarding the demographic features, laboratory test results, genetic polymorphisms of CYP3A5 (rs776746) and co-therapy medications were collected. PPK analysis was performed using the nonlinear mixed-effects modelling (NONMEM) software and two modelling strategies (the linear one-compartment model and nonlinear Michaelis-Menten model) were evaluated and compared. CYP3A5 genotype, weight, daily dose of TAC and daily dose of diltiazem were retained in the final linear model. The absorption rate constant (Ka) was set at 4.48 h-1 in the linear model, and the apparent clearance (CL/F) and volume of distribution (V/F) in the final linear model were 14.2 L/h and 172 L, respectively. CYP3A5 genotype, weight and daily dose of diltiazem were the significant factors retained in the final nonlinear model. The maximal dose rate (Vmax) and the average steady-state concentration at half-Vmax (Km) in the final nonlinear model were 2.15 mg/day and 0.845 ng/ml, respectively. The nonlinear model described the pharmacokinetic data of TAC better than the linear model in children with RNS. A dosing regimen was proposed based on weight, CYP3A5 genotype and daily dose of diltiazem according to the final nonlinear PK model, which may facilitate individualized drug therapy with TAC.
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Affiliation(s)
- Ling Li
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China; School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Min Zhu
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China; Department of Pharmacy, Shanghai Chest Hospital, Shanghai, China
| | - De-Yi Li
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Hong-Li Guo
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Ya-Hui Hu
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Ze-Yue Xu
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China; School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Xia Jing
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Feng Chen
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China.
| | - Fei Zhao
- Department of Nephrology, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Yun-Man Li
- School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Jing Xu
- Department of Pharmacy, Children's Hospital of Nanjing Medical University, Nanjing, China.
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai, China.
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49
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Zwart TC, Guchelaar HJ, van der Boog PJM, Swen JJ, van Gelder T, de Fijter JW, Moes DJAR. Model-informed precision dosing to optimise immunosuppressive therapy in renal transplantation. Drug Discov Today 2021; 26:2527-2546. [PMID: 34119665 DOI: 10.1016/j.drudis.2021.06.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 04/21/2021] [Accepted: 06/04/2021] [Indexed: 12/18/2022]
Abstract
Immunosuppressive therapy is pivotal for sustained allograft and patient survival after renal transplantation. However, optimally balanced immunosuppressive therapy is challenged by between-patient and within-patient pharmacokinetic (PK) variability. This could warrant the application of personalised dosing strategies to optimise individual patient outcomes. Pharmacometrics, the science that investigates the xenobiotic-biotic interplay using computer-aided mathematical modelling, provides options to describe and quantify this PK variability and enables identification of patient characteristics affecting immunosuppressant PK and treatment outcomes. Here, we review and critically appraise the available pharmacometric model-informed dosing solutions for the typical immunosuppressants in modern renal transplantation, to guide their initial and subsequent dosing.
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Affiliation(s)
- Tom C Zwart
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands
| | - Paul J M van der Boog
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands; LUMC Transplant Center, Leiden University Medical Center, Leiden, the Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands
| | - Teun van Gelder
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands
| | - Johan W de Fijter
- Department of Internal Medicine (Nephrology), Leiden University Medical Center, Leiden, the Netherlands; LUMC Transplant Center, Leiden University Medical Center, Leiden, the Netherlands
| | - Dirk Jan A R Moes
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, the Netherlands; Leiden Network for Personalised Therapeutics, Leiden, the Netherlands.
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50
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Fan Z, Zheng D, Wen X, Shen F, Lei L, Su S, Zhang S, Liu Q, Zhang X, Lu Y, Di L, Shen XM, Da Y. CYP3A5*3 polymorphism and age affect tacrolimus blood trough concentration in myasthenia gravis patients. J Neuroimmunol 2021; 355:577571. [PMID: 33866281 DOI: 10.1016/j.jneuroim.2021.577571] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 04/04/2021] [Accepted: 04/05/2021] [Indexed: 12/12/2022]
Abstract
The study aims to identify clinical factors affecting tacrolimus blood trough concentration (C0) in myasthenia gravis (MG) patients and to optimize the initial dose of tacrolimus in MG treatment. A total of 103 MG patients participated in this study, and their clinical factors, medication regimens, C0 values and CYP3A5*3 polymorphisms were collected in detail. We used a linear mixed model to analyze the effect of multiple factors on the dosage-weighted C0 (C0:D) and performed subgroup analyses to investigate the consistency of correlations between influencing factors and the C0:D ratios. Among all factors, CYP3A5*3 polymorphism and age showed a strong positive correlation with C0:D ratios. The C0:D ratios (ng/ml·mg-1) were higher for CYP3A5*3/*3 than for CYP3A5*1 (mean difference: 1.038, 95% confidence interval [CI]: 0.820-1.256, P-value <0.001), and for age in the range of 45-64 and ≥ 65 years than for age < 45 years (mean difference [95% CI] and P-value: 0.531[0.257-0.805] and P-value <0.001, 0.703 [0.377-1.029] and P-value <0.001, respectively). The C0:D ratios were not related to corticosteroid dosage, body weight, sex, hematocrit or the concomitant use of calcium channel blockers. The consistencies of the correlations between C0:D ratios and CYP3A5*3 polymorphism or age were confirmed by subgroup analyses. Thus, CYP3A5*3 polymorphism and age should be considered in optimizing the initial dose of tacrolimus for MG treatment.
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Affiliation(s)
- Zhirong Fan
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Deqiang Zheng
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Xinmei Wen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Faxiu Shen
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Lin Lei
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Shengyao Su
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Shu Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qing Liu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xueping Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yan Lu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Li Di
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xin-Ming Shen
- Department of Neurology and Neuromuscular Research Laboratory, Mayo Clinic, Rochester, MN 55905, USA.
| | - Yuwei Da
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China.
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