1
|
Aurélie L, Andréa B, Gauvind K, Olivier B, Raoul B, Dayan F, Sylvain B, Romain G. External Evaluation of Population Pharmacokinetics Models of Lithium in the Bipolar Population. Pharmaceuticals (Basel) 2023; 16:1627. [PMID: 38004492 PMCID: PMC10674621 DOI: 10.3390/ph16111627] [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: 10/09/2023] [Revised: 10/27/2023] [Accepted: 10/30/2023] [Indexed: 11/26/2023] Open
Abstract
Lithium has been used in the treatment of bipolar disorder for several decades. Treatment optimization is recommended for this drug, due to its narrow therapeutic range and a large pharmacokinetics (PK) variability. In addition to therapeutic drug monitoring, attempts have been made to predict individual lithium doses using population pharmacokinetics (popPK) models. This study aims to assess the clinical applicability of published lithium popPK models by testing their predictive performance on two different external datasets. Available PopPK models were identified and their predictive performance was determined using a clinical dataset (46 patients/samples) and the literature dataset (89 patients/samples). The median prediction error (PE) and median absolute PE were used to assess bias and inaccuracy. The potential factors influencing model predictability were also investigated, and the results of both external evaluations compared. Only one model met the acceptability criteria for both datasets. Overall, there was a lack of predictability of models; median PE and median absolute PE, respectively, ranged from -6.6% to 111.2% and from 24.4% to 111.2% for the literature dataset, and from -4.5% to 137.6% and from 24.9% to 137.6% for the clinical dataset. Most models underpredicted the observed concentrations (7 out of 10 models presented a negative bias). Renal status was included as a covariate of lithium's clearance in only two models. To conclude, most of lithium's PopPK models had limited predictive performances related to the absence of covariates of interest included, such as renal status. A solution to this problem could be to improve the models with methodologies such as metamodeling. This could be useful in the perspective of model-informed precision dosing.
Collapse
Affiliation(s)
- Lereclus Aurélie
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Inserm UMR 1106, 13385 Marseille, France (G.R.)
- EXACTCURE, 06000 Nice, France (F.D.)
| | | | - Kallée Gauvind
- Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, 13005 Marseille, France
| | - Blin Olivier
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Inserm UMR 1106, 13385 Marseille, France (G.R.)
- Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, 13005 Marseille, France
| | - Belzeaux Raoul
- Pôle Universitaire de Psychiatrie, CHU de Montpellier, 34000 Montpellier, France
| | | | | | - Guilhaumou Romain
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Inserm UMR 1106, 13385 Marseille, France (G.R.)
- Service de Pharmacologie Clinique et Pharmacovigilance, Hôpital de la Timone, 13005 Marseille, France
| |
Collapse
|
2
|
Oda K, Yamada T, Matsumoto K, Hanai Y, Ueda T, Samura M, Shigemi A, Jono H, Saito H, Kimura T. Model-informed precision dosing of vancomycin for rapid achievement of target area under the concentration-time curve: A simulation study. Clin Transl Sci 2023; 16:2265-2275. [PMID: 37718491 PMCID: PMC10651648 DOI: 10.1111/cts.13626] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 08/22/2023] [Accepted: 08/24/2023] [Indexed: 09/19/2023] Open
Abstract
In this study, we aimed to evaluate limited sampling strategies for achieving the therapeutic ranges of the area under the concentration-time curve (AUC) of vancomycin on the first and second day (AUC0-24 , AUC24-48 , respectively) of therapy. A virtual population of 1000 individuals was created using a population pharmacokinetic (PopPK) model, which was validated and incorporated into our model-informed precision dosing tool. The results were evaluated using six additional PopPK models selected based on a study design of prospective or retrospective data collection with sufficient concentrations. Bayesian forecasting was performed to evaluate the probability of achieving the therapeutic range of AUC, defined as a ratio of estimated/reference AUC within 0.8-1.2. The Bayesian posterior probability of achieving the AUC24-48 range increased from 51.3% (a priori probability) to 77.5% after using two-point sampling at the trough and peak on the first day. Sampling on the first day also yielded a higher Bayesian posterior probability (86.1%) of achieving the AUC0-24 range compared to the a priori probability of 60.1%. The Bayesian posterior probability of achieving the AUC at steady-state (AUCSS ) range by sampling on the first or second day decreased with decreased kidney function. We demonstrated that second-day trough and peak sampling provided accurate AUC24-48 , and first-day sampling may assist in rapidly achieving therapeutic AUC24-48 , although the AUCSS should be re-estimated in patients with reduced kidney function owing to its unreliable predictive performance.
Collapse
Affiliation(s)
- Kazutaka Oda
- Department of PharmacyKumamoto University HospitalKumamotoJapan
- Department of Infection ControlKumamoto University HospitalKumamotoJapan
| | - Tomoyuki Yamada
- Department of PharmacyOsaka Medical and Pharmaceutical University HospitalOsakaJapan
| | - Kazuaki Matsumoto
- Division of PharmacodynamicsKeio University Faculty of PharmacyTokyoJapan
| | - Yuki Hanai
- Department of Clinical Pharmacy, Faculty of Pharmaceutical SciencesToho UniversityChibaJapan
| | - Takashi Ueda
- Department of Infection Control and PreventionHyogo College of MedicineNishinomiyaHyogoJapan
| | - Masaru Samura
- Department of PharmacyYokohama General HospitalYokohamaKanagawaJapan
| | - Akari Shigemi
- Department of PharmacyKagoshima University HospitalKagoshima CityKagoshimaJapan
| | - Hirofumi Jono
- Department of PharmacyKumamoto University HospitalKumamotoJapan
| | - Hideyuki Saito
- Department of PharmacyKumamoto University HospitalKumamotoJapan
| | - Toshimi Kimura
- Department of PharmacyJuntendo University HospitalTokyoJapan
| |
Collapse
|
3
|
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.
Collapse
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.
| |
Collapse
|
4
|
Wei S, Zhang D, Zhao Z, Mei S. Population pharmacokinetic model of vancomycin in postoperative neurosurgical patients. Front Pharmacol 2022; 13:1005791. [PMID: 36225566 PMCID: PMC9548544 DOI: 10.3389/fphar.2022.1005791] [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: 07/29/2022] [Accepted: 09/13/2022] [Indexed: 12/03/2022] Open
Abstract
Objective: Vancomycin is commonly used in postoperative neurosurgical patients for empirical anti-infective treatment due to the low success rate of bacterial culture in cerebrospinal fluid (about 20%) and the high mortality of intracranial infection. At conventional doses, the rate of target achievement for vancomycin trough concentration is low and the pharmacokinetics of vancomycin varies greatly in these patients, which often leads to treatment failure. The objective of this study was to establish a population pharmacokinetic (PPK) model of vancomycin in postoperative neurosurgical patients for precision medicine. Method: A total of 895 vancomycin plasma concentrations from 560 patients (497 postoperative neurosurgical patients) were retrospectively collected. The model was analyzed by nonlinear mixed effects modeling method. One-compartment model and mixed residual model was employed. The influence of covariates on model parameters was tested by forward addition and backward elimination. Goodness-of-fit, bootstrap and visual predictive check were used for model evaluation. Monte Carlo simulations were employed for dosing strategies with AUC24 targets 400–600. Result: Estimated glomerular filtration rate (eGFR), body weight (BW) and mannitol had significant influence on vancomycin clearance (CL). eGFR(mL/min)=144×(Scr/a)b×0.993age, for female, a = 0.7, Scr ≤ 0.7 mg/dl, b = −0.329, Scr > 0.7 mg/dl, b = −1.209; for male, a = 0.9, Scr ≤ 0.9 mg/dl, b = −0.411, Scr > 0.9 mg/dl, b = −1.210. Vancomycin clearance was accelerated when co-medicated with mannitol and increased with eGFR and BW. In the final model, the population typical value is 7.98 L/h for CL and 60.2 L for apparent distribution volume, CL (L/h)=7.98×(eGFR/115.2)0.8×(BW/70)0.3×eA, where A = 0.13 when co-medicated with mannitol, otherwise A = 0. The model is stable and effective, with good predictability. Conclusion: In postoperative neurosurgical patients, a higher dose of vancomycin may be required due to the augmented renal function and the commonly used mannitol, especially in those with high body weight. Our vancomycin PPK model could be used for individualized treatment in postoperative neurosurgical patients.
Collapse
Affiliation(s)
- Shifeng Wei
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, China
| | - Dongjie Zhang
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, China
| | - Zhigang Zhao
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, China
- *Correspondence: Zhigang Zhao, ; Shenghui Mei,
| | - Shenghui Mei
- Department of Pharmacy, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Clinical Pharmacology, College of Pharmaceutical Sciences, Capital Medical University, Beijing, China
- *Correspondence: Zhigang Zhao, ; Shenghui Mei,
| |
Collapse
|
5
|
Clinical Practice Guidelines for Therapeutic Drug Monitoring of Vancomycin in the Framework of Model-Informed Precision Dosing: A Consensus Review by the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring. Pharmaceutics 2022; 14:pharmaceutics14030489. [PMID: 35335866 PMCID: PMC8955715 DOI: 10.3390/pharmaceutics14030489] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 01/08/2023] Open
Abstract
Background: To promote model-informed precision dosing (MIPD) for vancomycin (VCM), we developed statements for therapeutic drug monitoring (TDM). Methods: Ten clinical questions were selected. The committee conducted a systematic review and meta-analysis as well as clinical studies to establish recommendations for area under the concentration-time curve (AUC)-guided dosing. Results: AUC-guided dosing tended to more strongly decrease the risk of acute kidney injury (AKI) than trough-guided dosing, and a lower risk of treatment failure was demonstrated for higher AUC/minimum inhibitory concentration (MIC) ratios (cut-off of 400). Higher AUCs (cut-off of 600 μg·h/mL) significantly increased the risk of AKI. Although Bayesian estimation with two-point measurement was recommended, the trough concentration alone may be used in patients with mild infections in whom VCM was administered with q12h. To increase the concentration on days 1–2, the routine use of a loading dose is required. TDM on day 2 before steady state is reached should be considered to optimize the dose in patients with serious infections and a high risk of AKI. Conclusions: These VCM TDM guidelines provide recommendations based on MIPD to increase treatment response while preventing adverse effects.
Collapse
|
6
|
Alqahtani S, Alfarhan A, Alsultan A, Alsarhani E, Alsubaie A, Asiri Y. Assessment of Micafungin Dosage Regimens in Patients with Cancer Using Pharmacokinetic/Pharmacodynamic Modeling and Monte Carlo Simulation. Antibiotics (Basel) 2021; 10:antibiotics10111363. [PMID: 34827301 PMCID: PMC8615109 DOI: 10.3390/antibiotics10111363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 11/03/2021] [Accepted: 11/06/2021] [Indexed: 11/18/2022] Open
Abstract
Micafungin is widely used for invasive candidiasis, especially in critically ill patients and those with cancer, and for empirical antifungal therapy in patients with neutropenic fever. This is the first study to investigate the pharmacokinetics and disposition parameters of micafungin in patients with cancer. In this observational pharmacokinetic study, blood samples were collected and analyzed using high-performance liquid chromatography. Pharmacokinetic parameters were estimated using Monolix 4.4 software. The plasma micafungin concentrations were measured in a total of 133 samples from 19 patients. In the final two-compartment model with linear elimination, the estimated micafungin clearance (CL) was significantly higher in patients with cancer than in those without cancer (1.2 vs. 0.6 L/h, p = 0.012), whereas other parameters did not significantly differ between the two groups. Aspartate and alanine transaminases and body weight significantly influenced micafungin CL in patients, with and without cancer. Overall, the probability of target attainment increased with increasing doses and decreased with higher MICs in both groups. In simulations, the patients without cancer achieved higher pharmacokinetic/pharmacodynamic targets with a 90% probability for all simulated doses, compared to the patients with cancer. Micafungin demonstrated dose-proportional linear pharmacokinetics in both the patients with and those without cancer. The estimated micafungin CL was significantly higher in patients with cancer, suggesting a need for increased dosage, especially for Candida spp. with high MICs, in these patients. Further studies should assess the efficacy and optimum dosage of micafungin for the treatment and prevention of febrile neutropenia (FN) in patients with cancer.
Collapse
Affiliation(s)
- Saeed Alqahtani
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
- Clinical Pharmacokinetics and Pharmacodynamics Unit, King Saud University Medical City, Riyadh 11451, Saudi Arabia
- Correspondence:
| | - Asma Alfarhan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
- Clinical Pharmacokinetics and Pharmacodynamics Unit, King Saud University Medical City, Riyadh 11451, Saudi Arabia
| | - Abdullah Alsultan
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
- Clinical Pharmacokinetics and Pharmacodynamics Unit, King Saud University Medical City, Riyadh 11451, Saudi Arabia
| | - Emad Alsarhani
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
- Clinical Pharmacokinetics and Pharmacodynamics Unit, King Saud University Medical City, Riyadh 11451, Saudi Arabia
| | - Abdulaziz Alsubaie
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
- Clinical Pharmacokinetics and Pharmacodynamics Unit, King Saud University Medical City, Riyadh 11451, Saudi Arabia
| | - Yousif Asiri
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; (A.A.); (A.A.); (E.A.); (A.A.); (Y.A.)
| |
Collapse
|
7
|
Lin Z, Chen DY, Zhu YW, Jiang ZL, Cui K, Zhang S, Chen LH. Population pharmacokinetic modeling and clinical application of vancomycin in Chinese patients hospitalized in intensive care units. Sci Rep 2021; 11:2670. [PMID: 33514803 PMCID: PMC7846798 DOI: 10.1038/s41598-021-82312-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 01/18/2021] [Indexed: 11/19/2022] Open
Abstract
Management of vancomycin administration for intensive care units (ICU) patients remains a challenge. The aim of this study was to describe a population pharmacokinetic model of vancomycin for optimizing the dose regimen for ICU patients. We prospectively enrolled 466 vancomycin-treated patients hospitalized in the ICU, collected trough or approach peak blood samples of vancomycin and recorded corresponding clinical information from July 2015 to December 2017 at Tai Zhou Hospital of Zhejiang Province. The pharmacokinetics of vancomycin was analyzed by nonlinear mixed effects modeling with Kinetica software. Internal and external validation was evaluated by the maximum likelihood method. Then, the individual dosing regimens of the 92 patients hospitalized in the ICU whose steady state trough concentrations exceeded the target range (10–20 μg/ml) were adjusted by the Bayes feedback method. The final population pharmacokinetic model show that clearance rate (CL) of vancomycin will be raised under the conditions of dopamine combined treatment, severe burn status (Burn-S) and increased total body weight (TBW), but reduced under the conditions of increased serum creatinine (Cr) and continuous renal replacement therapy status; Meanwhile, the apparent distribution volume (V) of vancomycin will be enhanced under the terms of increased TBW, however decreased under the terms of increased age and Cr. The population pharmacokinetic parameters (CL and V) according to the final model were 3.16 (95%CI 2.83, 3.40) L/h and 60.71 (95%CI 53.15, 67.46). The mean absolute prediction error for external validation by the final model was 12.61% (95CI 8.77%, 16.45%). Finally, the prediction accuracy of 90.21% of the patients’ detected trough concentrations that were distributed in the target range of 10–20 μg/ml after dosing adjustment was found to be adequate. There is significant heterogeneity in the CL and V of vancomycin in ICU patients. The constructed model is sufficiently precise for the Bayesian dose prediction of vancomycin concentrations for the population of ICU Chinese patients.
Collapse
Affiliation(s)
- Zhong Lin
- Department of Clinical Pharmacy, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Ximen Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Dan-Yang Chen
- Rehabilitation Department, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Xi Men Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Yan-Wu Zhu
- Department of Clinical Pharmacy, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Ximen Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Zheng-Li Jiang
- Department of Clinical Pharmacy, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Ximen Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Ke Cui
- Intensive Care Unit, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Xi Men Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Sheng Zhang
- Intensive Care Unit, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Xi Men Street No. 150, Linhai, 317000, Zhejiang Province, China
| | - Li-Hua Chen
- Public Scientific Research Platform, Taizhou Hospital of Zhejiang Province Affiliated To Wenzhou Medical University, Xi Men Street No. 150, Linhai, 317000, Zhejiang Province, China.
| |
Collapse
|
8
|
Aljutayli A, Marsot A, Nekka F. An Update on Population Pharmacokinetic Analyses of Vancomycin, Part I: In Adults. Clin Pharmacokinet 2020; 59:671-698. [DOI: 10.1007/s40262-020-00866-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
|