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Wong S, Selby PR, Reuter SE. Determination of a vancomycin nephrotoxicity threshold and assessment of target attainment in hematology patients. Pharmacol Res Perspect 2024; 12:e1231. [PMID: 38940223 PMCID: PMC11211924 DOI: 10.1002/prp2.1231] [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: 02/13/2024] [Revised: 05/29/2024] [Accepted: 06/11/2024] [Indexed: 06/29/2024] Open
Abstract
An area-under-the-curve (AUC24)-based approach is recommended to guide vancomycin therapeutic drug monitoring (TDM), yet trough concentrations are still commonly used despite associated risks. A definitive toxicity target is lacking, which is important for hematology patients who have a higher risk of nephrotoxicity. The aims were to (1) assess the impact of trough-based TDM on acute kidney injury (AKI) incidence, (2) establish a vancomycin nephrotoxicity threshold, and (3) evaluate the proportion of hematology patients achieving vancomycin therapeutic targets. Retrospective data was collected from 100 adult patients with a hematological malignancy or aplastic anemia who received vancomycin between April 2020 and January 2021. AKI occurrence was determined based on serum creatinine concentrations, and individual pharmacokinetic parameters were estimated using a Bayesian approach. Receiver operating characteristic (ROC) curve analysis was performed to assess the ability of pharmacokinetic indices to predict AKI occurrence. The proportion of patients who achieved target vancomycin exposure was evaluated based on an AUC24/MIC ≥400 and the determined toxicity threshold. The incidence of AKI was 37%. ROC curve analysis indicated a maximum AUC24 of 644 mg.h/L over the treatment period was an important predictor of AKI. By Day 4 of treatment, 29% of treatment courses had supratherapeutic vancomycin exposure, with only 62% of courses achieving AUC24 targets. The identified toxicity threshold supports an AUC24 target range of 400-650 mg.h/L, assuming an MIC of 1 mg/L, to optimize vancomycin efficacy and minimize toxicity. This study highlights high rates of AKI in this population and emphasizes the importance of transitioning from trough-based TDM to an AUC-based approach to improve clinical outcomes.
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Affiliation(s)
- Sherilyn Wong
- UniSA Clinical and Health SciencesUniversity of South AustraliaAdelaideSouth AustraliaAustralia
| | - Philip R. Selby
- UniSA Clinical and Health SciencesUniversity of South AustraliaAdelaideSouth AustraliaAustralia
- School of MedicineThe University of AdelaideAdelaideSouth AustraliaAustralia
- SA Pharmacy, Royal Adelaide HospitalAdelaideSouth AustraliaAustralia
| | - Stephanie E. Reuter
- UniSA Clinical and Health SciencesUniversity of South AustraliaAdelaideSouth AustraliaAustralia
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2
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Terrier J, Gaspar F, Guidi M, Fontana P, Daali Y, Csajka C, Reny JL. Population Pharmacokinetic Models for Direct Oral Anticoagulants: A Systematic Review and Clinical Appraisal Using Exposure Simulation. Clin Pharmacol Ther 2022; 112:353-363. [PMID: 35593020 PMCID: PMC9540501 DOI: 10.1002/cpt.2649] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 05/13/2022] [Indexed: 01/22/2023]
Abstract
Available data have shown an association between direct oral anticoagulant (DOAC) plasma concentration and clinical, particularly bleeding, events. Factors that may influence DOAC plasma concentration are therefore the focus of particular attention. Population pharmacokinetic (PopPK) analyses can help in identifying such factors while providing predictive models. The main aim of the present study was to identify all the PopPK models to date for the four most frequently used DOACs (dabigatran, apixaban, rivaroxaban, and edoxaban). The secondary aim was to use these models to simulate different DOAC plasma concentration–time profiles in relevant clinical scenarios. The results of our model‐based simulations confirm the clinical relevance of the known major factors influencing DOAC exposure and support the current approved dose adaptation, at least for atrial fibrillation. They also highlight how the accumulation of covariates, not currently considered for dose adaptation due to their seemingly minor influence on DOAC exposure, lead to supratherapeutic blood concentrations and could thus enhance the risk of major bleeding. The present results therefore question DOAC dose adaptation in the presence of these covariates, such as drug–drug interaction or genotypes, alongside the known existing covariates. As the overall effect of accumulation of several covariates could be difficult to apprehend for the clinicians, PopPK modeling could represent an interesting approach for informed precision dosing and to improve personalized prescription of DOACs.
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Affiliation(s)
- Jean Terrier
- Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland.,Geneva Platelet Group, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Clinical Pharmacology and Toxicology Service, Anesthesiology Pharmacology and Intensive Care Department, Geneva University Hospitals, Geneva, Switzerland
| | - Frédéric Gaspar
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Geneva, Switzerland
| | - Monia Guidi
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Geneva, Switzerland.,Service of Clinical Pharmacology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Pierre Fontana
- Geneva Platelet Group, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Division of Angiology and Haemostasis, Geneva University Hospitals, Geneva, Switzerland
| | - Youssef Daali
- Geneva Platelet Group, Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Clinical Pharmacology and Toxicology Service, Anesthesiology Pharmacology and Intensive Care Department, Geneva University Hospitals, Geneva, Switzerland
| | - Chantal Csajka
- Center for Research and Innovation in Clinical Pharmaceutical Sciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.,School of Pharmaceutical Sciences, University of Geneva, Geneva, Switzerland.,Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, University of Lausanne, Geneva, Switzerland
| | - Jean-Luc Reny
- Division of General Internal Medicine, Geneva University Hospitals, Geneva, Switzerland.,Geneva Platelet Group, Faculty of Medicine, University of Geneva, Geneva, Switzerland
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3
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PBPK Modeling and Simulation and Therapeutic Drug Monitoring: Possible Ways for Antibiotic Dose Adjustment. Processes (Basel) 2021. [DOI: 10.3390/pr9112087] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Pharmacokinetics (PK) is a branch of pharmacology present and of vital importance for the research and development (R&D) of new drugs, post-market monitoring, and continued optimizations in clinical contexts. Ultimately, pharmacokinetics can contribute to improving patients’ clinical outcomes, helping enhance the efficacy of treatments, and reducing possible adverse side effects while also contributing to precision medicine. This article discusses the methods used to predict and study human pharmacokinetics and their evolution to the current physiologically based pharmacokinetic (PBPK) modeling and simulation methods. The importance of therapeutic drug monitoring (TDM) and PBPK as valuable tools for Model-Informed Precision Dosing (MIPD) are highlighted, with particular emphasis on antibiotic therapy since dosage adjustment of antibiotics can be vital to ensure successful clinical outcomes and to prevent the spread of resistant bacterial strains.
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Mueller-Schoell A, Groenland SL, Scherf-Clavel O, van Dyk M, Huisinga W, Michelet R, Jaehde U, Steeghs N, Huitema ADR, Kloft C. Therapeutic drug monitoring of oral targeted antineoplastic drugs. Eur J Clin Pharmacol 2021; 77:441-464. [PMID: 33165648 PMCID: PMC7935845 DOI: 10.1007/s00228-020-03014-8] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 10/01/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE This review provides an overview of the current challenges in oral targeted antineoplastic drug (OAD) dosing and outlines the unexploited value of therapeutic drug monitoring (TDM). Factors influencing the pharmacokinetic exposure in OAD therapy are depicted together with an overview of different TDM approaches. Finally, current evidence for TDM for all approved OADs is reviewed. METHODS A comprehensive literature search (covering literature published until April 2020), including primary and secondary scientific literature on pharmacokinetics and dose individualisation strategies for OADs, together with US FDA Clinical Pharmacology and Biopharmaceutics Reviews and the Committee for Medicinal Products for Human Use European Public Assessment Reports was conducted. RESULTS OADs are highly potent drugs, which have substantially changed treatment options for cancer patients. Nevertheless, high pharmacokinetic variability and low treatment adherence are risk factors for treatment failure. TDM is a powerful tool to individualise drug dosing, ensure drug concentrations within the therapeutic window and increase treatment success rates. After reviewing the literature for 71 approved OADs, we show that exposure-response and/or exposure-toxicity relationships have been established for the majority. Moreover, TDM has been proven to be feasible for individualised dosing of abiraterone, everolimus, imatinib, pazopanib, sunitinib and tamoxifen in prospective studies. There is a lack of experience in how to best implement TDM as part of clinical routine in OAD cancer therapy. CONCLUSION Sub-therapeutic concentrations and severe adverse events are current challenges in OAD treatment, which can both be addressed by the application of TDM-guided dosing, ensuring concentrations within the therapeutic window.
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Affiliation(s)
- Anna Mueller-Schoell
- Dept. of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany
- Graduate Research Training Program, PharMetrX, Berlin/Potsdam, Germany
| | - Stefanie L Groenland
- Department of Clinical Pharmacology, Division of Medical Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Oliver Scherf-Clavel
- Institute of Pharmacy and Food Chemistry, Julius-Maximilians-Universität Würzburg, Würzburg, Germany
| | - Madelé van Dyk
- College of Medicine and Public Health, Flinders University, Adelaide, SA, Australia
| | - Wilhelm Huisinga
- Institute of Mathematics, University of Potsdam, Potsdam, Germany
| | - Robin Michelet
- Dept. of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany
| | - Ulrich Jaehde
- Department of Clinical Pharmacy, Institute of Pharmacy, University of Bonn, Bonn, Germany
| | - Neeltje Steeghs
- Department of Clinical Pharmacology, Division of Medical Oncology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - Alwin D R Huitema
- Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
- Department of Clinical Pharmacy, University Medical Center, Utrecht University, Utrecht, The Netherlands
| | - Charlotte Kloft
- Dept. of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany.
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Stocker SL, Carland JE, Reuter SE, Stacy AE, Schaffer AL, Stefani M, Lau C, Kirubakaran R, Yang JJ, Shen CFJ, Roberts DM, Marriott DJE, Day RO, Brett J. Evaluation of a Pilot Vancomycin Precision Dosing Advisory Service on Target Exposure Attainment Using an Interrupted Time Series Analysis. Clin Pharmacol Ther 2020; 109:212-221. [PMID: 33190285 DOI: 10.1002/cpt.2113] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 11/10/2020] [Indexed: 12/30/2022]
Abstract
This study evaluated the ability of a pilot therapeutic drug monitoring (TDM) Advisory Service to facilitate vancomycin therapeutic target attainment within a real-world clinical setting. The Service provided area under the concentration-time curve (AUC)-guided vancomycin dose recommendations, using Bayesian forecasting software and clinical expertise, to prescribers at an Australian hospital. A retrospective audit of intravenous vancomycin therapy (> 48 hours) in adults (≥ 18 years old) was undertaken over a 54-month period to evaluate attainment of established vancomycin pharmacokinetic/pharmacodynamic targets (AUC over 24 hours / minimum inhibitory concentration: 400-600) before (36-month period) and after (18-month period) Service implementation. Interrupted time series analysis was employed to evaluate monthly measures of the median proportion of therapy spent within the target range. Indices of time to target attainment were also assessed before and after Service implementation. The final cohort comprised 1,142 courses of vancomycin (816 patients); 835 courses (596 patients) and 307 courses (220 patients) administered before and after Service implementation, respectively. Prior to piloting the Service, the median proportion of time in the target range was 40.1% (95% CI, 34.3-46.0%); this increased by 10.4% (95% CI, 1.2-19.6%, P = 0.03) after the Service, and was sustained throughout the post-Service evaluation period. Post-Service target attainment at 48-72 hours after initiation of therapy was increased (7.8%, 95% CI, 1.3-14.3%, P = 0.02). The findings of this study provide evidence that a consultative TDM Service can facilitate attainment of vancomycin therapeutic targets; however, optimization of the Service may further improve the use of vancomycin.
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Affiliation(s)
- Sophie L Stocker
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia.,Sydney Pharmacy School, Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Jane E Carland
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Stephanie E Reuter
- UniSA Clinical & Health Sciences, University of South Australia, Adelaide, South Australia, Australia
| | - Alexandra E Stacy
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,School of Medicine, The University of Notre Dame Australia, Sydney, New South Wales, Australia
| | - Andrea L Schaffer
- Centre for Big Data Research in Health, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Maurizio Stefani
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Cindy Lau
- Sydney Pharmacy School, Faculty of Medicine & Health, The University of Sydney, Sydney, New South Wales, Australia.,Pharmacy Department, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Ranita Kirubakaran
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Jennifer J Yang
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Catriona F J Shen
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Darren M Roberts
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Deborah J E Marriott
- St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia.,Department of Clinical Microbiology & Infectious Diseases, St Vincent's Hospital, Sydney, New South Wales, Australia
| | - Richard O Day
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
| | - Jonathan Brett
- Department of Clinical Pharmacology & Toxicology, St Vincent's Hospital, Sydney, New South Wales, Australia.,St Vincent's Clinical School, Faculty of Medicine, The University of New South Wales, Sydney, New South Wales, Australia
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Cheng Y, Wang CY, Li ZR, Pan Y, Liu MB, Jiao Z. Can Population Pharmacokinetics of Antibiotics be Extrapolated? Implications of External Evaluations. Clin Pharmacokinet 2020; 60:53-68. [PMID: 32960439 DOI: 10.1007/s40262-020-00937-4] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND AND OBJECTIVE External evaluation is an important issue in the population pharmacokinetic analysis of antibiotics. The purpose of this review was to summarize the current approaches and status of external evaluations and discuss the implications of external evaluation results for the future individualization of dosing regimens. METHODS We systematically searched the PubMed and EMBASE databases for external evaluation studies of population analysis and extracted the relevant information from these articles. A total of 32 studies were included in this review. RESULTS Vancomycin was investigated in 17 (53.1%) articles and was the most studied drug. Other studied drugs included gentamicin, tobramycin, amikacin, amoxicillin, ceftaroline, meropenem, fluconazole, voriconazole, and rifampicin. Nine (28.1%) studies were prospective, and the sample size varied widely between studies. Thirteen (40.6%) studies evaluated the population pharmacokinetic models by systematically searching for previous studies. Seven (21.9%) studies were multicenter studies, and 27 (84.4%) adopted the sparse sampling strategy. Almost all external evaluation studies of antibiotics (93.8%) used metrics for prediction-based diagnostics, while relatively fewer studies were based on simulations (46.9%) and Bayesian forecasting (25.0%). CONCLUSION The results of external evaluations in previous studies revealed the poor extrapolation performance of existing models of prediction- and simulation-based diagnostics, whereas the posterior Bayesian method could improve predictive performance. There is an urgent need for the development of standards and guidelines for external evaluation studies.
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Affiliation(s)
- Yu Cheng
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China.,Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Road, Gulou, Fuzhou, 350001, China
| | - Chen-Yu Wang
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China
| | - Zi-Ran Li
- College of Pharmacy, Fudan University, Shanghai, China
| | - Yan Pan
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China
| | - Mao-Bai Liu
- Department of Pharmacy, Fujian Medical University Union Hospital, 29 Xin Quan Road, Gulou, Fuzhou, 350001, China.
| | - Zheng Jiao
- Department of Pharmacy, Shanghai Chest Hospital, Shanghai Jiao Tong University, 241 West Huaihai Road, Shanghai, 200040, China.
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