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van Os W, Pham AD, Eberl S, Minichmayr IK, van Hasselt JGC, Zeitlinger M. Integrative model-based comparison of target site-specific antimicrobial effects: A case study with ceftaroline and lefamulin. Int J Antimicrob Agents 2024; 63:107148. [PMID: 38508535 DOI: 10.1016/j.ijantimicag.2024.107148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 01/11/2024] [Accepted: 03/14/2024] [Indexed: 03/22/2024]
Abstract
OBJECTIVE Predictions of antimicrobial effects typically rely on plasma-based pharmacokinetic-pharmacodynamic (PK-PD) targets, ignoring target-site concentrations and potential differences in tissue penetration between antibiotics. In this study, we applied PK-PD modelling to compare target site-specific effects of antibiotics by integrating clinical microdialysis data, in vitro time-kill curves, and antimicrobial susceptibility distributions. As a case study, we compared the effect of lefamulin and ceftaroline against methicillin-resistant Staphylococcus aureus (MRSA) at soft-tissue concentrations. METHODS A population PK model describing lefamulin concentrations in plasma, subcutaneous adipose and muscle tissue was developed. For ceftaroline, a similar previously reported PK model was adopted. In vitro time-kill experiments were performed with six MRSA isolates and a PD model was developed to describe bacterial growth and antimicrobial effects. The clinical PK and in vitro PD models were linked to compare antimicrobial effects of ceftaroline and lefamulin at the different target sites. RESULTS Considering minimum inhibitory concentration (MIC) distributions and standard dosages, ceftaroline showed superior anti-MRSA effects compared to lefamulin both at plasma and soft-tissue concentrations. Looking at the individual antibiotics, lefamulin effects were highest at soft-tissue concentrations, while ceftaroline effects were highest at plasma concentrations, emphasising the importance of considering target-site PK-PD in antibiotic treatment optimisation. CONCLUSION Given standard dosing regimens, ceftaroline appeared more effective than lefamulin against MRSA at soft-tissue concentrations. The PK-PD model-based approach applied in this study could be used to compare or explore the potential of antibiotics for specific indications or in populations with unique target-site PK.
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Affiliation(s)
- Wisse van Os
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Anh Duc Pham
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Sabine Eberl
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - Iris K Minichmayr
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria
| | - J G Coen van Hasselt
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Markus Zeitlinger
- Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.
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Zwep LB, Guo T, Nagler T, Knibbe CAJ, Meulman JJ, van Hasselt JGC. Virtual Patient Simulation Using Copula Modeling. Clin Pharmacol Ther 2024; 115:795-804. [PMID: 37946529 DOI: 10.1002/cpt.3099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023]
Abstract
Virtual patient simulation is increasingly performed to support model-based optimization of clinical trial designs or individualized dosing strategies. Quantitative pharmacological models typically incorporate individual-level patient characteristics, or covariates, which enable the generation of virtual patient cohorts. The individual-level patient characteristics, or covariates, used as input for such simulations should accurately reflect the values seen in real patient populations. Current methods often make unrealistic assumptions about the correlation between patient's covariates or require direct access to actual data sets with individual-level patient data, which may often be limited by data sharing limitations. We propose and evaluate the use of copulas to address current shortcomings in simulation of patient-associated covariates for virtual patient simulations for model-based dose and trial optimization in clinical pharmacology. Copulas are multivariate distribution functions that can capture joint distributions, including the correlation, of covariate sets. We compare the performance of copulas to alternative simulation strategies, and we demonstrate their utility in several case studies. Our work demonstrates that copulas can reproduce realistic patient characteristics, both in terms of individual covariates and the dependence structure between different covariates, outperforming alternative methods, in particular when aiming to reproduce high-dimensional covariate sets. In conclusion, copulas represent a versatile and generalizable approach for virtual patient simulation which preserve relationships between covariates, and offer an open science strategy to facilitate re-use of patient data sets.
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Affiliation(s)
- Laura B Zwep
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Tingjie Guo
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Thomas Nagler
- Department of Statistics, Ludwig Maximilian University of Munich, Munich, Germany
| | - Catherijne A J Knibbe
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - Jacqueline J Meulman
- LUXs Data Science, Leiden, The Netherlands
- Department of Statistics, Stanford University, Stanford, California, USA
| | - J G Coen van Hasselt
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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Mehta K, Balazki P, van der Graaf PH, Guo T, van Hasselt JGC. Predictions of Bedaquiline Central Nervous System Exposure in Patients with Tuberculosis Meningitis Using Physiologically based Pharmacokinetic Modeling. Clin Pharmacokinet 2024:10.1007/s40262-024-01363-6. [PMID: 38530588 DOI: 10.1007/s40262-024-01363-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2024] [Indexed: 03/28/2024]
Abstract
BACKGROUND AND OBJECTIVE The use of bedaquiline as a treatment option for drug-resistant tuberculosis meningitis (TBM) is of interest to address the increased prevalence of resistance to first-line antibiotics. To this end, we describe a whole-body physiologically based pharmacokinetic (PBPK) model for bedaquiline to predict central nervous system (CNS) exposure. METHODS A whole-body PBPK model was developed for bedaquiline and its metabolite, M2. The model included compartments for brain and cerebrospinal fluid (CSF). Model predictions were evaluated by comparison to plasma PK time profiles following different dosing regimens and sparse CSF concentrations data from patients. Simulations were then conducted to compare CNS and lung exposures to plasma exposure at clinically relevant dosing schedules. RESULTS The model appropriately described the observed plasma and CSF bedaquiline and M2 concentrations from patients with pulmonary tuberculosis (TB). The model predicted a high impact of tissue binding on target site drug concentrations in CNS. Predicted unbound exposures within brain interstitial exposures were comparable with unbound vascular plasma and unbound lung exposures. However, unbound brain intracellular exposures were predicted to be 7% of unbound vascular plasma and unbound lung intracellular exposures. CONCLUSIONS The whole-body PBPK model for bedaquiline and M2 predicted unbound concentrations in brain to be significantly lower than the unbound concentrations in the lung at clinically relevant doses. Our findings suggest that bedaquiline may result in relatively inferior efficacy against drug-resistant TBM when compared with efficacy against drug-resistant pulmonary TB.
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Affiliation(s)
- Krina Mehta
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
| | | | - Piet H van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara, Canterbury, UK
| | - Tingjie Guo
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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den Hartog I, Zwep LB, Meulman JJ, Hankemeier T, van de Garde EMW, van Hasselt JGC. Longitudinal metabolite profiling of Streptococcus pneumoniae-associated community-acquired pneumonia. Metabolomics 2024; 20:35. [PMID: 38441696 PMCID: PMC10914916 DOI: 10.1007/s11306-024-02091-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/17/2024] [Indexed: 03/07/2024]
Abstract
INTRODUCTION Longitudinal biomarkers in patients with community-acquired pneumonia (CAP) may help in monitoring of disease progression and treatment response. The metabolic host response could be a potential source of such biomarkers since it closely associates with the current health status of the patient. OBJECTIVES In this study we performed longitudinal metabolite profiling in patients with CAP for a comprehensive range of metabolites to identify potential host response biomarkers. METHODS Previously collected serum samples from CAP patients with confirmed Streptococcus pneumoniae infection (n = 25) were used. Samples were collected at multiple time points, up to 30 days after admission. A wide range of metabolites was measured, including amines, acylcarnitines, organic acids, and lipids. The associations between metabolites and C-reactive protein (CRP), procalcitonin, CURB disease severity score at admission, and total length of stay were evaluated. RESULTS Distinct longitudinal profiles of metabolite profiles were identified, including cholesteryl esters, diacyl-phosphatidylethanolamine, diacylglycerols, lysophosphatidylcholines, sphingomyelin, and triglycerides. Positive correlations were found between CRP and phosphatidylcholine (34:1) (cor = 0.63) and negative correlations were found for CRP and nine lysophosphocholines (cor = - 0.57 to - 0.74). The CURB disease severity score was negatively associated with six metabolites, including acylcarnitines (tau = - 0.64 to - 0.58). Negative correlations were found between the length of stay and six triglycerides (TGs), especially TGs (60:3) and (58:2) (cor = - 0.63 and - 0.61). CONCLUSION The identified metabolites may provide insight into biological mechanisms underlying disease severity and may be of interest for exploration as potential treatment response monitoring biomarker.
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Affiliation(s)
- Ilona den Hartog
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Laura B Zwep
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Jacqueline J Meulman
- LUXs Data Science, Leiden, The Netherlands
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Thomas Hankemeier
- Metabolomics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Ewoudt M W van de Garde
- Division of Pharmacoepidemiology and Clinical Pharmacology, Department of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
- Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - J G Coen van Hasselt
- Division of Systems Pharmacology & Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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Mehta K, Guo T, van der Graaf PH, van Hasselt JGC. Model-based dose optimization framework for bedaquiline, pretomanid and linezolid for the treatment of drug-resistant tuberculosis. Br J Clin Pharmacol 2024; 90:463-474. [PMID: 37817504 DOI: 10.1111/bcp.15925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/29/2023] [Accepted: 10/04/2023] [Indexed: 10/12/2023] Open
Abstract
AIMS Bedaquiline, pretomanid and linezolid (BPaL) combination treatment against Mycobacterium tuberculosis is promising, yet safety and adherence concerns exist that motivate exploration of alternative dosing regimens. We developed a mechanistic modelling framework to compare the efficacy of the current and alternative BPaL treatment strategies. METHODS Pharmacodynamic models for each drug in the BPaL combination treatment were developed using in vitro time-kill data. These models were combined with pharmacokinetic models, incorporating body weight, lesion volume, site-of-action distribution, bacterial susceptibility and pharmacodynamic interactions to assemble the framework. The model was qualified by comparing the simulations against the observed clinical data. Simulations were performed evaluating bedaquiline and linezolid approved (bedaquiline 400 mg once daily [QD] for 14 days followed by 200 mg three times a week, linezolid 1200 mg QD) and alternative dosing regimens (bedaquiline 200 mg QD, linezolid 600 mg QD). RESULTS The framework adequately described the observed antibacterial activity data in patients following monotherapy for each drug and approved BPaL dosing. The simulations suggested a minor difference in median time to colony forming unit (CFU)-clearance state with the bedaquiline alternative compared to the approved dosing and the linezolid alternative compared to the approved dosing. Median time to non-replicating-clearance state was predicted to be 15 days from the CFU-clearance state. CONCLUSIONS The model-based simulations suggested that comparable efficacy can be achieved using alternative bedaquiline and linezolid dosing, which may improve safety and adherence in drug-resistant tuberculosis patients. The framework can be utilized to evaluate treatment optimization approaches, including dosing regimen and duration of treatment predictions to eradicate both replicating- and non-replicating bacteria from lung and lesions.
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Affiliation(s)
- Krina Mehta
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Tingjie Guo
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Piet H van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara, Canterbury, UK
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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Tandar ST, Aulin LBS, Leemkuil EMJ, Liakopoulos A, van Hasselt JGC. Semi-mechanistic modeling of resistance development to β-lactam and β-lactamase-inhibitor combinations. J Pharmacokinet Pharmacodyn 2023:10.1007/s10928-023-09895-3. [PMID: 38008877 DOI: 10.1007/s10928-023-09895-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/27/2023] [Indexed: 11/28/2023]
Abstract
The use of β-lactam (BL) and β-lactamase inhibitor (BLI) combinations, such as piperacillin-tazobactam (PIP-TAZ) is an effective strategy to combat infections by extended-spectrum β-lactamase-producing bacteria. However, in Gram-negative bacteria, resistance (both mutational and adaptive) to BL-BLI combination can still develop through multiple mechanisms. These mechanisms may include increased β-lactamase activity, reduced drug influx, and increased drug efflux. Understanding the relative contribution of these mechanisms during resistance development helps identify the most impactful mechanism to target in designing a treatment to counter BL-BLI resistance. This study used semi-mechanistic mathematical modeling in combination with antibiotic sensitivity assays to assess the potential impact of different resistance mechanisms during the development of PIP-TAZ resistance in a Klebsiella pneumoniae isolate expressing CTX-M-15 and SHV-1 β-lactamases. The mathematical models were used to evaluate the potential impact of several cellular changes as a sole mediator of PIP-TAZ resistance. Our semi-mechanistic model identified 2 out of the 13 inspected mechanisms as key resistance mechanisms that may independently support the observed magnitude of PIP-TAZ resistance, namely porin loss and efflux pump up-regulation. Simulation using the resulting models also suggested the possible adjustment of PIP-TAZ dose outside its commonly used 8:1 dosing ratio. The current study demonstrated how theory-based mechanistic models informed by experimental data can be used to support hypothesis generation regarding potential resistance mechanisms, which may guide subsequent experimental studies.
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Affiliation(s)
- Sebastian T Tandar
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
| | - Linda B S Aulin
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Department Clinical Pharmacy and Biochemistry, Freie Universität Berlin, Berlin, Germany
| | - Eva M J Leemkuil
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Apostolos Liakopoulos
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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Liu F, Aulin LBS, Manson ML, Krekels EHJ, van Hasselt JGC. Unraveling the Effects of Acute Inflammation on Pharmacokinetics: A Model-Based Analysis Focusing on Renal Glomerular Filtration Rate and Cytochrome P450 3A4-Mediated Metabolism. Eur J Drug Metab Pharmacokinet 2023; 48:623-631. [PMID: 37715056 PMCID: PMC10624742 DOI: 10.1007/s13318-023-00852-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/13/2023] [Indexed: 09/17/2023]
Abstract
BACKGROUND AND OBJECTIVES: Acute inflammation caused by infections or sepsis can impact pharmacokinetics. We used a model-based analysis to evaluate the effect of acute inflammation as represented by interleukin-6 (IL-6) levels on drug clearance, focusing on renal glomerular filtration rate (GFR) and cytochrome P450 3A4 (CYP3A4)-mediated metabolism. METHODS A physiologically based model incorporating renal and hepatic drug clearance was implemented. Functions correlating IL-6 levels with GFR and in vitro CYP3A4 activity were derived and incorporated into the modeling framework. We then simulated treatment scenarios for hypothetical drugs by varying the IL-6 levels, the contribution of renal and hepatic drug clearance, and protein binding. The relative change in observed area under the concentration-time curve (AUC) was computed for these scenarios. RESULTS Inflammation showed opposite effects on drug exposure for drugs eliminated via the liver and kidney, with the effect of inflammation being inversely proportional to the extraction ratio (ER). For renally cleared drugs, the relative decrease in AUC was close to 30% during severe inflammation. For CYP3A4 substrates, the relative increase in AUC could exceed 50% for low-ER drugs. Finally, the impact of inflammation-induced changes in drug clearance is smaller for drugs with a larger unbound fraction. CONCLUSION This analysis demonstrates differences in the impact of inflammation on drug clearance for different drug types. The effects of inflammation status on pharmacokinetics may explain the inter-individual variability in pharmacokinetics in critically ill patients. The proposed model-based analysis may be used to further evaluate the effect of inflammation, i.e., by incorporating the effect of inflammation on other drug-metabolizing enzymes or physiological processes.
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Affiliation(s)
- Feiyan Liu
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Linda B S Aulin
- Department of Clinical Pharmacy and Biochemistry, Institute of Pharmacy, Freie Universitaet Berlin, Berlin, Germany
| | - Martijn L Manson
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Elke H J Krekels
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - J G Coen van Hasselt
- Division of Systems Pharmacology and Pharmacy, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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Mehta K, Guo T, van der Graaf PH, van Hasselt JGC. Predictions of Bedaquiline and Pretomanid Target Attainment in Lung Lesions of Tuberculosis Patients using Translational Minimal Physiologically Based Pharmacokinetic Modeling. Clin Pharmacokinet 2023; 62:519-532. [PMID: 36802057 PMCID: PMC10042768 DOI: 10.1007/s40262-023-01217-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/19/2023] [Indexed: 02/23/2023]
Abstract
BACKGROUND Site-of-action concentrations for bedaquiline and pretomanid from tuberculosis patients are unavailable. The objective of this work was to predict bedaquiline and pretomanid site-of-action exposures using a translational minimal physiologically based pharmacokinetic (mPBPK) approach to understand the probability of target attainment (PTA). METHODS A general translational mPBPK framework for the prediction of lung and lung lesion exposure was developed and validated using pyrazinamide site-of-action data from mice and humans. We then implemented the framework for bedaquiline and pretomanid. Simulations were conducted to predict site-of-action exposures following standard bedaquiline and pretomanid, and bedaquiline once-daily dosing. Probabilities of average concentrations within lesions and lungs greater than the minimum bactericidal concentration for non-replicating (MBCNR) and replicating (MBCR) bacteria were calculated. Effects of patient-specific differences on target attainment were evaluated. RESULTS The translational modeling approach was successful in predicting pyrazinamide lung concentrations from mice to patients. We predicted that 94% and 53% of patients would attain bedaquiline average daily PK exposure within lesions (Cavg-lesion) > MBCNR during the extensive phase of bedaquiline standard (2 weeks) and once-daily (8 weeks) dosing, respectively. Less than 5% of patients were predicted to achieve Cavg-lesion > MBCNR during the continuation phase of bedaquiline or pretomanid treatment, and more than 80% of patients were predicted to achieve Cavg-lung >MBCR for all simulated dosing regimens of bedaquiline and pretomanid. CONCLUSIONS The translational mPBPK model predicted that the standard bedaquiline continuation phase and standard pretomanid dosing may not achieve optimal exposures to eradicate non-replicating bacteria in most patients.
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Affiliation(s)
- Krina Mehta
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Tingjie Guo
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Piet H. van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara, Canterbury, UK
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Vinkenoog M, Steenhuis M, Brinke AT, van Hasselt JGC, Janssen MP, van Leeuwen M, Swaneveld FH, Vrielink H, van de Watering L, Quee F, van den Hurk K, Rispens T, Hogema B, van der Schoot CE. Associations Between Symptoms, Donor Characteristics and IgG Antibody Response in 2082 COVID-19 Convalescent Plasma Donors. Front Immunol 2022; 13:821721. [PMID: 35296077 PMCID: PMC8918483 DOI: 10.3389/fimmu.2022.821721] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Accepted: 02/03/2022] [Indexed: 12/13/2022] Open
Abstract
Many studies already reported on the association between patient characteristics on the severity of COVID-19 disease outcome, but the relation with SARS-CoV-2 antibody levels is less clear. To investigate this in more detail, we performed a retrospective observational study in which we used the IgG antibody response from 11,118 longitudinal antibody measurements of 2,082 unique COVID convalescent plasma donors. COVID-19 symptoms and donor characteristics were obtained by a questionnaire. Antibody responses were modelled using a linear mixed-effects model. Our study confirms that the SARS-CoV-2 antibody response is associated with patient characteristics like body mass index and age. Antibody decay was faster in male than in female donors (average half-life of 62 versus 72 days). Most interestingly, we also found that three symptoms (headache, anosmia, nasal cold) were associated with lower peak IgG, while six other symptoms (dry cough, fatigue, diarrhoea, fever, dyspnoea, muscle weakness) were associated with higher IgG concentrations.
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Affiliation(s)
- Marieke Vinkenoog
- Department of Donor Medicine Research, Sanquin Research, Amsterdam, Netherlands
- Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
| | - Maurice Steenhuis
- Department of Immunopathology, Sanquin Research, Amsterdam, Netherlands
- Landsteiner Laboratory, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, Netherlands
| | - Anja ten Brinke
- Department of Immunopathology, Sanquin Research, Amsterdam, Netherlands
- Landsteiner Laboratory, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, Netherlands
| | - J. G. Coen van Hasselt
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, Netherlands
| | - Mart P. Janssen
- Department of Donor Medicine Research, Sanquin Research, Amsterdam, Netherlands
- Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
| | - Matthijs van Leeuwen
- Leiden Institute of Advanced Computer Science, Leiden University, Leiden, Netherlands
| | - Francis H. Swaneveld
- Department of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, Netherlands
| | - Hans Vrielink
- Department of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, Netherlands
| | - Leo van de Watering
- Department of Transfusion Medicine, Sanquin Blood Supply, Amsterdam, Netherlands
| | - Franke Quee
- Department of Donor Medicine Research, Sanquin Research, Amsterdam, Netherlands
| | - Katja van den Hurk
- Department of Donor Medicine Research, Sanquin Research, Amsterdam, Netherlands
| | - Theo Rispens
- Department of Immunopathology, Sanquin Research, Amsterdam, Netherlands
- Landsteiner Laboratory, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, Netherlands
| | - Boris Hogema
- Department of Virology, Sanquin Diagnostic Services, Amsterdam, Netherlands
| | - C. Ellen van der Schoot
- Department of Experimental Immunohematology, Sanquin Research and Landsteiner Laboratory Amsterdam University Medical Centre, Amsterdam, Netherlands
- *Correspondence: C. Ellen van der Schoot,
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Aulin LBS, Tandar ST, van Zijp T, van Ballegooie E, van der Graaf PH, Saleh MAA, Välitalo P, van Hasselt JGC. Physiologically Based Modelling Framework for Prediction of Pulmonary Pharmacokinetics of Antimicrobial Target Site Concentrations. Clin Pharmacokinet 2022; 61:1735-1748. [PMID: 36401151 PMCID: PMC9676785 DOI: 10.1007/s40262-022-01186-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/23/2022] [Indexed: 11/20/2022]
Abstract
BACKGROUND AND OBJECTIVES Prediction of antimicrobial target-site pharmacokinetics is of relevance to optimize treatment with antimicrobial agents. A physiologically based pharmacokinetic (PBPK) model framework was developed for prediction of pulmonary pharmacokinetics, including key pulmonary infection sites (i.e. the alveolar macrophages and the epithelial lining fluid). METHODS The modelling framework incorporated three lung PBPK models: a general passive permeability-limited model, a drug-specific permeability-limited model and a quantitative structure-property relationship (QSPR)-informed perfusion-limited model. We applied the modelling framework to three fluoroquinolone antibiotics. Incorporation of experimental drug-specific permeability data was found essential for accurate prediction. RESULTS In the absence of drug-specific transport data, our QSPR-based model has generic applicability. Furthermore, we evaluated the impact of drug properties and pathophysiologically related changes on pulmonary pharmacokinetics. Pulmonary pharmacokinetics were highly affected by physiological changes, causing a shift in the main route of diffusion (i.e. paracellular or transcellular). Finally, we show that lysosomal trapping can cause an overestimation of cytosolic concentrations for basic compounds when measuring drug concentrations in cell homogenate. CONCLUSION The developed lung PBPK model framework constitutes a promising tool for characterization of pulmonary exposure of systemically administrated antimicrobials.
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Affiliation(s)
- Linda B. S. Aulin
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Sebastian T. Tandar
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Torben van Zijp
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Etienne van Ballegooie
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Piet H. van der Graaf
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands ,Certara QSP, Canterbury, UK
| | - Mohammed A. A. Saleh
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Pyry Välitalo
- grid.9668.10000 0001 0726 2490University of Eastern Finland, Kuopio, Finland ,grid.490668.50000 0004 0495 5912Finnish Medicines Agency, Kuopio, Finland
| | - J. G. Coen van Hasselt
- grid.5132.50000 0001 2312 1970Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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11
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Poppe M, Clodi C, Schriefl C, Mueller M, Sunder-Plaßmann R, Reiter B, Rechenmacher M, van Os W, van Hasselt JGC, Holzer M, Herkner H, Schwameis M, Jilma B, Schoergenhofer C, Weiser C. Targeted temperature management after cardiac arrest is associated with reduced metabolism of pantoprazole - A probe drug of CYP2C19 metabolism. Biomed Pharmacother 2021; 146:112573. [PMID: 34959115 DOI: 10.1016/j.biopha.2021.112573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 11/02/2022] Open
Abstract
OBJECTIVE Targeted temperature management (TTM) is part of standard post-resuscitation care. TTM may downregulate cytochrome enzyme activity and thus impact drug metabolism. This study compared the pharmacokinetics (PK) of pantoprazole, a probe drug of CYP2C19-dependent metabolism, at different stages of TTM following cardiac arrest. METHODS This prospective controlled study was performed at the Medical University of Vienna and enrolled 16 patients following cardiac arrest. The patients completed up to three study periods (each lasting 24 h) in which plasma concentrations of pantoprazole were quantified: (P1) hypothermia (33 °C) after admission, (P2) normothermia after rewarming (36 °C, intensive care), and (P3) normothermia during recovery (normal ward, control group). PK was analysed using non-compartmental analysis and nonlinear mixed-effects modelling. RESULTS 16 patients completed periods P1 and P2; ten completed P3. The median half-life of pantoprazole was 2.4 h (quartiles: 1.8-4.8 h) in P1, 2.8 h (2.1-6.8 h, p = 0.046 vs. P1, p = 0.005 vs. P3) in P2 and 1.2 h (0.9 - 2.3 h, p = 0.007 vs. P1) in P3. A two-compartment model described the PK data best. Typical values for clearance were estimated separately for each study period, indicating 40% and 29% reductions during P1 and P2, respectively, compared to P3. The central volume of distribution was estimated separately for P2, indicating a 64% increase compared to P1 and P3. CONCLUSION CYP2C19-dependent drug metabolism is downregulated during TTM following cardiac arrest. These results may influence drug choice and dosing of similarly metabolized drugs and may be helpful for designing studies in similar clinical situations.
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Affiliation(s)
- Michael Poppe
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | - Christian Clodi
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | | | - Matthias Mueller
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | - Raute Sunder-Plaßmann
- Clinical Institute of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | - Birgit Reiter
- Clinical Institute of Laboratory Medicine, Medical University of Vienna, Vienna, Austria
| | | | - Wisse van Os
- Department of Clinical Pharmacology, Medical University of Vienna, Austria
| | | | - Michael Holzer
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | - Harald Herkner
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | - Michael Schwameis
- Department of Emergency Medicine, Medical University of Vienna, Austria
| | - Bernd Jilma
- Department of Clinical Pharmacology, Medical University of Vienna, Austria
| | | | - Christoph Weiser
- Department of Emergency Medicine, Medical University of Vienna, Austria
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12
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Mehta K, Spaink HP, Ottenhoff THM, van der Graaf PH, van Hasselt JGC. Host-directed therapies for tuberculosis: quantitative systems pharmacology approaches. Trends Pharmacol Sci 2021; 43:293-304. [PMID: 34916092 DOI: 10.1016/j.tips.2021.11.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/26/2021] [Accepted: 11/18/2021] [Indexed: 12/26/2022]
Abstract
Host-directed therapies (HDTs) that modulate host-pathogen interactions offer an innovative strategy to combat Mycobacterium tuberculosis (Mtb) infections. When combined with tuberculosis (TB) antibiotics, HDTs could contribute to improving treatment outcomes, reducing treatment duration, and preventing resistance development. Translation of the interplay of host-pathogen interactions leveraged by HDTs towards therapeutic outcomes in patients is challenging. Quantitative understanding of the multifaceted nature of the host-pathogen interactions is vital to rationally design HDT strategies. Here, we (i) provide an overview of key Mtb host-pathogen interactions as basis for HDT strategies; and (ii) discuss the components and utility of quantitative systems pharmacology (QSP) models to inform HDT strategies. QSP models can be used to identify and optimize treatment targets, to facilitate preclinical to human translation, and to design combination treatment strategies.
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Affiliation(s)
| | | | - Tom H M Ottenhoff
- Department of Infectious Diseases, Leiden University Medical Center, Leiden, The Netherlands
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13
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Zwep LB, Haakman Y, Duisters KLW, Meulman JJ, Liakopoulos A, van Hasselt JGC. Identification of antibiotic collateral sensitivity and resistance interactions in population surveillance data. JAC Antimicrob Resist 2021; 3:dlab175. [PMID: 34859221 PMCID: PMC8633787 DOI: 10.1093/jacamr/dlab175] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 10/25/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Collateral effects of antibiotic resistance occur when resistance to one antibiotic agent leads to increased resistance or increased sensitivity to a second agent, known respectively as collateral resistance (CR) and collateral sensitivity (CS). Collateral effects are relevant to limit impact of antibiotic resistance in design of antibiotic treatments. However, methods to detect antibiotic collateral effects in clinical population surveillance data of antibiotic resistance are lacking. OBJECTIVES To develop a methodology to quantify collateral effect directionality and effect size from large-scale antimicrobial resistance population surveillance data. METHODS We propose a methodology to quantify and test collateral effects in clinical surveillance data based on a conditional t-test. Our methodology was evaluated using MIC data for 419 Escherichia coli strains, containing MIC data for 20 antibiotics, which were obtained from the Pathosystems Resource Integration Center (PATRIC) database. RESULTS We demonstrate that the proposed approach identifies several antibiotic combinations that show symmetrical or non-symmetrical CR and CS. For several of these combinations, collateral effects were previously confirmed in experimental studies. We furthermore provide insight into the power of our method for multiple collateral effect sizes and MIC distributions. CONCLUSIONS Our proposed approach is of relevance as a tool for analysis of large-scale population surveillance studies to provide broad systematic identification of collateral effects related to antibiotic resistance, and is made available to the community as an R package. This method can help mapping CS and CR, which could guide combination therapy and prescribing in the future.
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Affiliation(s)
- Laura B Zwep
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Yob Haakman
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | | | | | - Apostolos Liakopoulos
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Institute of Biology Leiden, Leiden University, Leiden, The Netherlands
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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14
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Aulin LBS, Liakopoulos A, van der Graaf PH, Rozen DE, van Hasselt JGC. Design principles of collateral sensitivity-based dosing strategies. Nat Commun 2021; 12:5691. [PMID: 34584086 PMCID: PMC8479078 DOI: 10.1038/s41467-021-25927-3] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 09/10/2021] [Indexed: 02/08/2023] Open
Abstract
Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance.
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Affiliation(s)
- Linda B S Aulin
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
| | | | - Piet H van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
- Certara, Canterbury, UK
| | - Daniel E Rozen
- Institute of Biology, Leiden University, Leiden, The Netherlands
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.
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15
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Zwep LB, Duisters KLW, Jansen M, Guo T, Meulman JJ, Upadhyay PJ, van Hasselt JGC. Identification of high-dimensional omics-derived predictors for tumor growth dynamics using machine learning and pharmacometric modeling. CPT Pharmacometrics Syst Pharmacol 2021; 10:350-361. [PMID: 33792207 PMCID: PMC8099445 DOI: 10.1002/psp4.12603] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 01/07/2021] [Accepted: 02/01/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacometric modeling can capture tumor growth inhibition (TGI) dynamics and variability. These approaches do not usually consider covariates in high-dimensional settings, whereas high-dimensional molecular profiling technologies ("omics") are being increasingly considered for prediction of anticancer drug treatment response. Machine learning (ML) approaches have been applied to identify high-dimensional omics predictors for treatment outcome. Here, we aimed to combine TGI modeling and ML approaches for two distinct aims: omics-based prediction of tumor growth profiles and identification of pathways associated with treatment response and resistance. We propose a two-step approach combining ML using least absolute shrinkage and selection operator (LASSO) regression with pharmacometric modeling. We demonstrate our workflow using a previously published dataset consisting of 4706 tumor growth profiles of patient-derived xenograft (PDX) models treated with a variety of mono- and combination regimens. Pharmacometric TGI models were fit to the tumor growth profiles. The obtained empirical Bayes estimates-derived TGI parameter values were regressed using the LASSO on high-dimensional genomic copy number variation data, which contained over 20,000 variables. The predictive model was able to decrease median prediction error by 4% as compared with a model without any genomic information. A total of 74 pathways were identified as related to treatment response or resistance development by LASSO, of which part was verified by literature. In conclusion, we demonstrate how the combined use of ML and pharmacometric modeling can be used to gain pharmacological understanding in genomic factors driving variation in treatment response.
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Affiliation(s)
- Laura B. Zwep
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
- Mathematical InstituteLeiden UniversityLeidenThe Netherlands
| | | | - Martijn Jansen
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
| | - Tingjie Guo
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
- Department of Intensive Care MedicineAmsterdam UMCVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | | | - Parth J. Upadhyay
- Leiden Academic Centre for Drug ResearchLeiden UniversityLeidenThe Netherlands
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16
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Abstract
Immune checkpoint inhibitors (ICIs) have demonstrated significant clinical impact in improving overall survival of several malignancies associated with poor outcomes; however, only 20–40% of patients will show long-lasting survival. Further clarification of factors related to treatment response can support improvements in clinical outcome and guide the development of novel immune checkpoint therapies. In this article, we have provided an overview of the pharmacokinetic (PK) aspects related to current ICIs, which include target-mediated drug disposition and time-varying drug clearance. In response to the variation in treatment exposure of ICIs and the significant healthcare costs associated with these agents, arguments for both dose individualization and generalization are provided. We address important issues related to the efficacy and safety, the pharmacodynamics (PD), of ICIs, including exposure–response relationships related to clinical outcome. The unique PK and PD aspects of ICIs give rise to issues of confounding and suboptimal surrogate endpoints that complicate interpretation of exposure–response analysis. Biomarkers to identify patients benefiting from treatment with ICIs have been brought forward. However, validated biomarkers to monitor treatment response are currently lacking.
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Affiliation(s)
- Maddalena Centanni
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Dirk Jan A R Moes
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Iñaki F Trocóniz
- Pharmacometrics and Systems Pharmacology, Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy and Nutrition, University of Navarra, Pamplona, Spain
| | - Joseph Ciccolini
- SMARTc, CRCM Inserm U1068 Aix Marseille Univ and La Timone University Hospital of Marseille, Marseille, France
| | - J G Coen van Hasselt
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands.
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17
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Saleh MAA, van de Garde EMW, van Hasselt JGC. Host-response biomarkers for the diagnosis of bacterial respiratory tract infections. Clin Chem Lab Med 2019; 57:442-451. [PMID: 30183665 DOI: 10.1515/cclm-2018-0682] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Accepted: 08/03/2018] [Indexed: 12/30/2022]
Abstract
Appropriate antibiotic treatment for respiratory tract infections (RTIs) necessitates rapid and accurate diagnosis of microbial etiology, which remains challenging despite recent innovations. Several host response-based biomarkers due to infection have been suggested to allow discrimination of bacterial and non-bacterial microbial RTI etiology. This review provides an overview of clinical studies that investigated the diagnostic performance of host-response proteomic biomarkers to identify RTI microbial etiology. Procalcitonin and C-reactive protein have been studied most extensively; whereof procalcitonin has demonstrated the strongest diagnostic performance compared to other biomarkers. Proadrenomedullin, soluble triggering receptor expressed on myeloid cells-1, neopterin and pentraxin-3 need more studies to confirm their diagnostic value. For syndecan-4 and lipocalin-2 currently insufficient evidence exists. Common limitations in several of the studies were the relatively small scale setting, heterogeneous patient population and the absence of statistical power calculation.
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Affiliation(s)
- Mohammed A A Saleh
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 Leiden, The Netherlands, Phone: +31 62 452 9116
| | - Ewoudt M W van de Garde
- Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands.,Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
| | - J G Coen van Hasselt
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 Leiden, The Netherlands, Phone: +31 71 527 3266
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18
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Yu H, Janssen JM, Sawicki E, van Hasselt JGC, de Weger VA, Nuijen B, Schellens JHM, Beijnen JH, Huitema ADR. A Population Pharmacokinetic Model of Oral Docetaxel Coadministered With Ritonavir to Support Early Clinical Development. J Clin Pharmacol 2019; 60:340-350. [PMID: 31595980 DOI: 10.1002/jcph.1532] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2019] [Accepted: 09/20/2019] [Indexed: 11/08/2022]
Abstract
Oral administration of docetaxel is an attractive alternative for conventional intravenous (IV) administration. The low bioavailability of docetaxel, however, hinders the application of oral docetaxel in the clinic. The aim of the current study was to develop a population pharmacokinetic (PK) model for docetaxel and ritonavir based on the phase 1 studies and to support drug development of this combination treatment. PK data were collected from 191 patients who received IV docetaxel and different oral docetaxel formulations (drinking solution, ModraDoc001 capsule, and ModraDoc006 tablet) coadministered with ritonavir. A PK model was first developed for ritonavir. Subsequently, a semiphysiological PK model was developed for docetaxel, which incorporated the inhibition of docetaxel metabolism by ritonavir. The uninhibited intrinsic clearance of docetaxel was estimated based on data on IV docetaxel as 1980 L/h (relative standard error, 11%). Ritonavir coadministration extensively inhibited the hepatic metabolism of docetaxel to 9.3%, which resulted in up to 12-fold higher docetaxel plasma concentrations compared to oral docetaxel coadministered without ritonavir. In conclusion, a semiphysiological PK model for docetaxel and ritonavir was successfully developed. Coadministration of ritonavir resulted in increased plasma concentrations of docetaxel after administration of the oral formulations of ModraDoc. Furthermore, the oral ModraDoc formulations showed lower variability in plasma concentrations between and within patients compared to the drinking solution. Comparable exposure could be reached with the oral ModraDoc formulations compared to IV administration.
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Affiliation(s)
- Huixin Yu
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Julie M Janssen
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Emilia Sawicki
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - J G Coen van Hasselt
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Vincent A de Weger
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Bastiaan Nuijen
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
| | - Jan H M Schellens
- Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Jos H Beijnen
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands.,Utrecht Institute of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Alwin D R Huitema
- Department of Pharmacy & Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands.,Department of Clinical Pharmacy, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
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19
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Calizo RC, Bhattacharya S, van Hasselt JGC, Wei C, Wong JS, Wiener RJ, Ge X, Wong NJ, Lee JJ, Cuttitta CM, Jayaraman G, Au VH, Janssen W, Liu T, Li H, Salem F, Jaimes EA, Murphy B, Campbell KN, Azeloglu EU. Disruption of podocyte cytoskeletal biomechanics by dasatinib leads to nephrotoxicity. Nat Commun 2019; 10:2061. [PMID: 31053734 PMCID: PMC6499885 DOI: 10.1038/s41467-019-09936-x] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2018] [Accepted: 04/05/2019] [Indexed: 12/22/2022] Open
Abstract
Nephrotoxicity is a critical adverse event that leads to discontinuation of kinase inhibitor (KI) treatment. Here we show, through meta-analyses of FDA Adverse Event Reporting System, that dasatinib is associated with high risk for glomerular toxicity that is uncoupled from hypertension, suggesting a direct link between dasatinib and podocytes. We further investigate the cellular effects of dasatinib and other comparable KIs with varying risks of nephrotoxicity. Dasatinib treated podocytes show significant changes in focal adhesions, actin cytoskeleton, and morphology that are not observed with other KIs. We use phosphoproteomics and kinome profiling to identify the molecular mechanisms of dasatinib-induced injury to the actin cytoskeleton, and atomic force microscopy to quantify impairment to cellular biomechanics. Furthermore, chronic administration of dasatinib in mice causes reversible glomerular dysfunction, loss of stress fibers, and foot process effacement. We conclude that dasatinib induces nephrotoxicity through altered podocyte actin cytoskeleton, leading to injurious cellular biomechanics.
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Affiliation(s)
- Rhodora C Calizo
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Smiti Bhattacharya
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Department of Mechanical Engineering, Columbia University, New York, NY, 10027, USA
| | - J G Coen van Hasselt
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Chengguo Wei
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jenny S Wong
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Robert J Wiener
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Xuhua Ge
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Nicholas J Wong
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jia-Jye Lee
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Christina M Cuttitta
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Gomathi Jayaraman
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Vivienne H Au
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - William Janssen
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tong Liu
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers University-New Jersey Medical School, Newark, NJ, 07103, USA
| | - Hong Li
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers University-New Jersey Medical School, Newark, NJ, 07103, USA
| | - Fadi Salem
- Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Edgar A Jaimes
- Renal Service, Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA
| | - Barbara Murphy
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kirk N Campbell
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Evren U Azeloglu
- Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA. .,Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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20
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Abstract
The majority of diseases are associated with alterations in multiple molecular pathways and complex interactions at the cellular and organ levels. Single-target monotherapies therefore have intrinsic limitations with respect to their maximum therapeutic benefits. The potential of combination drug therapies has received interest for the treatment of many diseases and is well established in some areas, such as oncology. Combination drug treatments may allow us to identify synergistic drug effects, reduce adverse drug reactions, and address variability in disease characteristics between patients. Identification of combination therapies remains challenging. We discuss current state-of-the-art systems pharmacology approaches to enable rational identification of combination therapies. These approaches, which include characterization of mechanisms of disease and drug action at a systems level, can enable understanding of drug interactions at the molecular, cellular, physiological, and organismal levels. Such multiscale understanding can enable precision medicine by promoting the rational development of combination therapy at the level of individual patients for many diseases.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Pharmacological Sciences, Systems Biology Center, Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; .,Division of Systems Biomedicine and Pharmacology, Leiden Academic Center for Drug Research, Leiden University, 2333 Leiden, Netherlands;
| | - Ravi Iyengar
- Department of Pharmacological Sciences, Systems Biology Center, Mount Sinai Institute for Systems Biomedicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
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21
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Illamola SM, Sherwin CM, van Hasselt JGC. Clinical Pharmacokinetics of Amikacin in Pediatric Patients: A Comprehensive Review of Population Pharmacokinetic Analyses. Clin Pharmacokinet 2018; 57:1217-1228. [DOI: 10.1007/s40262-018-0641-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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22
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Aulin LBS, Valitalo PA, Rizk ML, Visser SAG, Rao G, van der Graaf PH, van Hasselt JGC. Validation of a Model Predicting Anti-infective Lung Penetration in the Epithelial Lining Fluid of Humans. Pharm Res 2018; 35:26. [PMID: 29368211 PMCID: PMC5783989 DOI: 10.1007/s11095-017-2336-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Accepted: 12/20/2017] [Indexed: 11/29/2022]
Affiliation(s)
- Linda B S Aulin
- Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, Netherlands
| | | | | | | | - Gauri Rao
- Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Piet H van der Graaf
- Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, Netherlands.,Certara, Canterbury, UK
| | - J G Coen van Hasselt
- Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, 2333 CC, Leiden, Netherlands.
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23
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Affiliation(s)
- Wojciech Krzyzanski
- Department of Pharmaceutical Sciences, University at Buffalo, Buffalo, NY, USA.
| | - J G Coen van Hasselt
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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24
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Ramamoorthy A, Sadler BM, van Hasselt JGC, Elassaiss-Schaap J, Kasichayanula S, Edwards AY, van der Graaf PH, Zhang L, Wagner JA. Crowdsourced Asparagus Urinary Odor Population Kinetics. CPT Pharmacometrics Syst Pharmacol 2017; 7:34-41. [PMID: 29239147 PMCID: PMC5784735 DOI: 10.1002/psp4.12264] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 09/28/2017] [Accepted: 10/19/2017] [Indexed: 01/09/2023]
Abstract
The consumption of asparagus is associated with the production of malodorous urine with considerable interindividual variability (IIV). To characterize the urinary odor kinetics after consumption of asparagus spears, we conducted a study with consenting attendees from two American Society for Clinical Pharmacology and Therapeutics (ASCPT) meetings. Subjects were randomized to eat a specific number of asparagus spears, and then asked to report their urinary odor perception. Eighty‐seven subjects were included in the final analysis. A mixed effect proportional odds model was developed that adequately characterized the dose‐response relationship. We estimated the half‐life of the asparagus effect on malodorous urine to be 4.7 hours (relative standard error (RSE) = 13.2%), and identified a dose‐response slope term with good precision (24.3%). Age was found as the predictor of IIV in slope estimates. This study design and tools can be used as a demonstration “crowdsourcing” project for studying population kinetics in organizational and educational settings.
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Affiliation(s)
- Anuradha Ramamoorthy
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - Brian M Sadler
- Pharmacokinetics, Pharmacodynamics, Modeling & Simulation, ICON Plc, Cary, North Carolina, USA
| | - J G Coen van Hasselt
- Cluster Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Jeroen Elassaiss-Schaap
- Cluster Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,PD-Value BV, Houten, The Netherlands
| | | | - Alena Y Edwards
- Pharmacokinetics, Pharmacodynamics, Modeling & Simulation, ICON Plc, Marlow, UK
| | - Piet H van der Graaf
- Cluster Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands.,Certara QSP, Canterbury, UK
| | - Lei Zhang
- Office of Clinical Pharmacology, Office of Translational Sciences, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, Maryland, USA
| | - John A Wagner
- Takeda Pharmaceuticals International Co, Cambridge, Massachusetts, USA
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25
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Antunes NDJ, van Dijkman SC, Lanchote VL, Wichert-Ana L, Coelho EB, Alexandre Junior V, Takayanagui OM, Tozatto E, van Hasselt JGC, Della Pasqua O. Population pharmacokinetics of oxcarbazepine and its metabolite 10-hydroxycarbazepine in healthy subjects. Eur J Pharm Sci 2017; 109S:S116-S123. [PMID: 28528287 DOI: 10.1016/j.ejps.2017.05.034] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2017] [Accepted: 05/15/2017] [Indexed: 01/11/2023]
Abstract
Oxcarbazepine is indicated for the treatment of partial or generalised tonic-clonic seizures. Most of the absorbed oxcarbazepine is converted into its active metabolite, 10-hydroxycarbazepine (MHD), which can exist as R-(-)- and S-(+)-MHD enantiomers. Here we describe the influence of the P-glycoprotein (P-gp) inhibitor verapamil, on the disposition of oxcarbazepine and MHD enantiomers, both of which are P-gp substrates. Healthy subjects (n=12) were randomised to oxcarbazepine or oxcarbazepine combined with verapamil at doses of 300mg b.i.d. and 80mg t.i.d., respectively. Blood samples (n=185) were collected over a period of 12h post oxcarbazepine dose. An integrated PK model was developed using nonlinear mixed effects modelling using a meta-analytical approach. The pharmacokinetics of oxcarbazepine was described by a two-compartment model with absorption transit compartments and first-order elimination. The concentration-time profiles of both MHD enantiomers were characterised by a one-compartment distribution model. Clearance estimates (95% CI) were 84.9L/h (69.5-100.3) for oxcarbazepine and 2.0L/h (1.9-2.1) for both MHD enantiomers. The volume of distribution was much larger for oxcarbazepine (131L (97-165)) as compared to R-(-)- and S-(+)-MHD (23.6L (14.4-32.8) vs. 31.7L (22.5-40.9), respectively). Co-administration of verapamil resulted in a modest increase of the apparent bioavailability of oxcarbazepine by 12% (10-28), but did not affect parent or metabolite clearances. Despite the evidence of comparable systemic levels of OXC and MHD following administration of verapamil, differences in brain exposure to both moieties cannot be excluded after P-glycoprotein inhibition.
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Affiliation(s)
- Natalicia de Jesus Antunes
- Department of Clinical Chemistry and Toxicology, Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Brazil
| | - Sven C van Dijkman
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Vera Lucia Lanchote
- Department of Clinical Chemistry and Toxicology, Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Brazil
| | - Lauro Wichert-Ana
- Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Brazil
| | - Eduardo Barbosa Coelho
- Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Brazil
| | - Veriano Alexandre Junior
- Department of Neurobehavioural Sciences, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Brazil
| | | | - Eduardo Tozatto
- Department of Clinical Chemistry and Toxicology, Faculty of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Brazil
| | - J G Coen van Hasselt
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Oscar Della Pasqua
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands; Clinical Pharmacology & Therapeutic Group, School of Life and Medical Sciences, University College London, London, UK.
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26
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Krekels EHJ, van Hasselt JGC, van den Anker JN, Allegaert K, Tibboel D, Knibbe CAJ. Evidence-based drug treatment for special patient populations through model-based approaches. Eur J Pharm Sci 2017; 109S:S22-S26. [PMID: 28502674 DOI: 10.1016/j.ejps.2017.05.022] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 05/11/2017] [Indexed: 10/19/2022]
Abstract
The majority of marketed drugs remain understudied in some patient populations such as pregnant women, paediatrics, the obese, the critically-ill, and the elderly. As a consequence, currently used dosing regimens may not assure optimal efficacy or minimal toxicity in these patients. Given the vulnerability of some subpopulations and the challenges and costs of performing clinical studies in these populations, cutting-edge approaches are needed to effectively develop evidence-based and individualized drug dosing regimens. Five key issues are presented that are essential to support and expedite the development of drug dosing regimens in these populations using model-based approaches: 1) model development combined with proper validation procedures to extract as much valid information from available study data as possible, with limited burden to patients and costs; 2) integration of existing data and the use of prior pharmacological and physiological knowledge in study design and data analysis, to further develop knowledge and avoid unnecessary or unrealistic (large) studies in vulnerable populations; 3) clinical proof-of-principle in a prospective evaluation of a developed drug dosing regimen, to confirm that a newly proposed regimen indeed results in the desired outcomes in terms of drug concentrations, efficacy, and/or safety; 4) pharmacodynamics studies in addition to pharmacokinetics studies for drugs for which a difference in disease progression and/or in exposure-response relation is anticipated compared to the reference population; 5) additional efforts to implement developed dosing regimens in clinical practice once drug pharmacokinetics and pharmacodynamics have been characterized in special patient populations. The latter remains an important bottleneck, but this is essential to truly realize evidence-based and individualized drug dosing for special patient populations. As all tools required for this purpose are available, we have the moral and societal obligation to make safe and effective pharmacotherapy available for these patients too.
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Affiliation(s)
- Elke H J Krekels
- Leiden Academic Center for Drug Research, Systems Pharmacology Cluster, Division of Pharmacology, Leiden University, Leiden, The Netherlands.
| | - J G Coen van Hasselt
- Leiden Academic Center for Drug Research, Systems Pharmacology Cluster, Division of Pharmacology, Leiden University, Leiden, The Netherlands; Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John N van den Anker
- Intensive Care and Department of Pediatric Surgery, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands; Division of Clinical Pharmacology, Children's National Health System, Washington, DC, USA; Division of Pediatric Pharmacology and Pharmacometrics, University of Basel Children's Hospital, Basel, Switzerland
| | - Karel Allegaert
- Intensive Care and Department of Pediatric Surgery, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands; Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Dick Tibboel
- Intensive Care and Department of Pediatric Surgery, Erasmus MC Sophia Children's Hospital, Rotterdam, The Netherlands
| | - Catherijne A J Knibbe
- Leiden Academic Center for Drug Research, Systems Pharmacology Cluster, Division of Pharmacology, Leiden University, Leiden, The Netherlands; Department of Clinical Pharmacy, St. Antonius Hospital, Nieuwegein, The Netherlands
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27
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Illamola SM, Colom H, van Hasselt JGC. Evaluating renal function and age as predictors of amikacin clearance in neonates: model-based analysis and optimal dosing strategies. Br J Clin Pharmacol 2016; 82:793-805. [PMID: 27198625 DOI: 10.1111/bcp.13016] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2015] [Revised: 04/30/2016] [Accepted: 05/15/2016] [Indexed: 11/29/2022] Open
Abstract
AIMS We aimed to compare the performance of renal function and age as predictors of inter-individual variability (IIV) in clearance of amikacin in neonates through parallel development of population pharmacokinetic (PK) models and their associated impact on optimal dosing regimens. METHODS Amikacin concentrations were retrospectively collected for 149 neonates receiving amikacin (post-natal age (PNA) between 4-89 days). Two population PK models were developed in parallel, considering at least as predictors current body weight (WT), in combination with either creatinine clearance (CLcr ) or age descriptors. Using stochastic simulations for both renal function or age-based dosing, we identified optimal dosing strategies that were based on attainment of optimal peak- (PCC) and trough target concentration coverage (TCC) windows associated with efficacy and toxicity. RESULTS The CLcr and age-based population PK models both included current body weight (WT) on CL, central distribution volume and intercompartmental clearance, in combination with either CLcr or PNA as predictors for IIV of clearance (CL). The WT-CLcr model explained 6.9% more IIV in CL compared with the WT-PNA model. Both models successfully described an external dataset (n = 53) of amikacin PK. The simulation analysis of optimal dose regimens suggested similar performance of either CLcr or PNA based dosing. CONCLUSION CLcr predicted more IIV in CL, but did not translate into clinically relevant improvements of target concentrations. Our optimized dose regimens can be considered for further evaluation to optimize initial treatment with amikacin.
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Affiliation(s)
- Sílvia M Illamola
- Biochemistry Service, Hospital Universitari Vall d'Hebron, Universitat Autònoma de Barcelona, Spain.,Biochemistry Service, Hôpital Européen Georges Pompidou, Paris, France.,Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, Universitat de Barcelona, Spain
| | - Helena Colom
- Department of Pharmacy and Pharmaceutical Technology, School of Pharmacy, Universitat de Barcelona, Spain
| | - J G Coen van Hasselt
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, the Netherlands
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28
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Jacobs BAW, Deenen MJ, Pluim D, van Hasselt JGC, Krähenbühl MD, van Geel RMJM, de Vries N, Rosing H, Meulendijks D, Burylo AM, Cats A, Beijnen JH, Huitema ADR, Schellens JHM. Pronounced between-subject and circadian variability in thymidylate synthase and dihydropyrimidine dehydrogenase enzyme activity in human volunteers. Br J Clin Pharmacol 2016; 82:706-16. [PMID: 27161955 DOI: 10.1111/bcp.13007] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2016] [Revised: 04/25/2016] [Accepted: 05/08/2016] [Indexed: 01/04/2023] Open
Abstract
AIMS The enzymatic activity of dihydropyrimidine dehydrogenase (DPD) and thymidylate synthase (TS) are important for the tolerability and efficacy of the fluoropyrimidine drugs. In the present study, we explored between-subject variability (BSV) and circadian rhythmicity in DPD and TS activity in human volunteers. METHODS The BSVs in DPD activity (n = 20) in peripheral blood mononuclear cells (PBMCs) and in plasma, measured by means of the dihydrouracil (DHU) and uracil (U) plasma levels and DHU : U ratio (n = 40), and TS activity in PBMCs (n = 19), were examined. Samples were collected every 4 h throughout 1 day for assessment of circadian rhythmicity in DPD and TS activity in PBMCs (n = 12) and DHU : U plasma ratios (n = 23). In addition, the effects of genetic polymorphisms and gene expression on DPD and TS activity were explored. RESULTS Population mean (± standard deviation) DPD activity in PBMCs and DHU : U plasma ratio were 9.2 (±2.1) nmol mg(-1) h(-1) and 10.6 (±2.4), respectively. Individual TS activity in PBMCs ranged from 0.024 nmol mg(-1) h(-1) to 0.596 nmol mg(-1) h(-1) . Circadian rhythmicity was demonstrated for all phenotype markers. Between 00:30 h and 02:00 h, DPD activity in PBMCs peaked, while the DHU : U plasma ratio and TS activity in PBMCs showed trough activity. Peak-to-trough ratios for DPD and TS activity in PBMCs were 1.69 and 1.62, respectively. For the DHU : U plasma ratio, the peak-to-trough ratio was 1.43. CONCLUSIONS BSV and circadian variability in DPD and TS activity were demonstrated. Circadian rhythmicity in DPD might be tissue dependent. The results suggested an influence of circadian rhythms on phenotype-guided fluoropyrimidine dosing and supported implications for chronotherapy with high-dose fluoropyrimidine administration during the night.
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Affiliation(s)
- Bart A W Jacobs
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Maarten J Deenen
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Dick Pluim
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - J G Coen van Hasselt
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Martin D Krähenbühl
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Robin M J M van Geel
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Niels de Vries
- Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Hilde Rosing
- Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Didier Meulendijks
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Artur M Burylo
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Annemieke Cats
- Department of Gastroenterology & Hepatology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jos H Beijnen
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
| | - Alwin D R Huitema
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Jan H M Schellens
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.,Department of Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands
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29
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van Hasselt JGC, Rizk ML, Lala M, Chavez-Eng C, Visser SAG, Kerbusch T, Danhof M, Rao G, van der Graaf PH. Pooled population pharmacokinetic model of imipenem in plasma and the lung epithelial lining fluid. Br J Clin Pharmacol 2016; 81:1113-23. [PMID: 26852277 DOI: 10.1111/bcp.12901] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2015] [Revised: 01/08/2016] [Accepted: 02/02/2016] [Indexed: 01/01/2023] Open
Abstract
AIMS Several clinical trials have confirmed the therapeutic benefit of imipenem for treatment of lung infections. There is however no knowledge of the penetration of imipenem into the lung epithelial lining fluid (ELF), the site of action relevant for lung infections. Furthermore, although the plasma pharmacokinetics (PK) of imipenem has been widely studied, most studies have been based on selected patient groups. The aim of this analysis was to characterize imipenem plasma PK across populations and to quantify imipenem ELF penetration. METHODS A population model for imipenem plasma PK was developed using data obtained from healthy volunteers, elderly subjects and subjects with renal impairment, in order to identify predictors for inter-individual variability (IIV) of imipenem PK. Subsequently, a clinical study which measured plasma and ELF concentrations of imipenem was included in order to quantify lung penetration. RESULTS A two compartmental model best described the plasma PK of imipenem. Creatinine clearance and body weight were included as subject characteristics predictive for IIV on clearance. Typical estimates for clearance, central and peripheral volume, and inter-compartmental clearance were 11.5 l h(-1) , 9.37 l, 6.41 l, 13.7 l h(-1) , respectively (relative standard error (RSE) <8%). The distribution of imipenem into ELF was described using a time-independent penetration coefficient of 0.44 (RSE 14%). CONCLUSION The identified lung penetration coefficient confirms the clinical relevance of imipenem for treatment of lung infections, while the population PK model provided insights into predictors of IIV for imipenem PK and may be of relevance to support dose optimization in various subject groups.
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Affiliation(s)
- J G Coen van Hasselt
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | | | | | | | | | | | - Meindert Danhof
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Gauri Rao
- University at Buffalo, Buffalo, New York, USA
| | - Piet H van der Graaf
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
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30
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Yu H, Steeghs N, Kloth JSL, de Wit D, van Hasselt JGC, van Erp NP, Beijnen JH, Schellens JHM, Mathijssen RHJ, Huitema ADR. Integrated semi-physiological pharmacokinetic model for both sunitinib and its active metabolite SU12662. Br J Clin Pharmacol 2016; 79:809-19. [PMID: 25393890 DOI: 10.1111/bcp.12550] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2014] [Accepted: 11/07/2014] [Indexed: 12/31/2022] Open
Abstract
AIMS Previously published pharmacokinetic (PK) models for sunitinib and its active metabolite SU12662 were based on a limited dataset or lacked important elements such as correlations between sunitinib and its metabolite. The current study aimed to develop an improved PK model that circumvented these limitations and to prove the utility of the PK model in treatment optimization in clinical practice. METHODS One thousand two hundred and five plasma samples from 70 cancer patients were collected from three PK studies with sunitinib and SU12662. A semi-physiological PK model for sunitinib and SU12662 was developed incorporating pre-systemic metabolism using non-linear mixed effects modelling (nonmem). Allometric scaling based on body weight was applied. The final model was used for simulation of the PK of different treatment regimens. RESULTS Sunitinib and SU12662 PK were best described by a one and two compartment model, respectively. Introduction of pre-systemic formation of SU12662 strongly improved model fit, compared with solely systemic metabolism. The clearance of sunitinib and SU12662 was estimated at 35.7 (relative standard error (RSE) 5.7%) l h(-1) and 17.1 (RSE 7.4%) l h(-1), respectively for 70 kg patients. Correlation coefficients were estimated between inter-individual variability of both clearances, both volumes of distribution and between clearance and volume of distribution of SU12662 as 0.53, 0.48 and 0.45, respectively. Simulation of the PK model predicted correctly the ratio of patients who did not reach proposed PK targets for efficacy. CONCLUSIONS A semi-physiological PK model for sunitinib and SU12662 in cancer patients was presented including pre-systemic metabolism. The model was superior to previous PK models in many aspects.
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Affiliation(s)
- Huixin Yu
- Department of Pharmacy and Pharmacology, Netherlands Cancer Institute-Antoni van Leeuwenhoek, Amsterdam, The Netherlands
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31
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Välitalo PAJ, Griffioen K, Rizk ML, Visser SAG, Danhof M, Rao G, van der Graaf PH, van Hasselt JGC. Structure-Based Prediction of Anti-infective Drug Concentrations in the Human Lung Epithelial Lining Fluid. Pharm Res 2015; 33:856-67. [DOI: 10.1007/s11095-015-1832-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Accepted: 11/18/2015] [Indexed: 10/22/2022]
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32
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van Hasselt JGC, van der Graaf PH. Towards integrative systems pharmacology models in oncology drug development. Drug Discov Today Technol 2015; 15:1-8. [PMID: 26464083 DOI: 10.1016/j.ddtec.2015.06.004] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Revised: 05/31/2015] [Accepted: 06/12/2015] [Indexed: 02/02/2023]
Abstract
Quantitative systems pharmacology (QSP) modeling represents an emerging area of value to further streamline knowledge integration and to better inform decision making processes in drug development. QSP models reside at the interface between systems biology models and pharmacological models, yet their concrete implementation still needs to be established further. This review outlines key modeling techniques in both of these areas and to subsequently discuss challenges and opportunities for further integration, in oncology drug development.
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Affiliation(s)
- J G Coen van Hasselt
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden, The Netherlands.
| | - Piet H van der Graaf
- Division of Pharmacology, Cluster Systems Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Einsteinweg 55, Leiden, The Netherlands.
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33
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van Hasselt JGC, van Eijkelenburg NKA, Beijnen JH, Schellens JHM, Huitema ADR. Design of a drug-drug interaction study of vincristine with azole antifungals in pediatric cancer patients using clinical trial simulation. Pediatr Blood Cancer 2014; 61:2223-9. [PMID: 25175364 DOI: 10.1002/pbc.25198] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Accepted: 07/01/2014] [Indexed: 01/28/2023]
Abstract
BACKGROUND The aim of the current work was to perform a clinical trial simulation (CTS) analysis to optimize a drug-drug interaction (DDI) study of vincristine in children who also received azole antifungals, taking into account challenges of conducting clinical trials in this population, and, to provide a motivating example of the application of CTS in the design of pediatric oncology clinical trials. PROCEDURE A pharmacokinetic (PK) model for vincristine in children was used to simulate concentration-time profiles. A continuous model for body surface area versus age was defined based on pediatric growth curves. Informative sampling time windows were derived using D-optimal design. The CTS framework was used to different magnitudes of clearance inhibition (10%, 25%, or 40%), sample size (30-500), the impact of missing samples or sampling occasions, and the age distribution, on the power to detect a significant inhibition effect, and in addition, the relative estimation error (REE) of the interaction effect. RESULTS A minimum group specific sample size of 38 patients with a total sample size of 150 patients was required to detect a clearance inhibition effect of 40% with 80% power, while in the case of a lower effect of clearance inhibition, a substantially larger sample size was required. However, for the majority of re-estimated drug effects, the inhibition effect could be estimated precisely (REE < 25%) in even smaller sample sizes and with lower effect sizes. CONCLUSION This work demonstrated the utility of CTS for the evaluation of PK clinical trial designs in the pediatric oncology population.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands; Department of Pharmacy & Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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34
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van Hasselt JGC, Gupta A, Hussein Z, Beijnen JH, Schellens JHM, Huitema ADR. Population pharmacokinetic-pharmacodynamic analysis for eribulin mesilate-associated neutropenia. Br J Clin Pharmacol 2014; 76:412-24. [PMID: 23601153 DOI: 10.1111/bcp.12143] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Accepted: 03/26/2013] [Indexed: 11/30/2022] Open
Abstract
AIMS Eribulin mesilate is an inhibitor of microtubule dynamics that is approved for the treatment of late-stage metastatic breast cancer. Neutropenia is one of the major dose-limiting adverse effects of eribulin. The objective of this analysis was to develop a population pharmacokinetic-pharmacodynamic model for eribulin-associated neutropenia. METHODS A combined data set of 12 phase I, II and III studies for eribulin mesilate was analysed. The population pharmacokinetics of eribulin was described using a previously developed model. The relationship between eribulin pharmacokinetic and neutropenia was described using a semi-physiological lifespan model for haematological toxicity. Patient characteristics predictive of increased sensitivity to develop neutropenia were evaluated using a simulation framework. RESULTS Absolute neutrophil counts were available from 1579 patients. In the final covariate model, the baseline neutrophil count (ANC0) was estimated to be 4.03 × 10(9) neutrophils l(-1) [relative standard error (RSE) 1.2%], with interindividual variability (IIV, 37.3 coefficient of variation % [CV%]). The mean transition time was estimated to be 109 h (RSE 1.8%, IIV 13.9CV%), the feedback constant (γ) was estimated to be 0.216 (RSE 1.4%, IIV 12.2CV%), and the linear drug effect coefficient (SLOPE) was estimated to be 0.0451 μg l(-1) (RSE 3.2%, IIV 54CV%). Albumin, aspartate transaminase and receival of granulocyte colony-stimulating factor (G-CSF) were identified as significant covariates on SLOPE, and albumin, bilirubin, G-CSF, alkaline phosphatase and lactate dehydrogenase were identified as significant covariates on mean transition time. CONCLUSIONS The developed model can be applied to investigate optimal treatment strategies quantitatively across different patient groups with respect to neutropenia. Albumin was identified as the most clinically important covariate predictive of interindividual variability in the neutropenia time course.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands; Department of Pharmacy & Pharmacology, Slotervaart Hospital/The Netherlands Cancer Institute, Amsterdam, The Netherlands
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van Hasselt JGC, Andrew MA, Hebert MF, Tarning J, Vicini P, Mattison DR. The status of pharmacometrics in pregnancy: highlights from the 3(rd) American conference on pharmacometrics. Br J Clin Pharmacol 2013; 74:932-9. [PMID: 22452385 PMCID: PMC3522806 DOI: 10.1111/j.1365-2125.2012.04280.x] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Physiological changes during pregnancy may alter drug pharmacokinetics. Therefore, mechanistic understanding of these changes and, ultimately, clinical studies in pregnant women are necessary to determine if and how dosing regimens should be adjusted. Because of the typically limited number of patients who can be recruited in this patient group, efficient design and analysis of these studies is of special relevance. This paper is a summary of a conference session organized at the American Conference of Pharmacometrics in April 2011, around the topic of applying pharmacometric methodology to this important problem. The discussion included both design and analysis of clinical studies during pregnancy and in silico predictions. An overview of different pharmacometric methods relevant to this subject was given. The impact of pharmacometrics was illustrated using a range of case examples of studies around pregnancy.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Clinical Pharmacology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
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van Hasselt JGC, Schellens JHM, Mac Gillavry MR, Beijnen JH, Huitema ADR. Model-based evaluation and optimization of cardiac monitoring protocols for adjuvant treatment of breast cancer with trastuzumab. Pharm Res 2012; 29:3499-511. [PMID: 22907417 DOI: 10.1007/s11095-012-0845-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2012] [Accepted: 07/30/2012] [Indexed: 01/03/2023]
Abstract
PURPOSE Trastuzumab treatment is associated with occurrence of cardiac toxicity, for which monitoring of the left ventricular ejection fraction (LVEF) is indicated. The performance of the currently used monitoring protocol as defined in the summary of product characteristics (SPC) is however unknown. The objective of this analysis was to develop a model-based framework for evaluation and optimization of cardiac monitoring strategies. METHODS The model-based framework comprised a previously developed exposure-response model for trastuzumab induced changes in LVEF, and a protocol-execution model that allowed incorporation of treatment interventions as described by a monitoring protocol. Metrics for evaluation of toxicity, dose intensity and monitoring burden were defined to allow evaluation and optimization of cardiac monitoring protocols. RESULTS The success of a protocol-defined dose reduction was improved from 40% for the SPC-based protocol, to 79% for a scoring-based protocol, thereby decreasing the observed severity of cardiotoxicity. Including adaptation based on risk-profile allowed reduction of the mean number of LVEF measurements by 19%. CONCLUSIONS This model-based evaluation approach enabled evaluation and optimization of cardiac monitoring protocols that would be difficult to evaluate in a clinical setting. This approach can potentially be applied for other drugs that use repeated evaluation of continuous biomarkers for toxicity.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Clinical Pharmacology, The Netherlands Cancer Institute, Amsterdam, The Netherlands.
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van Hasselt JGC, Green B, Morrish GA. Leveraging physiological data from literature into a pharmacokinetic model to support informative clinical study design in pregnant women. Pharm Res 2012; 29:1609-17. [PMID: 22246291 DOI: 10.1007/s11095-012-0671-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2011] [Accepted: 01/03/2012] [Indexed: 12/12/2022]
Abstract
PURPOSE Physiological changes during pregnancy can effect pharmacokinetic (PK) parameters, which may lead to altered dose requirements. We aimed to leverage literature-based physiological changes during pregnancy into a PK model and compare its performance to a published reference model in pregnant women and to use the literature-based model to determine informative PK sampling times for a clinical study that aims to quantify the PK of enoxaparin throughout pregnancy. METHODS Changes in total body water (BW) and creatinine clearance (CRCL) during pregnancy were described using regression models. BW and CRCL were linked to a PK model of enoxaparin in non-pregnant women. Performance of the literature-based PK model was compared to a previously published empirical reference model. D-optimal sampling times were determined and evaluated for literature-based and reference models. RESULTS The literature-based model adequately predicted anti-Xa plasma concentrations when compared to reference model predictions. An informative sampling design was successfully developed, with parameters expected with good precision (RSE < 36.4%). CONCLUSION A literature-based model describing enoxaparin PK during pregnancy was developed and evaluated. The modelling framework could be used to support development of informative designs in pregnancy when prior models are unavailable.
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Affiliation(s)
- J G Coen van Hasselt
- Department of Pharmacy and Pharmacology, Netherlands Cancer Institute/Slotervaart Hospital, Louwesweg 6, PO Box 90440, 1006 BK, Amsterdam, The Netherlands.
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van Hasselt JGC, van den Heuvel MM, Schellens JHM, Beijnen JH, Brandsma D, Huitema ADR. Severe cannabinoid intoxication in a patient with non-small-cell lung cancer. J Palliat Care 2012; 28:60-61. [PMID: 22582474] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Affiliation(s)
- J G Coen van Hasselt
- Department of Clinical Pharmacology, Netherlands Cancer Institute, and Department of Pharmacy and Pharmacology, Slotervaart Hospital, Louwesweg 6, P.O. Box 90440, 1006 BK Amsterdam, Netherlands.
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Liem-Moolenaar M, de Boer P, Timmers M, Schoemaker RC, van Hasselt JGC, Schmidt S, van Gerven JMA. Pharmacokinetic-pharmacodynamic relationships of central nervous system effects of scopolamine in healthy subjects. Br J Clin Pharmacol 2011; 71:886-98. [PMID: 21306419 DOI: 10.1111/j.1365-2125.2011.03936.x] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT • The cholinergic system is important for different central nervous system functions, including memory, learning and attention. Scopolamine, a centrally active muscarinic antagonist, has been used to model dementia and to demonstrate the pharmacological effects of cholinergic drugs, but for most effects the concentration-effect relationships are unknown. WHAT THIS STUDY ADDS • We determined the pharmacokinetic-pharmacodynamic relationships of scopolamine using a multidimensional central nervous system test battery in a large group of healthy volunteers. The results suggested there are various functional cholinergic systems with different pharmacological characteristics, which can be used to study the effects of drugs that directly or indirectly modify cholinergic systems. The design of such studies should take the different concentration-effect relationships into account. AIM(S) Although scopolamine is a frequently used memory impairment model, the relationships between exposure and corresponding central nervous system (CNS) effects are mostly unknown. The aim of our study was to characterize these using pharmacokinetic-pharmacodynamic (PK-PD) modelling. METHODS In two double-blind, placebo-controlled, four-way crossover studies, 0.5-mg scopolamine was administered i.v. to 90 healthy male subjects. PK and PD/safety measures were monitored pre-dose and up to 8.5 h after administration. PK-PD relationships were modelled using non-linear mixed-effect modelling. RESULTS Most PD responses following scopolamine administration in 85 subjects differed significantly from placebo. As PD measures lagged behind the plasma PK profile, PK-PD relationships were modelled using an effect compartment and arbitrarily categorized according to their equilibration half-lives (t(1/2) k(eo) ; hysteresis measure). t(1/2) k(eo) for heart rate was 17 min, saccadic eye movements and adaptive tracking 1-1.5 h, body sway, smooth pursuit, visual analogue scales alertness and psychedelic 2.5-3.5 h, pupil size, finger tapping and visual analogue scales feeling high more than 8 h. CONCLUSIONS Scopolamine affected different CNS functions in a concentration-dependent manner, which based on their distinct PK-PD characteristics seemed to reflect multiple distinct functional pathways of the cholinergic system. All PD effects showed considerable albeit variable delays compared with plasma concentrations. The t(1/2) k(eo) of the central effects was longer than of the peripheral effects on heart rate, which at least partly reflects the long CNS retention of scopolamine, but possibly also the triggering of independent secondary mechanisms. PK-PD analysis can optimize scopolamine administration regimens for future research and give insight into the physiology and pharmacology of human cholinergic systems.
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