Population pharmacokinetics of liposomal amphotericin B in pediatric patients with malignant diseases
Open accessAbstract
A population pharmacokinetic model of liposomal amphotericin B (L-AmB) in pediatric patients with malignant diseases was developed and evaluated. Blood samples were collected from 39 pediatric oncology patients who received multiple doses of L-AmB with a dose range from 0.8 to 5.9 mg/kg of body weight/day. The patient cohort had an average age of 7 years (range, 0.2 to 17 years) and weighed an average of 28.8 ± 19.8 kg. Population pharmacokinetic analyses were performed with NONMEM software. Pharmacokinetic parameters, interindividual variability (IIV), between-occasion variability (BOV), and intraindividual variability were estimated. The influence of patient characteristics on the pharmacokinetics of L-AmB was explored. The final population pharmacokinetic model was evaluated by using a bootstrap sampling technique. The L-AmB plasma concentration-time data was described by a two-compartment pharmacokinetic model with zero-order input and first-order elimination. The population mean estimates of clearance (CL) and volume of distribution in the central compartment ( V 1 ) were 0.44 liters/h and 3.12 liters, respectively, and exhibited IIV (CL, 10%) and significant BOV (CL, 46% and V 1 , 56%). The covariate models were CL (liters/h) = 0.44 · e 0.0152 · (WT − 21 ) and V 1 (liters) = 3.12 · e 0.0241 · (WT − 21) , where WT is the patient's body weight (kg) centered on the study population cohort median of 21 kg. Model evaluation by the bootstrap procedure indicated that the full pharmacokinetic model was robust and parameter estimates were accurate. In conclusion, the pharmacokinetics of L-AmB in pediatric oncology patients were adequately described by the developed population model. The model has been evaluated and can be used in the design of rational dosing strategies for L-AmB antifungal therapy in this special population.
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Among 39 pediatric patients, those with liposomal amphotericin B Cmax/MIC >40 were more likely to achieve a complete or partial response.
“Among 39 patients, those with liposomal amphotericin B C max /MIC >40 were more likely to achieve a complete or partial response.”
From Fungal Sepsis: Optimizing Antifungal Therapy in the Critical Care Setting (2011) · cites this paper as [135]
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- Authors
- Hong, Y., Shaw, P. J., Nath, C. E., Yadav, S. P., Stephen, K. R., Earl, J. W., & McLachlan, A. J.
- Affiliations
- The University of Sydney (AU)
- Department of Oncology
- Children's Hospital at Westmead (AU)
- Corresponding author
- McLachlan, Andrew J.
- Venue
- Antimicrobial Agents and Chemotherapy
- Publisher
- American Society for Microbiology
- Published
- 2006-03
- Volume
- 50
- Issue
- 3
- Pages
- 935-942
- ISSN
- 0066-4804 (ISSN-L)
- 1098-6596
- PMC
- PMC1426421
- OpenAlex
- W2146085427
- Cited by
- 102
- References
- 27
- Citations by year
- 2026: 3 · 2025: 2 · 2024: 2 · 2023: 3 · 2022: 5 · 2021: 7 · 2020: 9 · 2019: 5 · 2018: 5 · 2017: 4 · 2016: 8 · 2015: 4 · 2014: 8 · 2013: 2 · 2012: 6
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Antimicrobial Agents and Chemotherapy (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Health Sciences › Medicine › Infectious Diseases › Antifungal resistance and susceptibility
- Health Sciences › Medicine › Pharmacology › Antibiotics Pharmacokinetics and Efficacy
- Keywords
- liposomal amphotericin B, population pharmacokinetics, pediatric oncology patients, childhood cancer, two-compartment model, interindividual variability, covariate modeling, body weight, clearance, volume of distribution, antifungal therapy, dosing regimen
- MeSH terms
- Adolescent, Amphotericin B, Antifungal Agents, Body Surface Area, Body Weight, Child, Child, Preschool, Female, Humans, Infant, Liposomes, Male, Models, Biological, Neoplasms, Software, Models, Statistical, Cohort Studies
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