Population Pharmacokinetics of Anticancer Agents
Summary
Population pharmacokinetics examines the variability in drug concentrations across individuals receiving anticancer therapies, with the aim of defining dosage strategies that maximise efficacy while minimising toxicity. By analysing data from diverse patient cohorts—often incorporating sparse sampling—mixed-effects models characterise key parameters such as clearance, volume of distribution and absorption rates. Covariates including age, body composition, organ function and genetic polymorphisms are integrated to explain inter-individual differences. These insights underpin therapeutic drug monitoring and the development of adaptive dosing regimens for agents such as taxanes, platinum compounds and targeted therapies. The global relevance lies in tailoring treatments to patient subgroups, informing dose adjustments in vulnerable populations and guiding early-phase clinical trials. Through population pharmacokinetics, clinicians and researchers can predict exposure–response relationships, support regulatory decision-making and accelerate model-informed drug development, ultimately advancing personalised oncology care.
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Population Pharmacokinetics of Anticancer Agents publication trend
The graph below shows the total number of articles in population pharmacokinetics of anticancer agents across all publications each year (not limited to Nature Index journals).
Technical terms
Population pharmacokinetics: The study of drug concentration variability across a patient population, using statistical models to estimate typical values and sources of variability for pharmacokinetic parameters.
Area under the curve (AUC): The integral of drug concentration over time, representing overall exposure to the agent.
Non-linear mixed-effects model: A statistical framework combining fixed effects (typical parameter values) and random effects (inter-individual variability) to analyse pharmacokinetic data.
Covariate: A patient-specific characteristic (for example, weight, organ function or genotype) that is incorporated into a pharmacokinetic model to explain variability in drug handling.
References
- Oral docetaxel plus encequidar – A pharmacokinetic model and evaluation against IV docetaxel. Journal of Pharmacokinetics and Pharmacodynamics (2024).
- A sub-pharmacological test dose does not predict individual docetaxel exposure in prostate cancer patients. Cancer Chemotherapy and Pharmacology (2024).
- ADME gene polymorphisms do not influence the pharmacokinetics of docetaxel: Results from a population pharmacokinetic study in Indian cancer patients. Cancer Medicine (2021).
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