What is Population Pharmacokinetic Modeling?
A population pharmacokinetic (also applicable to pharmacokinetic - pharmacodynamic relationships) analysis is a nonlinear mixed-effects modeling approach used to estimate pharmacokinetic parameters and the associated variability of a drug in a given population. The nonlinear mixed-effects modeling approach is built on a hierarchical structure which includes the estimation of two types of effects - fixed effects and random effects - which gives rise to the ‘mixed effects’ component of the name. The fixed-effects component represents structural parameters, and the random-effects component comprises between subject variability and residual variability.
Data Requirements
The nonlinear mixed-effects modeling approach is a robust tool for population analysis as it can handle both sparse and rich data, as well as unbalanced or unstructured data.
Population vs Individual Level Analysis
Nonlinear mixed-effects modeling considers the study population as the unit for analysis, hence any variability present between individuals (such as demographics, laboratory measures, genetics, disease state and concomitant medications) is maintained. Here, these individual-level attributes, such as age and weight, may be included in the model to help account for variability observed between individuals.
Comparison to Traditional Methods
In comparison to traditional methods, nonlinear mixed-effects modeling is considered the best approach for determining population-level conclusions. The superiority of nonlinear mixed-effects modeling illustrates its advantage over the naïve pooled data approach and two-stage approach when there are sparse data, an interest in understanding sources of variability, and when there is a need to develop a model to make future, model-based, predictions (ie, simulations).
What is Population Pharmacokinetic Simulation?
Model-based simulations are a powerful tool used throughout the drug development process. Simulations may be performed in silico to predict what may occur under different scenarios of interest, such as using different dosing regimens or study populations. This in turn allows the drug developer the opportunity to design more optimal studies, sometimes even foregoing the need for additional clinical trials. Population pharmacokinetic models and corresponding simulations may also be used to extrapolate into special populations, such as pediatric, geriatric, or organ impairment patients, where data may be difficult to obtain.
Overall Benefits of Population Pharmacokinetic Modeling & Simulation?
Overall, population pharmacokinetic modeling and simulation provides a robust tool in understanding a drug’s pharmacokinetic and/or pharmacodynamic profile. Leveraging population pharmacokinetic modeling and simulation can help optimize dosing regimens, identify unique patient sub-populations for dose adjustment, and improve the design and execution of clinical trials across the drug development spectrum.