7.1 : Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.

The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately is important. There are three types of parameter models: compartment, physiological, and distributed. The primary advantage of the model approach is its ability to provide detailed insight into drug distribution and kinetics by simulating specific physiological scenarios. However, it requires assumptions and parameters that may not always represent real-life complexity.

The model-independent method, or the noncompartmental analysis, does not rely on specific compartment models. This method assumes linear kinetics for drugs and can be applied to any compartment model. This approach involves collecting experimental data post a single dose of the drug. The method helps estimate bioavailability, clearance, apparent volume of distribution, half-life, and drug absorption rate. The main advantage of the model-independent approach is its flexibility, as it does not depend on predefined assumptions about the body's compartments. However, it may not be suitable for drugs exhibiting nonlinear kinetics.

In practice, understanding when to use each approach is crucial. The model approach is more appropriate when detailed information about drug distribution and organ-specific kinetics is required, such as during drug development or in cases of complex pharmacokinetics, while the model-independent method is better suited for routine pharmacokinetic evaluations where quick and straightforward analysis is sufficient, or when assumptions about compartmental distribution are impractical.