Pharmacokinetic (PK) studies give us a glance on how the body effects the drug. PK studies is one of the important tools in the drug discovery process, these studies provide some meaningful insights which are highly decision enabling for the research team. Below is a glance on the basic types of PK Models
- Compartmental model – It is similar to the kinetic models used in other scientific fields such as chemical kinetics in chemistry and thermodynamics in physics. This type of study uses kinetic model to predict and describe the concentration curve. The advantage of this analysis is that the data provided is capable to predict the concentration at any given point of time and the only disadvantage is the inability to develop and validate a model. Physiologically Based Pharmacokinetic Modelling (PBPK) which is one of the most complex model relies on the use of physiological information to ease development and validation.
This is further divided in to two parts single and multi compartmental model
- Single or one compartmental model – The one-compartment model is the simplest way to describe the process of drug distribution and elimination. It model is also called linear Pharmacokinetics because the graph of the relationship between the various factors involved (dose, blood plasma concentrations, elimination, etc.) gives a straight line on the graph. For a drugs to be effective it need to move rapidly from blood plasma to other body fluids and tissues.
- Multi Compartmental Model – This model helps us overcome the limitations of single compartmental model. The graph for the non-linear relationship between the various factors is represented by a curve. The relationship between the factors can be calculating the dimensions of varied areas under the curve. This model is basically based on Michaelis–Menten enzyme kinetics.
- Non Compartmental Model – This model is totally dependent on the exposure of the drug that is Area Under Curve (AUC) using the trapezoidal rule. In trapezoidal is totally dependent on the length of x, thus the area estimation is highly dependent on the blood/plasma sampling schedule.