A PK model: a description of the time-course and factors affecting the handling of drugs by the body.
1. Time-variant Models
2. Deterministic model – Mathematical model in which outcomes are precisely determined through known relationships among states and events, without any room for random variation. In such models, a given input will always produce the same output, such as in a known chemical reaction.
3. Static Model
4. Lumped Model – The lumped-element model (also called lumped-parameter model, or lumped-component model) simplifies the description of the behaviour of spatially distributed physical systems into a topology consisting of discrete entities that approximate the behaviour of the distributed system under certain assumptions.
5. Linear models describe a continuous response variable as a function of one or more predictor variables. They can help you understand and predict the behavior of complex systems or analyze experimental, financial, and biological data. Linear regression is a statistical method used to create a linear model.
However, many times if you call a PK model linear, it is referring specifically to the clearance parameter.
6. Continuous modelling is the mathematical practice of applying a model to continuous data (data which has a potentially infinite number, and divisibility, of attributes). They often use differential equations and are converse to discrete modelling.
7. Time-invariant models
8. A stochastic model is a tool for estimating probability distributions of potential outcomes by allowing for random variation in one or more inputs over time. The random variation is usually based on fluctuations observed in historical data for a selected period using standard time-series techniques.
9. Dynamic models are simplified representations of some real-world entity, in equations or computer code. They are intended to mimic some essential features of the study system while leaving out inessentials. The models are called dynamic because they describe how system properties change over time: a gene’s expression level, the abundance of an endangered species, the mercury level in different organs within an individual, and so on.
10. The distributed model defines a way of contact in between the components of a system and it refers to how resources are spread out and works on more than one device to improve the effectiveness and performance of a task.
11. Nonlinear model can refer to a nonlinear regression model or it can also refer to the clearance mechanism.
12. Discrete modelling is the discrete analogue of continuous modelling. In discrete modelling, formulae are fit to discrete data—data that could potentially take on only a countable set of values, such as the integers, and which are not infinitely divisible.
Important PK variables (not all-inclusive)
F = bioavailability
V = Volume of distribution
Cl = Clearance