This page presents the various computing methods deployed within EzeCHiel.

These computing methods are decomposed into the following categories:

1. Prediction engines, to calculate the predicted concentration from the patient/population parameters
2. A posteriori engines, to calculate the a posteriori parameters of a patient, based on the observed concentration and the population data
3. Posology engines, to offer propositions about suitable posologies, considering a set of constraints (time, available doses)

Prediction engines

Currently, two main models have been implemented, both of them for 1, 2 and 3 compartments, and for different kind of intakes:

1. Linear elimination
2. Michaelis-Menten elimination

Intakes supported by EzeCHiel:

1. Bolus
2. Infusion
3. Extravascular

The equations of these prediction engines are detailed within 6 subpages, corresponding to the type of elimination and number of compartments:

Linear elimination

• Linear elimination with 1 compartment
• Linear elimination with 2 compartments
• Linear elimination with 3 compartments

Michaelis-Menten elimination (non-linear)

• Michaelis-Menten elimination with 1 compartment
• Michaelis-Menten elimination with 2 compartments
• Michaelis-Menten elimination with 3 compartments

A posteriori engines

Bayesian approach

 

Posology engines

 

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