Induction

Auto induction refers to a phenomenon where a drug induces the production of enzymes that are responsible for its own metabolism. This can lead to an increase in the rate at which the drug is metabolized over time, resulting in a decrease in its plasma concentration and potentially reducing its therapeutic effectiveness.

Induction can be computed by two ways on Teoreler - Static and Indirect effect.

Static

Static induction uses a simplified approach to estimate the effect of enzyme induction on drug metabolism. It assumes a constant level of enzyme induction throughout the dosing period, leading to a fixed increase in the metabolic clearance of the drug. This method is often used for its simplicity and ease of implementation, but it may not accurately capture the dynamic nature of enzyme induction over time.

In a static model1,2, fold induction of an enzyme is computed as follows:

Indenz=1+Emax×CdrugEC50+CdrugInd_{enz} = 1 + \frac{E_{max} \times C_{drug}}{EC_{50} + C_{drug}}
[ 1 ]

where, Indenz is the fold induction of the enzyme, Emax is the maximal fold activation in vitro, Cdrug is the concentration of the drug in the liver or gut at a given time, and EC50 is the concentration of the drug that produces half-maximal induction.

Indirect Effect

Indirect effect induction models the time-dependent process of enzyme induction, taking into account the dynamic changes in enzyme levels over time. This approach considers the rate of enzyme synthesis and degradation, allowing for a more accurate representation of how enzyme levels fluctuate in response to drug exposure. Indirect effect models are particularly useful for drugs that exhibit delayed or prolonged induction effects, as they can capture the temporal aspects of enzyme regulation more effectively.

In an indirect effect model2, fold induction of an enzyme is computed as follows:

dIndenzdt=kdeg×(Emax×CdrugEC50+Cdrug−Indenz)\frac{dInd_{enz}}{dt} = k_{deg} \times \left(\frac{E_{max} \times C_{drug}}{EC_{50} + C_{drug}} - Ind_{enz}\right)
[ 2 ]

where, dIndenz/dt is the change in fold induction of the enzyme over time, kdeg is the degradation rate constant of the enzyme.

References

  1. Peter, S.A. Evaluation of Drug–Drug Interaction Risk with PBPK Models. Physiologically‐Based Pharmacokinetic (PBPK) Modelling and Simulations. 2012. p.183-207. https://doi.org/10.1002/9781118140291.ch9
  2. Yamashita F, Sasa Y, Yoshida S, Hisaka A, Asai Y, Kitano H, et al. Modelling of rifampicin-induced CYP3A4 activation dynamics for the prediction of clinical drug-drug interactions from in vitro data. PLoS One. 2013;8(9):e70330. https://doi.org/10.1371/journal.pone.0070330
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