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Enzyme induction
Many of the enzymes involved in drug metabolism may be up-regulated by exposure to drugs and environmental chemicals leading to increased rates of metabolism. This phenomenon is known as enzyme induction.
The Simcyp Simulator can predict the extent of in vivo induction from in vitro data using a concentration-dependent induction model. Accordingly, it can be used to assess the inducing potential of new chemical entities at clinically relevant concentrations within virtual populations.
Prediction of the impact of enzyme induction on in vivo pharmacokinetics requires knowledge of the turnover rate of the enzyme(s) involved, in addition to in vitro data. Estimates of the turnover (kdeg) values of a range of CYPs (based on a meta-analysis of the literature [Ghanbari et al.,2006]) are incorporated into a database within the Simcyp Simulator.
The Simcyp induction model is highly flexible and can handle different in vitro experimental designs of varying complexity. In the simplest case, the maximum fold induction (Indmax) is used to simulate induction. However, to accommodate different degrees of induction as a function of the concentration of the inducer, an indication of the potency of the inducer (IndC50) is also required. For weak inducers, and when Indmax has not been determined in vitro, the initial slope of the concentration-induction relationship (Indslope) is used to model induction.
The Simcyp Simulator also contains an induction calibrator which relates relevant in vitro parameters of test compounds to those of a positive control (e.g. rifampicin), as recommended in the FDA draft guidelines. The in vitro and in vivo dose-response relationships for enzyme induction by rifampicin have been well-characterised, allowing calibration of the link between in vitro and in vivo induction and hence extrapolation to outcome in virtual populations.This ability to anticipate likely extremes of induction is particularly advantageous as most investigators assess induction in human hepatocytes from only 3 donors, as recommended in FDA guidance.
For compounds that both inhibit and induce CYPs, predicting the net effect in vivo is particularly challenging. The Simcyp models allow this to be done in relevant virtual populations purely from in vitro data (Figure 13). An understanding of the change in the direction (net inhibition to net induction) of an interaction with time is essential for the design of multidose experimental studies needed to inform dosage recommendations when the extent of interaction is time-dependent.
Figure 13. Simulation of the change in systemic exposure to a drug over time when co-administered with another compound that is both an inhibitor and an inducer of CYP3A4. The extent of drug interaction varies with time, as indicated by the change in Rss (the ratio of AUC in the absence and presence of the inhibitor/inducer).
