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ADMEWORKS DDI Simulator - Functionality

Competitive and Mechanism-Based Inhibition models

Prediction of drug-drug interaction using either competitive (reversible) inhibition or mechanism-based (irreversible) inhibition (MBI) model is possible. In the case of MBI model, decreasing pattern of the activity of the metabolizing enzyme due to repeated dose of the inhibitor, as well as the recovery pattern after the inhibitor dose was stopped, can be verified from the time graphs.

Physiologically-based Pharmacokinetic Model

As opposed to simple approximation by “1+[I]/Ki” where the concentration is constant, DDI Simulator uses PBPK model to simulate more accurate time-dependent concentrations. The comparison graphs below show several drugs give better agreement with experimentally observed results using the PBPK model.

Database of in vivo Ki values

A database of well-known substrates and inhibitors is provided so users can readily simulate DDI with their own compound. The database contains in vivo Ki values obtained by fitting parameters using time concentration profiles from actual DDI clinical studies. Moreover, accurate estimation of the in vivo Ki from in vitro Ki value is also possible using the relationship as shown in the figure below, i.e. the ratio of in vivo and in vitro Ki highly correlates with octanol-water partition coefficient (clogP).

Inhibition of Multiple CYP Isoforms

Accurate prediction of DDI is possible for drugs metabolized by several CYP isoforms. By simply assigning each CYP’s contribution to the total metabolism of the substrate, the effect of simultaneous inhibition of multiple CYP isoforms can be studied.

Inhibition of Intestinal Metabolism

Drug metabolizing enzymes like CYP3A4 exists not only in the liver but also in the small intestines. Inhibition may occur in both places that would affect the risk level of DDI.
DDI Simulator automatically calculates the maximum risk when inhibition also occurs in the small intestines.

Optimization of Dosing Regimen to Minimize Risk

Flexible settings allow the user to study the best dosing regimen for both the substrate and the inhibitor in order to minimize the risk of DDI. Also, simulation of the maximum risk when administering repeated doses of the inhibitor is automatically done by calculating the right substrate dose timing at the steady-state.