[Q-DIPS: current approach to prediction of drug interactions].
Interactions are an important cause of adverse drug effects. Because of the large number of substances and the complexity of the mechanisms involved, computers can be of great help in the detection, prediction and management of interactions. We propose a new complementary approach to the prediction of interactions through a key mechanism, hepatic drug biotransformation. The originality of the approach consists in integrating in vitro enzymatic data and pharmacokinetic data to make in vivo predictions. An Inhibition Index (II) is defined to characterize the interaction potential of an inhibitor for a specific isozyme independently of the isozyme's substrates. It is thus possible, even in the absence of prior clinical observations, to make individualized qualitative as well as quantitative predictions of potential in vivo interactions. Q-DIPS is a prototype computer system under development on a Macintosh to manage the large amount of multi-dimensional data and facilitate the investigation and validation of extrapolations. The kinetics of II for two antifungal drugs, fluconazole and ketoconazole, are simulated and compared in order to illustrate the potential of the approach.
Leemann
T
T
Division de Pharmacologie clinique, Hôpital cantonal universitaire, Genève.
Dayer
P
P
D001711:Biotransformation; D003198:Computer Simulation; D004347:Drug Interactions; D015725:Fluconazole / Q000493:pharmacokinetics; D006801:Humans; D007654:Ketoconazole / Q000493:pharmacokinetics; D008099:Liver / Q000378:metabolism; D010599:Pharmacokinetics; D011336:Probability; D012984:Software
D015725:Fluconazole; D007654:Ketoconazole
Q-DIPS: une approche nouvelle de la prédiction des interactions médicamenteuses.