Development and Application of the Strategy for the Quantitative Prediction of Drug-induced Parkinsomisms

摘要

Durg-induced parkinsonism is generally known as a sie effect of antipsychotic drugs. Recently, the induction of parkinsonism has been reported with the use of various peripherally acting durgs such as calcium channel blockers, antiarryhythmic agents and so on. therefore, it is eagerly rquired to quantitatively assess the extent of drug-induced parkinsonism prior to the dispensing of durgs. We have developed a strategy to quantitatiely predict the intensity of drug-induced parkinsonism based on the receptor-occupancies of the dopanine D_1,D_2 and muscarinic acetycholine (mACh) receptors in ivio and in vitro. first, we assessed the in vivo dopamine D_1, D_2 and mACh receptor occupanices in the striatum in mice after drug administrationfor twently five durgs. Simultaneously, the intensity of catalepsy induced by these drugs were assessed in the same animals. the intensity of catalepsy cna be predicted by in vivo occupancies of the dopamine D_1, D_2 and mACh receptors using a pharmacodynamic model. Second, we applied this pharmacodynamic model to preidict quantitatiely the risk of drug-induced parkinsonism in humans. The in vivo dopamine D_1, D_2 and mACh recpetor ocupancies of each drug in humans were stimated from the pharmacokinetic data in humans and the in vitro affiniteis for the recprotrs in mice. The estimated risk of each drug to induce parkinsonsim well coincided with the incidence of aprkinsornism rpeorted uring the clinical trial period. The pharmacodynamic model was applicable not only to an individula drug but also to a prescription. The clinicla risk of every prescription to induce parkinsonism canb e quantitatively predicted by this stratgy from th set of pharmacokinetic data in humans and the afinities for the receptors of each drug in the rpescription. Finally, we incroporated this model into a prescription-ordering system to develop a computer-aided durg infrmation system for ational rescription. developed system can display the risk of oparkinsonism for an individual prescription and provide essential drug informations to the physician to prescribe. The developed system any be also applciable to quantitatively predict other receptor-mediated adverse reactions of drugs.