Inhibition of Hepatic Microsomal Drug Metabolism by the Hydrazines Ro 4-4602, MK 486, and Procarbazine Hydrochloride

1972 ◽  
Vol 50 (7) ◽  
pp. 721-724 ◽  
Author(s):  
Norman R. Bade ◽  
Stuart M. MacLeod ◽  
Kenneth W. Renton
Keyword(s):  
Drug Interaction ◽  
Drug Metabolism ◽  
Sleeping Time ◽  
Hydrazine Derivatives ◽  
Significant Drug Interaction ◽  
Microsomal Drug Metabolism ◽  
Clinically Significant ◽  
Hepatic Biotransformation

Preliminary experiments were undertaken to examine the effect of three hydrazine derivatives, viz. Ro 4-4602, MK 486, and procarbazine hydrochloride, on hepatic microsomal drug metabolism in rats. All three compounds when given as pretreatment significantly prolonged pentobarbital sleeping time. In vitro, the hepatic microsomal N-demethylation of aminopyrine was inhibited. It is concluded that all three drugs are possible sources of clinically significant drug interaction when administered in combination with other agents which undergo hepatic biotransformation.

Comparative Effects of Medetomidine Enantiomers on in vitro and in vivo Microsomal Drug Metabolism

1991 ◽  
Vol 69 (3) ◽  
pp. 189-194 ◽  
Author(s):  
Olavi Pelkonen ◽  
Juhani Puurunen ◽  
Pentti Arvela ◽  
Risto Lammintausta
Keyword(s):  
Drug Metabolism ◽  
Microsomal Drug Metabolism

scholarly journals Clinically Significant Drug Interaction between Tipranavir-Ritonavir and Phenobarbital in an HIV-Infected Subject

2007 ◽  
Vol 45 (12) ◽  
pp. 1654-1655 ◽  
Author(s):  
S. Bonora ◽  
A. Calcagno ◽  
S. Fontana ◽  
A. D'Avolio ◽  
M. Siccardi ◽  
...  
Keyword(s):  
Drug Interaction ◽  
Infected Subject ◽  
Significant Drug Interaction ◽  
Clinically Significant

ASSESSMENT OF DRUG INTERACTIONS IN OUTPATIENT PRESCRIPTIONS IN HUE UNIVERSITY OF MEDICINE AND PHARMACY HOSPITAL

2018 ◽  
Vol 8 (5) ◽  
pp. 26-36
Author(s):  
Phuong Vo Thi Hong ◽  
Hien Nguyen Thi
Keyword(s):  
Drug Interaction ◽  
Proton Pump Inhibitor ◽  
Drug Interactions ◽  
Descriptive Study ◽  
Management Guideline ◽  
Cross Sectional ◽  
Significant Drug Interaction ◽  
Clinically Significant ◽  
Multiple Symptoms ◽  
Outpatient Prescriptions

Background: The combination of drugs in treatment is inevitable, especially in multiple diseases and multiple symptoms. This is the leading cause of occurrence of drug - drug interactions. Objectives: (1) To identify clinically significant drug interactions in outpatient prescriptions in Hue University of Medicine and Pharmacy Hospital, (2) To build a management guideline of clinically significant drug interactions in Hue University of Medicine and Pharmacy Hospital. Materials and methods: 5338 outpatient prescriptions were collected from Pharmacy Faculty – Hue University of Medicine and Pharmacy Hospital from 1st to 31st October 2017, using cross-sectional descriptive study method. Results and Conclusion: The list of 20 clinically significant drug interaction pairs was identified and a management guideline for each interacting pair was built. The prevalence of prescriptions with drug interactions was 6.7%. The most commonly identified drug interaction pair was clopidogrel and proton pump inhibitor (1.59%). The occurrence of drug interactions increased with increase in the age of patients and the number of drugs prescribed (p < 0.05). Key words: combination of drugs, drug interaction, clinically significant, prescription, outpatient

scholarly journals In vitro and in silico Approaches to Study Cytochrome P450-Mediated Interactions

2017 ◽  
Vol 20 (1) ◽  
pp. 319 ◽  
Author(s):  
Boon Hooi Tan ◽  
Yan Pan ◽  
Amelia Nathania Dong ◽  
Chin Eng Ong
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
Drug Metabolism ◽  
In Silico ◽  
High Throughput Screening ◽  
Rational Design ◽  
Pharmacokinetic Variability ◽  
Drug Drug Interaction ◽  
In Silico Methods

In vitro and in silico models of drug metabolism are utilized regularly in the drug research and development as tools for assessing pharmacokinetic variability and drug-drug interaction risk. The use of in vitro and in silico predictive approaches offers advantages including guiding rational design of clinical drug-drug interaction studies, minimization of human risk in the clinical trials, as well as cost and time savings due to lesser attrition during compound development process. This article gives a review of some of the current in vitro and in silico methods used to characterize cytochrome P450(CYP)-mediated drug metabolism for estimating pharmacokinetic variability and the magnitude of drug-drug interactions. Examples demonstrating the predictive applicability of specific in vitro and in silico approaches are described. Commonly encountered confounding factors and sources of bias and error in these approaches are presented. With the advent of technological advancement in high throughput screening and computer power, the in vitro and in silico methods are becoming more efficient and reliable and will continue to contribute to the process of drug discovery, development and ultimately safer and more effective pharmacotherapy. This article is open to POST-PUBLICATION REVIEW. Registered readers (see “For Readers”) may comment by clicking on ABSTRACT on the issue’s contents page.

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