306
Views
9
CrossRef citations to date
0
Altmetric
Reviews

Preclinical evidence of new opioid modulators for the treatment of addiction

, PhD, , PhD, , PhD & , PhD
Pages 977-994 | Published online: 15 Jul 2010
 

Abstract

Importance of the field: Addiction to opiates is one of the most severe forms of substance dependence, and despite a variety of pharmacological approaches to treat it, relapse is observed in a high percentage of subjects. New pharmacological compounds are necessary to improve the outcome of treatments and reduce adverse side effects. Moreover, drugs that act on the opioid system can also be of benefit in the treatment of alcohol or cocaine addiction.

Area covered by this review: Recent preclinical studies of pharmacological agents for the treatment of opiate addiction (2008 to the present date).

What the reader will gain: The reader will be informed of the latest drugs shown in animal models to modify dependence on opiates and the reinforcing effects of these drugs. In addition, reports of the latest studies to test these compounds in models of other drug addictions are reviewed.

Take home message: The classic clinical pharmacotherapy for opiate dependence, involving mu-opioid receptor agonists or antagonists, has not yielded a high success rate in humans. In pharmacotherapy for opioid dependence, new options are emerging and different pharmacological strategies are now being tested.

Notes

This box summarizes key points contained in the article.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 99.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,464.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.