Harnessing associative learning paradigms to optimize drug treatment.
Pavlovian conditioned drug effects
associative learning
extinction
placebo
treatment optimization
Journal
Trends in pharmacological sciences
ISSN: 1873-3735
Titre abrégé: Trends Pharmacol Sci
Pays: England
ID NLM: 7906158
Informations de publication
Date de publication:
06 2022
06 2022
Historique:
received:
17
12
2021
revised:
06
03
2022
accepted:
08
03
2022
pubmed:
5
4
2022
medline:
18
5
2022
entrez:
4
4
2022
Statut:
ppublish
Résumé
Continuous treatment with drugs is an inevitable prerequisite for many clinical conditions, such as chronic inflammatory diseases, pain, or depression. However, the amount of adverse side effects induced by opioids, antidepressants, or immunosuppressive drugs urges the need for developing alternative or supportive treatment strategies. In this context, conditioned pharmacological effects, obtained by means of associative learning, have been successfully implemented as controlled drug-dose reduction strategies to maintain and strengthen the efficacy of medical treatments. Such approaches have been proven effective in experimental animals, healthy subjects, and patient populations. Thus, a systematic use of conditioned pharmacological effects should be seriously considered as a supportive treatment option to optimize pharmacological treatment effects for the patients benefit.
Identifiants
pubmed: 35369993
pii: S0165-6147(22)00052-9
doi: 10.1016/j.tips.2022.03.002
pii:
doi:
Substances chimiques
Analgesics, Opioid
0
Antidepressive Agents
0
Immunosuppressive Agents
0
Types de publication
Journal Article
Review
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
464-472Informations de copyright
Copyright © 2022 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests No interests are declared.