Harnessing associative learning paradigms to optimize drug treatment.


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
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

464-472

Informations 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.

Auteurs

Martin Hadamitzky (M)

Institute of Medical Psychology and Behavioral Immunobiology, Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, University of Duisburg-, Essen, Germany. Electronic address: martin.hadamitzky@uk-essen.de.

Manfred Schedlowski (M)

Institute of Medical Psychology and Behavioral Immunobiology, Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Hospital Essen, University of Duisburg-, Essen, Germany; Department of Clinical Neuroscience, Osher Center for Integrative Medicine, Karolinska Institutet, 171 77 Stockholm, Sweden.

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Classifications MeSH