Format

Send to

Choose Destination
See comment in PubMed Commons below
Eur Neuropsychopharmacol. 2014 Sep;24(9):1463-74. doi: 10.1016/j.euroneuro.2014.06.013. Epub 2014 Jul 3.

A multivariate approach linking reported side effects of clinical antidepressant and antipsychotic trials to in vitro binding affinities.

Author information

1
Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria.
2
Department of Psychiatry and Psychotherapy, Medical University Vienna, Vienna, Austria.
3
Department of Pharmacology, Medical University Vienna, Vienna, Austria.
4
Department of Pharmaceutical Chemistry, University of Vienna, Vienna, Austria. Electronic address: gerhard.f.ecker@univie.ac.at.

Abstract

The vast majority of approved antidepressants and antipsychotics exhibit a complex pharmacology. The mechanistic understanding of how these psychotropic medications are related to adverse drug reactions (ADRs) is crucial for the development of novel drug candidates and patient adherence. This study aims to associate in vitro assessed binding affinity profiles (39 compounds, 24 molecular drug targets) and ADRs (n=22) reported in clinical trials of antidepressants and antipsychotics (n>59.000 patients) by the use of robust multivariate statistics. Orthogonal projection to latent structures (O-PLS) regression models with reasonable predictability were found for several frequent ADRs such as nausea, diarrhea, hypotension, dizziness, headache, insomnia, sedation, sleepiness, increased sweating, and weight gain. Results of the present study support many well-known pharmacological principles such as the association of hypotension and dizziness with α1-receptor or sedation with H1-receptor antagonism. Moreover, the analyses revealed novel or hardly investigated mechanisms for common ADRs including the potential involvement of 5-HT6-antagonism in weight gain, muscarinic receptor antagonism in dizziness, or 5-HT7-antagonism in sedation. To summarize, the presented study underlines the feasibility and value of a multivariate data mining approach in psychopharmacological development of antidepressants and antipsychotics.

KEYWORDS:

Adverse effects; Antidepressive agents; Antipsychotic agents; Clinical pharmacology; Depressive disorder; Schizophrenia

PMID:
25044049
PMCID:
PMC4502613
DOI:
10.1016/j.euroneuro.2014.06.013
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Elsevier Science Icon for PubMed Central
    Loading ...
    Support Center