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Investigating the Effects of Antipsychotics and Schizotypy on the N400 Using Event-Related Potentials and Semantic Categorization
Published on: November 19, 2014
Visualizing classification of drugs used in psychotic disorders: A 'subway map' representing mechanisms, established
Crystal Zhou1,2, David J Nutt3, Simon Jc Davies1
1Geriatric Psychiatry Division, Centre for Addiction and Mental Health/University of Toronto, Toronto, ON, Canada.
Abstract:
Drugs used to treat psychotic disorders ('antipsychotics') have been widely used in psychiatry since the introduction of chlorpromazine in the mid-1950s. The categorization of these drugs evolved in a piecemeal way, relying initially on grouping by chemical structure (e.g. phenothiazines, butyrophenones), then by epoch of introduction (e.g. first generation ('conventional') vs second generation ('atypical')). As psychopharmacological expertise has advanced, it has become possible to quantify affinities for each drug in this class for relevant receptors including dopamine D2, 5HT2A, 5HT2C, histamine H1 and others. However, until the recent emergence of a new generation of agents known collectively as dopamine D2 receptor partial agonists (e.g. aripiprazole, brexpiprazole and cariprazine), there had been little reference in drug classification to specific pharmacological properties. An overview of data on receptor affinities across multiple drugs and receptor types would permit categorization according to binding affinities and putative pharmacological mechanisms. In this paper, we have attempted to construct a 'subway map' of 32 drugs used for treatment of psychotic disorders. This design allows a visualization of both the historical classifications by structure and epoch of introduction, and of the binding affinities for key receptors based on appraisal of scientific literature. The map represents a step towards categorization by mechanism, allowing prescribers and patients to understand which drugs share common biological features and the extent to which drugs may have similarities and differences in their mechanisms. In addition, this approach may encourage more logical groupings of drugs to be used in systematic reviews and meta-analyses.
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