ReviewNature reviews. Drug discovery2024
Drug targeting in psychiatric disorders - how to overcome the loss in translation?
Review in Nature reviews. Drug discovery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Synaptic Plasticity-Intrinsic Excitability and Antidepressant Discovery.Biomedicines · 2026Review
- Building a credibility-based framework for target discovery: Perspectives from tRNA synthetase-linked metabolic diseases.Briefings in bioinformatics · 2026Article
- The applications of single-cell multiomics in drug screening.Pharmaceutical science advances · 2025Review
- AI-powered programmable virtual humans toward human physiologically-based drug discovery.Drug discovery today · 2025Review
- The neuroreceptors and transporters underlying spontaneous brain activity.Communications biology · 2025Article
- Rare Copy Number Variants Reveal Critical Cell Types and Periods of Brain Development in Neurodevelopmental Disorders.Biological psychiatry global open science · 2025Article
- Innovations in aging biology: highlights from the ARDD emerging science & technologies workshop.npj aging · 2025Article
- Application of GWAS summary data and drug-induced gene expression profiles of neural progenitor cells in psychiatric drug prioritization analysis.Molecular psychiatry · 2025Article
- Combination of Haloperidol With UNC9994, β-arrestin-Biased Analog of Aripiprazole, Ameliorates Schizophrenia-Related Phenotypes Induced by NMDAR Deficit in Mice.The international journal of neuropsychopharmacology · 2024Article
- Oxygen matters: Unraveling the role of oxygen in the neuronal response to cisplatin.Journal of the peripheral nervous system : JPNS · 2024Article
- What Remains to Be Discovered in Schizophrenia Therapeutics: Contributions by Advancing the Molecular Mechanisms of Drugs for Psychosis and Schizophrenia.Biomolecules · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In spite of major efforts and investment in development of psychiatric drugs, many clinical trials have failed in recent decades, and clinicians still prescribe drugs that were discovered many years ago. Although multiple reasons have been discussed for the drug development deadlock, we focus here on one of the major possible biological reasons: differences between the characteristics of drug targets in preclinical models and the corresponding targets in patients. Importantly, based on technological advances in single-cell analysis, we propose here a framework for the use of available and newly emerging knowledge from single-cell and spatial omics studies to evaluate and potentially improve the translational predictivity of preclinical models before commencing preclinical and, in particular, clinical studies. We believe that these recommendations will improve preclinical models and the ability to assess drugs in clinical trials, reducing failure rates in expensive late-stage trials and ultimately benefitting psychiatric drug discovery and development.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.