Failed trials for central nervous system disorders do not necessarily invalidate preclinical models and drug targets
Open accessAbstract
A recent article identified five key technical determinants that make substantial contributions to the outcome of drug R&D projects (Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat. Rev. Drug Discov . 13 , 419–431 (2014)) 1 . Careful consideration of such determinants might be particularly valuable in the fields of neurology and psychiatry, in which successful drug development has declined precipitously over the past decade. This decline has largely been fuelled by a high failure rate in the translation of preclinical efficacy findings, caused by multiple factors (see Supplementary information S1 (table) ), including limited training and poor protocol design, inadequate animal models, insufficiently validated therapeutic targets and problems with data handling and reporting.
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No eEF2K inhibitor has yet established antidepressant efficacy in humans, and the absence of clinical-grade compounds limits assessment of target engagement, tolerability, and long-term safety.
“No eEF2K inhibitor has yet established antidepressant efficacy in humans, and the absence of clinical-grade compounds limits assessment of target engagement, tolerability, and long-term safety [146,165].”
From Synaptic Plasticity—Intrinsic Excitability and Antidepressant Discovery (2026) · cites this paper as [165]
The Target engagement section explains why demonstrating drug exposure and target binding is important in clinical testing, which supports the general concern about assessing target engagement. It does not address eEF2K inhibitors, their antidepressant efficacy in humans, the availability of clinical-grade compounds, or their tolerability and long-term safety. (LLM, conf=0.78)
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- Authors
- Bespalov, A., Steckler, T., Altevogt, B., Koustova, E., Skolnick, P., Deaver, D., Millan, M. J., Bastlund, J. F., Doller, D., Witkin, J., Moser, P., O'Donnell, P., Ebert, U., Geyer, M. A., Prinssen, E., Ballard, T., & Macleod, M.
- Affiliations
- First Pavlov State Medical University of St. Petersburg (RU)
- Janssen (Belgium) (BE)
- Pfizer (United States) (US)
- National Institutes of Health (US)
- Alkermes (United States) (US)
- Servier (France) (FR)
- Lundbeck (Denmark) (DK)
- Eli Lilly (United States) (US)
- Boehringer Ingelheim (Germany) (DE)
- University of California San Diego (US)
- F. Hoffmann-La Roche AG (CH)
- University of Edinburgh (GB)
- Corresponding author
- Bespalov, Anton
- ORCID
- Venue
- Nature Reviews Drug Discovery
- Published
- 2016-06-17
- Volume
- 15
- Issue
- 7
- Pages
- 516-516
- ISSN
- 1474-1776 (ISSN-L)
- 1474-1784
- OpenAlex
- W2430666023
- Cited by
- 84
- References
- 11
- Citations by year
- 2026: 9 · 2025: 8 · 2024: 11 · 2023: 9 · 2022: 8 · 2021: 5 · 2020: 12 · 2019: 5 · 2018: 4 · 2017: 10 · 2016: 3
- FWCI
- 11.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Reviews Drug Discovery (publishedVersion, other-oa)
- PubMed (publishedVersion)
- Funders
- National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC/L000970/1)
- Universiteit Utrecht
- Genentech
- Topics
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- CNS drug development, clinical trial failure, preclinical models, therapeutic target, translational failure, animal models, protocol design, neurology
- MeSH terms
- Animals, Central Nervous System Diseases, Clinical Trials as Topic, Drug Evaluation, Preclinical, Humans, Research Design, Treatment Failure
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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