Evidence map›Paper›PMID 40112231›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives.

Sung-Hyun Kim, Sumin Yang, Jeehye Jung, Jeonghyeon Choi, Mingon Kang, Jae-Yeol Joo

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Effects of Psilocin and Psilocybin on Human 5-HTPharmaceuticals (Basel, Switzerland) · 2025
    Article
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sung-Hyun KimDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do, 15588, Republic of Korea.
Sumin YangDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do, 15588, Republic of Korea.
Jeehye JungDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do, 15588, Republic of Korea.
Jeonghyeon ChoiDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do, 15588, Republic of Korea.
Mingon KangDepartment of Computer Science, University of Nevada, Las Vegas, NV, 89154, USA.
Jae-Yeol JooDepartment of Pharmacy, College of Pharmacy, Hanyang University, Ansan, Gyeonggi-do, 15588, Republic of Korea.ORCID https://orcid.org/0000-0003-2571-3173

Funding

Ministry of Science, ICT and Future Planning 2022R1A2C1002984Ministry of Science, ICT and Future Planning RS-2023-00217123
6 · The paper itself

Abstract

Mental disorders are a representative type of brain disorder, including anxiety, major depressive depression (MDD), and autism spectrum disorder (ASD), that are caused by multiple etiologies, including genetic heterogeneity, epigenetic dysregulation, and aberrant morphological and biochemical conditions. Psychedelic drugs such as psilocybin and lysergic acid diethylamide (LSD) have been renewed as fascinating treatment options and have gradually demonstrated potential therapeutic effects in mental disorders. However, the multifaceted conditions of psychiatric disorders resulting from individuality, complex genetic interplay, and intricate neural circuits impact the systemic pharmacology of psychedelics, which disturbs the integration of mechanisms that may result in dissimilar medicinal efficiency. The precise prescription of psychedelic drugs remains unclear, and advanced approaches are needed to optimize drug development. Here, recent studies demonstrating the diverse pharmacological effects of psychedelics in mental disorders are reviewed, and emerging perspectives on structural function, the microbiota-gut-brain axis, and the transcriptome are discussed. Moreover, the applicability of deep learning is highlighted for the development of drugs on the basis of big data. These approaches may provide insight into pharmacological mechanisms and interindividual factors to enhance drug discovery and development for advanced precision medicine.

Indexed as

Deep LearningHallucinogensMental DisordersHumansLysergic Acid DiethylamidePsilocybinHallucinogensLysergic Acid DiethylamidePsilocybinartificial intelligencedeep learningdrug developmentmental disorderspsychedelic drugstranscriptome

Identifiers

PMID40112231
PMCPMC12005819

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.