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Record W4388821899 · doi:10.1021/acs.jmedchem.3c01225

Novel Psilocin Prodrugs with Altered Pharmacological Properties as Candidate Therapies for Treatment-Resistant Anxiety Disorders

2023· article· en· W4388821899 on OpenAlexaff
Sheetal A. Raithatha, Jillian M. Hagel, Kaveh Matinkhoo, Lisa Yu, David Press, Sarah G. Cook, Govinda Sharma, D. Dhananjaya, Glynnis Jensen, Jessica B. Lee, Charlie X. Cai, Jonathan Gallant, Jaideep S. Bains, Joseph E. Tucker, Peter J. Facchini

Bibliographic record

VenueJournal of Medicinal Chemistry · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsilocybinProdrugPharmacologyChemistryHallucinogenAnxietyActive metabolitePsychologyPharmacokineticsMedicinePsychiatry

Abstract

fetched live from OpenAlex

The psychedelic prodrug psilocybin has shown therapeutic benefits for the treatment of numerous psychiatric conditions. Despite positive clinical end points targeting depression and anxiety, concerns regarding the duration of the psychedelic experience produced by psilocybin, associated with enduring systemic exposure to the active metabolite psilocin, pose a barrier to its therapeutic application. Our objective was to create a novel prodrug of psilocin with similar therapeutic benefits but a reduced duration of psychedelic effects compared with psilocybin. Here, we report the synthesis and functional screening of 28 new chemical entities. Our strategy was to introduce a diversity of cleavable groups at the 4-hydroxy position of the core indole moiety to modulate metabolic processing. We identified several novel prodrugs of psilocin with altered pharmacokinetic profiles and reduced pharmacological exposure compared with psilocybin. These candidate prodrugs have the potential to maintain the long-term benefits of psilocybin therapy while attenuating the duration of psychedelic effects.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.346
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations18
Published2023
Admission routes1
Has abstractyes

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