A streamlined synthesis of 5-methoxy-N,N-dimethyltryptamine, bufotenin, and bufotenin prodrugs from melatonin
Bibliographic record
Abstract
The recent resurgence in psychedelic research has increased demand for these molecules for clinical studies. Due to the differences between national regulations and considering the dominance of the American market and its continued prohibition of many such molecules, the commercial availability of many of these compounds remains poor. This has also inhibited research into developing scalable and economic routes to these compounds. Many of the approaches to date use expensive starting materials, require extensive chromatography, or incorporate late-stage chemistries that raise toxicity concerns. Herein we report a streamlined, chromatography-free synthesis of analytically pure 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT, 76% overall yield from melatonin) and its demethylated derivative bufotenin (51% from 5-MeO-DMT) from the inexpensive and widely available compound melatonin. The sequence to 5-MeO-DMT can be conducted on lab scale (64 g of product) in under 5 days (3 days if you discount the initial hydrolysis) by a single operator. Demethylation to obtain bufotenin hydrobromide takes up to an additional 2 days and was done on 22 g of product. We then report the preparation of candidate prodrugs of bufotenin with the potential to increase its suitability for both nanoformulation and/or passive uptake across the blood-brain-barrier.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".