CYP2D6 inhibition

CYP2D6 inhibition. Slows the enzyme handling many antidepressants, antipsychotics, opioids and psilocin. For a prodrug like codeine the effect inverts — less active drug, not more.

What acts on it

What is affected by it

What a clean result means here

A clean result means NO DOCUMENTED INTERACTION IN THIS DATASET. It does not mean safe, and it is not a clearance. Most substances are not in this dataset at all, and for many pairs that are, nobody has ever studied the combination.

In this dataset

  • Monoamine oxidase inhibition (prescription MAOIs, RIMAs, linezolid, methylene blue, harmala alkaloids)
  • Serotonergic drugs and the serotonin-toxicity mechanism
  • Dietary tyramine and L-dopa loads
  • The major cytochrome P450 pathways: CYP3A4, CYP2D6, CYP1A2, CYP2C9, CYP2C19 — inhibition and induction
  • P-glycoprotein inhibition and induction
  • 11β-HSD2 inhibition (the licorice mechanism) and the potassium consequences that follow it
  • QT prolongation as an additive pharmacodynamic axis
  • Culinary seasonings and common foods with documented pharmacological activity
  • A selected set of narrow-therapeutic-index drugs where those shifts matter most

Not in this dataset

  • Any substance not named in this dataset — which is most substances. There are tens of thousands of marketed drugs and this table holds fewer than a hundred entries.
  • Phase-2 conjugation (UGT, SULT, NAT2, COMT) except where a specific entry names it. The oilahuasca corpus turns heavily on phase 2 and this engine models it only in passing.
  • Pharmacogenomics. CYP2D6 and CYP2C19 are strongly polymorphic; a poor metaboliser and an ultra-rapid metaboliser can have opposite outcomes from the same pair, and this engine does not know your genotype.
  • Dose, timing, duration, formulation and route — all of which change whether a documented interaction is clinically real for you.
  • Renal and hepatic impairment, age, pregnancy, and body composition.
  • Additive sedation, respiratory depression, bleeding risk, hypoglycaemia and most other pharmacodynamic axes beyond the ones listed above.
  • Herb–herb interactions outside the named entries, and essentially the whole botanical world: most plants have no interaction literature at all.
  • Allergy, intolerance, and contamination or adulteration of unregulated products.
  • Anything published after the last-reviewed date below.

72 substances, 20 mechanisms, 64 citations. Last reviewed . Primary literature (every DOI resolved against the Crossref API) and FDA drug labelling. There is no free, openly-licensed, comprehensive drug-interaction dataset to draw on; NLM retired its Drug Interaction API on 2024-01-02 and DrugBank's interaction set is a commercial licence.

References

  1. U.S. Food and Drug Administration (2023). Drug Development and Drug Interactions: Table of Substrates, Inhibitors and Inducers. FDA. https://www.fda.gov/drugs/drug-interactions-labeling/drug-development-and-drug-interactions-table-substrates-inhibitors-and-inducers
  2. Flockhart DA, Thacker D, McDonald C, Desta Z (2021). The Flockhart Cytochrome P450 Drug-Drug Interaction Table. Division of Clinical Pharmacology, Indiana University School of Medicine. https://drug-interactions.medicine.iu.edu
  3. Beakley BD, Kaye AM, Kaye AD (2015). Tramadol, Pharmacology, Side Effects, and Serotonin Syndrome: A Review. Pain Physician. doi:10.36076/ppj.2015/18/395
  4. Gurley BJ, Gardner SF, Hubbard MA, et al. (2005). In vivo effects of goldenseal, kava kava, black cohosh, and valerian on human cytochrome P450 1A2, 2D6, 2E1, and 3A4/5 phenotypes. Clinical Pharmacology & Therapeutics. doi:10.1016/j.clpt.2005.01.009

Every DOI above was resolved against the Crossref API on 2026-09-09 and the returned title checked against the one printed here. Three DOIs in the first draft resolved to real but different papers and were corrected before publication.

Last reviewed . All interaction pages.