Dezocine and Addiction: Friend or Foe?
Abstract
The neurological effects of opium were first described over 8000 years ago. Morphine was isolated in 1803 and by the mid-1800s had become both a pain-relieving blessing and an addictive curse. As part of the crusade to identify safer and more reliable alternatives to morphine, dezocine (Dalgan®) was marketed in the US in 1986. Its use was discontinued in the US in 2011 without revealing the reasons, but it remains one of the most widely used analgesic agents in China today. Dezocine's unique pharmacology makes it an effective analgesic with limited opioid-associated side effects and little or no reported potential for dependence and addiction. In addition, dezocine's blocking effect on serotonin and norepinephrine transporters recommends its further exploration as a potential treatment for various chronic and neuropathic pain conditions. Most recently, data suggest that dezocine might represent a viable treatment for addiction management. This report focuses on the data supporting dezocine's non-addictive profile and its potential use to treat opioid addiction and withdrawal, as well as recent efforts to generate formulations of dezocine that support sub-chronic and chronic dosing.
Read the paper
Related studies
- Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
- De Novo Transcriptome Analysis and Detection of Antimicrobial Peptides of the American Cockroach Periplaneta americana (Linnaeus)
- Molecular Characterization and Expression Profiling of Tomato GRF Transcription Factor Family Genes in Response to Abiotic Stresses and Phytohormones
- Assembly of Tight Junction Strands: Claudin-10b and Claudin-3 Form Homo Tetrameric Building Blocks that Polymerise in a Channel-Independent Manner
- Update of the Pompe variant database for the prediction of clinical phenotypes: Novel disease‐associated variants, common sequence variants, and results from newborn screening
- Machine Learning-Based SERS Chemical Space for Two-Way Prediction of Structures and Spectra of Untrained Molecules
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.