Deep learning analysis of particle content in extracted slow-release morphine: longer boiling reduces large fragments while retaining morphine extraction
Henrik Sahlin Pettersen, Per Ole M. Gundersen, Trond Oskar Aamo, Katrine Melby

TL;DR
This study shows that boiling morphine tablets longer reduces harmful particles while keeping most of the drug, helping reduce injection risks for users.
Contribution
The study introduces deep learning-based particle analysis to assess injection risks from morphine extraction methods.
Findings
Method D (10-minute boiling) reduced particles most effectively while retaining 81.2% morphine.
Method A produced the most small particles (<100 μm) due to lack of coating removal.
Longer boiling times significantly decrease particle content across all size categories.
Abstract
Injecting drug users often extract morphine from slow-release oral tablets, potentially leading to harmful particle contamination upon injection. This study assesses the efficiency of morphine extraction and particle content of filtrates produced by various methods employed by drug users in Trondheim, Norway. The findings provide important insights that can inform harm-reduction services and healthcare providers in efforts to reduce injection-related morbidity among people who already inject drugs. Four extraction methods were evaluated using 60 mg Dolcontin tablets: Method A (no coating removal, 3-minute boiling), Method B (coating removal, crushing, 3-minute boiling), Method C (coating removal, 3-minute boiling), and Method D (coating removal, 10-minute boiling). Resulting solutions were filtered using cotton balls, and morphine content was quantified using LC-MS/MS. Particle content…
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Taxonomy
TopicsHIV, Drug Use, Sexual Risk · Forensic Toxicology and Drug Analysis · Opioid Use Disorder Treatment
