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Dronabinol as an Adjunct for Reducing Pain

CED Clinical Relevanceย ย #97High Clinical Relevanceย ย Strong evidence or policy relevance with direct clinical implications.
๐Ÿงช Clinical Trial Watchย ย |ย ย CED Clinic
Clinical TrialChronic PainLow Back PainDronabinolPlacebo-Controlled
Trial ID NCT06454669
Phase N/A
Status Recruiting
Condition Low Back Pain
Intervention Dronabinol
Why This Matters

Chronic low back pain affects millions globally with limited effective treatment options, and this represents one of the first rigorous placebo-controlled trials specifically examining synthetic THC for this indication. The study addresses a critical evidence gap in cannabinoid medicine where most chronic pain data comes from observational studies rather than controlled trials.

Clinical Summary

This is an exploratory proof-of-concept, double-blind, placebo-controlled trial randomizing up to 75 participants with chronic low back pain 2:1 to receive oral dronabinol (synthetic THC) up to 30mg daily versus placebo over 8 weeks. The primary focus is establishing safety profiles and feasibility rather than efficacy endpoints, with results intended to inform the design of future larger-scale trials. The study is currently recruiting participants at a single site.

Dr. Caplan’s Take

โ€œIf this trial demonstrates acceptable safety and tolerability profiles, it could provide the foundational data needed to advance synthetic THC into larger efficacy trials for chronic low back pain. This represents an important step toward evidence-based cannabinoid prescribing for one of the most common pain conditions I encounter in practice.โ€

Clinical Perspective
๐Ÿง  Patients should understand this is an early-stage safety study, not designed to definitively prove effectiveness for pain relief. Clinicians interested in cannabinoid pain management should monitor these results closely, as they may inform future prescribing guidelines and help establish dosing frameworks for dronabinol in chronic pain conditions.

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This trial item was assembled from normalized source metadata and pipeline scoring.






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