Overdose Risk and Client Characteristics Associated With the Injection of Buprenorphine at a Medically Supervised Injecting Center in Sydney, Australia

Patterns of use and adverse events reported among persons who regularly inject buprenorphine: a systematic review

Background and Aims

Given the ongoing opioid crisis, novel interventions to treat severe opioid use disorder (OUD) are urgently needed. Injectable opioid agonist therapy (iOAT) with diacetylmorphine or hydromorphone is effective for the treatment of severe, treatment-refractory OUD, however barriers to implementation persist. Intravenous buprenorphine for the treatment of OUD (BUP iOAT) has several possible advantages over traditional iOAT, including a safety profile that might enable take-home dosing. We aimed to characterize injecting practices among real-world populations of persons who regularly inject buprenorphine, as well as associated adverse events reported in order to inform a possible future BUP iOAT intervention.

Methods

We conducted a systematic review. We searched MEDLINE, EMBASE, and PsycINFO from inception through July 2020 and used backwards citation screening to search for publications reporting on dose, frequency among persons who regularly inject the drug, or adverse events associated with intravenous use of buprenorphine. The review was limited to English language publications and there was no limitation on study type. Study quality and risk of bias was assessed using the Mixed Methods Appraisal Tool. Narrative synthesis was used in reporting the results.

Results

Eighty-eight studies were included in our review. Regular injection of buprenorphine was identified across diverse settings world-wide. Daily dose of oral buprenorphine injected was < 1–12 mg. Frequency of injection was 0–10 times daily. Adverse events could be characterized as known side effects of opioids/buprenorphine or injection-related complications. Most studies were deemed to be of low quality.

Conclusions

Extramedical, intravenous use of buprenorphine, continues to be documented. BUP iOAT may be feasible and results may inform the development of a study to test the efficacy and safety of such an intervention. Future work should also examine acceptability among people with severe OUD in North America. Our review was limited by the quality of included studies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12954-022-00695-5.

Investigation of buprenorphine-related deaths using urinary metabolite concentrations

Quantitative analysis of postmortem urine, instead of blood, for buprenorphine and metabolites may provide additional evidence for the diagnosis of fatal buprenorphine poisoning. In this study, 247 autopsy urine samples, previously testing positive for buprenorphine or norbuprenorphine, were quantitatively reanalysed with a recently developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for unconjugated buprenorphine (BUP), norbuprenorphine (NBUP), naloxone (NAL), and their respective conjugated metabolites, buprenorphine glucuronide (BUPG), norbuprenorphine glucuronide (NBUPG), and naloxone glucuronide (NALG). The cases were divided, according to medical examiners' decision, to buprenorphine poisonings and other causes of death. The groups were compared for urinary concentrations and metabolite concentration ratios of the six analytes. All median concentrations were higher in the buprenorphine poisoning group. The median concentration of BUPG was significantly higher and the median metabolite ratios NBUP/BUP, NBUPG/BUPG, and NBUPtotal/BUPtotal were significantly lower in poisonings than in other causes of death. Naloxone-related concentrations and ratios were not significantly different between the groups.

Intrinsic Efficacy of Opioid Ligands and Its Importance for Apparent Bias, Operational Analysis, and Therapeutic Window

Evidence from several novel opioid agonists and knockout animals suggests that improved opioid therapeutic window, notably for analgesia versus respiratory depression, is a result of ligand bias downstream of activation of the µ-opioid receptor (MOR) toward G protein signaling and away from other pathways, such as arrestin recruitment. Here, we argue that published claims of opioid bias based on application of the operational model of agonism are frequently confounded by failure to consider the assumptions of the model. These include failure to account for intrinsic efficacy and ceiling effects in different pathways, distortions introduced by analysis of amplified (G protein) versus linear (arrestin) signaling mechanisms, and nonequilibrium effects in a dynamic signaling cascade. We show on both theoretical and experimental grounds that reduced intrinsic efficacy that is unbiased across different downstream pathways, when analyzed without due considerations, does produce apparent but erroneous MOR ligand bias toward G protein signaling, and the weaker the G protein partial agonism is the greater the apparent bias. Experimentally, such apparently G protein-biased opioids have been shown to exhibit low intrinsic efficacy for G protein signaling when ceiling effects are properly accounted for. Nevertheless, such agonists do display an improved therapeutic window for analgesia versus respiratory depression. Reduced intrinsic efficacy for G proteins rather than any supposed G protein bias provides a more plausible, sufficient explanation for the improved safety. Moreover, genetic models of G protein-biased opioid receptors and replication of previous knockout experiments suggest that reduced or abolished arrestin recruitment does not improve therapeutic window for MOR-induced analgesia versus respiratory depression. SIGNIFICANCE STATEMENT: Efforts to improve safety of µ-opioid analgesics have focused on agonists that show signaling bias for the G protein pathway versus other signaling pathways. This review provides theoretical and experimental evidence showing that failure to consider the assumptions of the operational model can lead to large distortions and overestimation of actual bias. We show that low intrinsic efficacy is a major determinant of these distortions, and pursuit of appropriately reduced intrinsic efficacy should guide development of safer opioids.