Abstract
Aims:
Cannabis use is highly prevalent in patients seeking treatment for opioid use disorder. Studies have shown mixed results on the association between cannabis use and opioid use as well as the impact of MOUD on cannabis use. The current study aims to investigate the effects of buprenorphine versus naltrexone on cannabis use outcomes in treatment seeking individuals with Opioid Use Disorder (OUD).
Methods:
The current study was based on data from the CTN-0051 X:BOT trial, which compared the opioid relapse-free survival outcomes of two treatment seeking groups, one receiving Extended-Release Naltrexone (XR-naltrexone) (N=283) versus another receiving Buprenorphine-Naloxone (N=287) for OUD. A mixed-effects logistic regression model including treatment assignment (buprenorphine-naloxone vs XR-naltrexone), time, and a time by treatment interaction was run on the sample with the odds of cannabis use as the outcome, as well as two cross-lagged mediation models to explore the prospective mediation of cannabis use on opioid use outcomes (and opioid use on cannabis use outcomes) by treatment assignment during the trial.
Results:
There was a significant effect of buprenorphine treatment on reduced cannabis use. Participants receiving buprenorphine treatment were 39% less likely to use cannabis than those receiving naltrexone over all the timepoints (p=.0499). No significant mediation was found between treatment assignment and opioid use on cannabis use outcomes or between treatment assignment and cannabis use on opioid use outcomes in this trial.
Conclusion:
Participants in this trial receiving buprenorphine treatment for OUD used less cannabis than those receiving naltrexone treatment.
Keywords: Opioid use disorder, cannabis use disorder, Buprenorphine, Naltrexone, timeline follow back, treatment effect
1.0. Introduction
The use of cannabis is prevalent among patients seeking treatment for opioid use disorder, with 24% of people in treatment for opioid use disorder also using cannabis (SAMHSA, 2012, n.d.). Comorbid cannabis use was even more common in patients in treatment trials for OUD (Bawor et al., 2015; Budney et al., 1998).
How medications for opioid use disorder interact with cannabis use is an important question in treatment of individuals with opioid use disorder. The opioid receptor is involved in not only mediating the effect of exogenous opioids but other drugs of abuse as well. The opioid receptor antagonist naltrexone is approved for treatment of alcohol use disorder (Rösner et al., 2010) and some evidence exists for benefits in other substance use disorders (Trivedi et al., 2021). Although less evidence exists for naltrexone for cannabis use disorder (CUD), animal and human lab studies have shown the opioid receptor mediates the reward of cannabis (Cooper & Haney, 2010; Navarro et al., 2001). A human lab study has also shown naltrexone decreases self-administration and drug effect in non-treatment seeking cannabis users(Haney et al., 2015), although another study did not find this decrease (Haney et al., 2003). These human lab studies only include naltrexone effects on cannabis use in a small non-treatment seeking population. No studies have prospectively tested naltrexone or buprenorphine for individuals seeking treatment for cannabis use disorder or in individuals with cannabis use in the OUD population. We therefore considered cannabis use outcomes in a randomized trial of patients with OUD assigned to either naltrexone or buprenorphine.
In treatment of OUD, reduction or cessation of opioid use is the main target, and certain substances such as stimulants have been shown to have adverse effects on outcomes(Foot et al., 2023). However, it is less clear to what extent clinicians should be concerned about cannabis use(Bleyer et al., 2022; Powell et al., 2018). A recent review of 41 studies examining cannabis use on medication for opioid use disorder (MOUD) treatment, including methadone, buprenorphine, and naltrexone found mixed results regarding the relationship between baseline or follow up cannabis use and opioid use disorder treatment outcomes with most trials finding no significant interaction between cannabis use and treatment outcomes (Lake & St. Pierre, 2020). A quantitative meta-analysis combining studies was not possible due to variation of study designs, measures of use, and other outcome measures. There was heterogeneity from a qualitative perspective between findings related to different forms of MOUD (i.e., some buprenorphine studies showed poorer adherence to treatment in individuals who used cannabis, while most naltrexone studies showed better outcomes in individuals using cannabis) although the sample sizes were small in most studies and precluded drawing definitive conclusions. In the case of a randomized trial there is therefore the possibility of a mediating effect of treatment assignment on cannabis use in one arm of the trial leading to improvement or worsening in opioid use disorder or vice versa (changes in opioid use leads to change in cannabis use). In this exploratory study we aimed to determine whether cannabis use differed by treatment assignment (buprenorphine or long acting naltrexone) in a multisite OUD randomized treatment trial. Additionally, we used a cross lagged mediation model to explore possible mediating effects of MOUD treatment assignment on CUD on OUD and vice-versa (i.e., did differences in opioid use by treatment assignment lead to subsequent changes in cannabis use or vice-versa). Previous exploratory analyses have considered the relationship between other illicit substance and alcohol use and opioid use disorder outcomes in this trial, but this analysis is the first to consider the effects of randomized treatment assignment on cannabis use(Bunting et al., 2022; Castillo et al., 2023; Foot et al., 2023; Mintz et al., 2021).
2.0. Materials and Methods
This secondary analysis was based on data from the national Drug Abuse Treatment Clinical Trials Network (CTN-0051) X:BOT Trial. X:BOT was a 24 week randomized comparative effectiveness trial which compared the opioid relapse-free survival outcomes of two groups, one receiving extended-release naltrexone (XR-naltrexone) (N=283) versus another receiving buprenorphine-naloxone (N=287) for OUD. Most participants were between 24–45 years old (mean 34 years old). All were English speaking, with non-prescribed opioid use within the past month, met DSM-5 criteria for OUD, and were seeking agonist-based or antagonist-based treatment for OUD. Participants were recruited from 8 community-based inpatient addiction treatment programs located across the United States. Participants were not eligible if they experienced chronic pain requiring opioids, had a severe comorbid substance use disorder, had serious medical or psychiatric conditions, exhibited suicidal or homicidal ideation, were on methadone maintenance (≥ 30mg per day) at time of consent, had legal complications impacting their ability to complete the trial, or had an allergy or sensitivity to buprenorphine-naloxone or XR-naltrexone. Exclusion criteria also included females who were pregnant, breastfeeding, planning pregnancy, or unwilling to use birth control. The study was approved by the Institutional Review Board of New York University Medical Center. Each of the 8 sites obtained local Institutional Review Board approval, and all participants provided written informed consent.
Eligible, consenting participants were randomly assigned to daily sublingual buprenorphine-naloxone or XR-naltrexone intramuscular injections every 28 days. All participants began the study after admission to inpatient withdrawal management units but before they began medications for opioid use disorder. After consent and enrollment participants were randomized to begin treatment with buprenorphine or XR-naltrexone. For participants assigned to XR-naltrexone, the first injection was given only after a negative naloxone challenge and an opioid negative urine. Withdrawal management was with a methadone or buprenorphine taper, or with non-opioid medications to address symptoms, depending on the treatment site and clinician(Shulman et al., 2021). All patients were seen and evaluated weekly and received weekly medication management counseling from a study physician. Participants also had access to optional outpatient counseling available through the community-based treatment program or elsewhere in the community. XR-naltrexone was the standard 380mg dose injected intramuscularly every 28 days. Daily sublingual buprenorphine-naloxone was increased from 8mg to 24mg per day, as per clinical judgment. Weekly assessments were completed including a self-reported timeline follow back (TLFB) of illicit opioid, cannabis and other substance use, urine toxicology screenings, opioid craving reports, as well as documentation of adverse events.
2.1. Analysis
To determine the effect of treatment assignment (defined as a dichotomous variable based on randomization assignment) on cannabis use outcomes a mixed-effects logistic regression model was run on the full intention to treat sample with the odds of cannabis use as the outcome for weeks 1–24. Since this was a randomized trial, we used an intention to treat definition of treatment assignment even though some participants never started treatment with their assigned medication. The outcome of cannabis use was defined each week as either positive or negative for cannabis use based on self-report on the previous seven days of TLFB. The model included random intercepts for subject and for site, and an AR(1) correlation structure for within-subject observations. The terms included in the model were binary Treatment assignment, Visit week (as a continuous variable) and baseline Cannabis Use (Yes/No). All possible interactions were investigated in the initial model, then non-significant interactions were removed, ultimately leading to a final model where only main effects were present.
We had previously found that individuals assigned to XR-naltrexone were less likely to use opioids compared to those assigned to buprenorphine, likely due to XR-naltrexone’s antagonism of the opioid receptor(Greiner et al., 2021). There was a concern that treatment assignment effects on cannabis use were mediated by this differential opioid use and not a direct effect of the medication assignment or vice versa (cannabis use as a meditator of opioid use). It was also possible this difference in opioid use was mediated by the effects of the assigned treatment on cannabis use. To explore this, we estimated the effect of treatment assignment on previous cannabis and opioid use and the interaction between previous cannabis use and opioid use on current cannabis and opioid use. A cross-lagged mediation model was fit for the first 8 weeks of treatment with a random intercept for site. TLFB Opioid use and TLFB Cannabis use (both binary: Any vs No Use) were modelled for each week from week 1 to week 8, using a logit link function. Each substance use outcome was modelled on treatment group and prior week opioid and cannabis use. For each week, indirect effects were calculated from the effect of treatment group on prior week opioid use (a1) and the effect of prior week opioid use on cannabis use (b1) to yield the indirect effect of treatment on cannabis use through opioid use (figure 1 pathway 1), and from the effect of treatment group on prior week cannabis use (a2) and the effect of prior week cannabis use on opioid use (b2) to yield the indirect effect of treatment on opioid use through cannabis use (figure 1 pathway 2).
Figure 1.
Cross-Lagged Mediation Model Pathways:
A second cross-lagged mediation model was fit for 4 week TLFB substance use with a random intercept for site. TLFB Opioid use and TLFB Cannabis use (again both binary: Any vs No Use) were modelled for each 4-week period, using a logit link function. Each substance use outcome was modelled on treatment group and prior 4 week opioid and cannabis use. For each 4 week period, indirect effects were calculated from the effect of treatment group on prior 4 week opioid use (a1) and the effect of prior 4 week opioid use on cannabis use (b1) to yield the indirect effect of treatment on cannabis use through opioid use, and from the effect of treatment group on prior 4 week cannabis use (a2) and the effect of prior 4 week cannabis use on opioid use (b2) to yield the indirect effect of treatment on opioid use through cannabis use. Additionally, all associations investigated were prospective and not concurrent when looking at opioid use and cannabis use.
3.0. Results
3.1. Participant Characteristics
Of the 569 participants (one subject was excluded due to a lack of baseline TLFB data) included in this analysis, 40.6% used cannabis at baseline (Table 1). Of the 287 participants receiving buprenorphine-naloxone, 42.2% were cannabis users at baseline, and of the 282 participants receiving XR-naltrexone 39% used cannabis at baseline. 73.3% of participants were male, 29.7% were female, and 73.8% of participants were white. 67.5% of all participants reported intravenous (IV) opioid use at baseline, and rates of baseline cannabis use were similar among IV vs non-IV users (40.6% vs. 40.5%).
Table 1.
Baseline Demographics by Baseline Cannabis Use
| Baseline Cannabis (n=231) | No Baseline Cannabis (n=338) | Total (n=569) | ||||||
|---|---|---|---|---|---|---|---|---|
| Variable | n | % | n | % | n | n | ||
| Treatment Group | ||||||||
| buprenorphine-naloxone | 121 | 42.2% | 166 | 57.8% | 287 | 50.4% | ||
| XR-naltrexone | 110 | 39.0% | 172 | 61.0% | 282 | 49.6% | ||
| Induction Status | ||||||||
| Not Inducted | 34 | 35.4% | 62 | 64.6% | 96 | 16.9% | ||
| Inducted | 197 | 41.6% | 276 | 58.4% | 473 | 83.1% | ||
| Site | ||||||||
| Site 1 | 43 | 47.3% | 48 | 52.7% | 91 | 16.0% | ||
| Site 2 | 32 | 41.0% | 46 | 59.0% | 78 | 13.7% | ||
| Site 3 | 21 | 31.8% | 45 | 68.2% | 66 | 11.6% | ||
| Site 4 | 30 | 37.0% | 51 | 63.0% | 81 | 14.2% | ||
| Site 5 | 39 | 42.9% | 52 | 57.1% | 91 | 16.0% | ||
| Site 6 | 36 | 53.7% | 31 | 46.3% | 67 | 11.8% | ||
| Site 7 | 16 | 25.4% | 47 | 74.6% | 63 | 11.1% | ||
| Site 8 | 14 | 43.8% | 18 | 56.3% | 32 | 5.6% | ||
| Gender | ||||||||
| Male | 173 | 43.3% | 227 | 56.8% | 400 | 70.3% | ||
| Female | 58 | 34.3% | 111 | 65.7% | 169 | 29.7% | ||
| Education Level | ||||||||
| <High School | 55 | 41.7% | 77 | 58.3% | 132 | 23.2% | ||
| High School/GED | 84 | 44.2% | 106 | 55.8% | 190 | 33.4% | ||
| >High School | 92 | 37.2% | 155 | 62.8% | 247 | 43.4% | ||
| Race | ||||||||
| White Only | 175 | 41.7% | 245 | 58.3% | 420 | 73.8% | ||
| Black Only | 19 | 33.3% | 38 | 66.7% | 57 | 10.0% | ||
| Other | 37 | 40.2% | 55 | 59.8% | 92 | 16.2% | ||
| IV User | ||||||||
| No | 75 | 40.5% | 110 | 59.5% | 185 | 32.5% | ||
| Yes | 156 | 40.6% | 228 | 59.4% | 384 | 67.5% | ||
| Baseline Urine Toxicology Positive for Cannabis Use | ||||||||
| Negative | 156 | 32.2% | 329 | 67.8% | 485 | 85.2% | ||
| Positive | 75 | 89.3% | 9 | 10.7% | 84 | 14.8% | ||
| Proportion of Days with Cannabis Use at Baseline [Median (IQR)] | 231 | 22% (7%–74%) | 338 | 0% (0%–0%) | 569 | 0% (0%–12%) | ||
3.2. Treatment Effects
As shown in Table 2, there was a significant effect of treatment assignment on cannabis use during the trial, with buprenorphine-naloxone participants having 39% lower odds of cannabis use compared to XR-naltrexone participants (p=.0499), when adjusted for visit and baseline cannabis use. The significant effect of buprenorphine treatment on reduced cannabis use was present while adjusted for baseline cannabis use, and the timing of the visit within the treatment phase of the trial, and the interactions testing for differences by baseline use or visit were non-significant. A significant effect of time was also present, with odds of cannabis use increasing by 6% on average with each additional week in study (p<.0001) after adjustment for treatment group and baseline cannabis use. Additionally, there was a significant effect of baseline cannabis use, with baseline cannabis users having 13.6x the odds of cannabis use during the trial compared to non-users at baseline (p<.0001), adjusted for visit and treatment group.
Table 2.
Significant Predictors of Cannabis Use
| Predictor | Contrast | Estimate | 95% Confidence Limits | |
|---|---|---|---|---|
| Time | Visit (k+1) vs Visit (k) | 1.060 | 1.049 | 1.071 |
| Treatment Assignment | buprenorphine-naloxone vs XR-naltrexone | 0.613 | 0.376 | 1.000 |
| Baseline Use | Baseline Cannabis User vs Baseline Cannabis Non-User | 13.613 | 8.301 | 22.322 |
3.3. Mediation Effects
The cross lagged mediation model fit for weeks 1–8 (Table 3) indicated no significant mediation of treatment effect on opioid use through cannabis use or of treatment effect on cannabis use on opioid use. The additional cross lagged mediation model fit for 4-week periods 1–6 (Table 4) also showed no significant mediation of treatment effect on opioid use through cannabis use or of treatment effect on cannabis use on opioid use. These results highlight the lack of a significant prospective association between opioid use and subsequent cannabis use, and vice versa, in the trial.
Table 3.
Lagged Mediation Effects by Week
| Indirect Effect | Alpha Path | Beta Path | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Path | Week | Est | SE | p | Est | SE | p | Est | SE | p |
| Treatme nt Group -> Cannabi s Use -> Opioid Use | 2 | −0.451 | 12.901 | 0.972 | 1.073 | 48.102 | 0.982 | −0.420 | 6.909 | 0.951 |
| 3 | −0.208 | 3.405 | 0.951 | −0.432 | 12.103 | 0.972 | 0.480 | 5.999 | 0.936 | |
| 4 | −0.085 | 4.080 | 0.983 | −0.155 | 5.075 | 0.976 | 0.547 | 8.530 | 0.949 | |
| 5 | 0.479 | 21.839 | 0.983 | 0.437 | 15.312 | 0.977 | 1.096 | 11.613 | 0.925 | |
| 6 | 0.076 | 71.570 | 0.999 | −0.014 | 13.284 | 0.999 | −5.322 | 61.059 | 0.931 | |
| 7 | 0.091 | 9.227 | 0.992 | 0.430 | 25.034 | 0.986 | 0.211 | 9.258 | 0.982 | |
| 8 | 0.488 | 9.863 | 0.961 | 0.502 | 9.979 | 0.960 | 0.972 | 0.732 | 0.184 | |
| Treatme nt Group ->Opioid Use -> Cannabis Use | 2 | 0.127 | 20.233 | 0.995 | 0.241 | 32.117 | 0.994 | 0.526 | 13.910 | 0.970 |
| 3 | −0.090 | 5.697 | 0.987 | −0.156 | 6.815 | 0.982 | 0.577 | 11.332 | 0.959 | |
| 4 | −0.673 | 7.070 | 0.924 | −1.111 | 28.882 | 0.969 | 0.605 | 11.029 | 0.956 | |
| 5 | 0.147 | 10.429 | 0.989 | 0.078 | 3.900 | 0.984 | 1.891 | 39.395 | 0.962 | |
| 6 | −0.040 | 20.272 | 0.998 | −0.034 | 19.205 | 0.999 | 1.171 | 64.666 | 0.986 | |
| 7 | −0.282 | 21.450 | 0.989 | −0.585 | 79.950 | 0.994 | 0.482 | 102.329 | 0.996 | |
| 8 | −0.516 | 28.970 | 0.986 | −1.011 | 999.999 | 0.999 | 0.510 | 28.641 | 0.986 | |
Table 4.
Lagged Mediation Effects By 4-week Period
| Indirect Effect | Alpha Path | Beta Path | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Path | 4 week period | Est | SE | p | Est | SE | p | Est | SE | p |
| Treatment Group -> Cannabis Use -> Opioid Use | 2 | 0.040 | 0.473 | 0.933 | 0.083 | 1.184 | 0.944 | 0.475 | 1.083 | 0.661 |
| 3 | 0.321 | 0.366 | 0.380 | 0.427 | 0.263 | 0.104 | 0.753 | 1.159 | 0.516 | |
| 4 | −0.031 | 0.200 | 0.876 | 0.272 | 0.811 | 0.737 | −0.114 | 0.622 | 0.854 | |
| 5 | 0.026 | 0.143 | 0.854 | 0.171 | 0.715 | 0.811 | 0.154 | 1.342 | 0.909 | |
| 6 | −0.001 | 0.052 | 0.980 | −0.033 | 0.706 | 0.963 | 0.039 | 0.982 | 0.968 | |
| Treatment Group -> Opioid Use -> Cannabis Use | 2 | 0.084 | 0.106 | 0.431 | −0.311 | 0.905 | 0.731 | −0.270 | 0.797 | 0.735 |
| 3 | −0.219 | 1.085 | 0.840 | −0.851 | 1.374 | 0.536 | 0.257 | 1.609 | 0.873 | |
| 4 | 0.061 | 0.476 | 0.899 | −0.186 | 1.490 | 0.901 | −0.326 | 0.321 | 0.310 | |
| 5 | 0.656 | 5.925 | 0.912 | −0.349 | 2.676 | 0.896 | −1.880 | 2.823 | 0.505 | |
| 6 | −0.306 | 0.935 | 0.744 | −0.209 | 0.581 | 0.719 | 1.462 | 0.608 | 0.016 | |
4.0. Discussion
This study examined the effect of randomization to buprenorphine-naloxone or XR-naltrexone for opioid use disorder on cannabis use outcomes, as well as investigated the mediating effects of changes in cannabis on subsequent opioid use and vice versa. The analysis showed participants randomized to buprenorphine reported significantly less cannabis use during treatment. Cross lagged mediation models indicated no mediation effects between treatment assignment and cannabis use on subsequent opioid use or opioid use on subsequent cannabis use.
The finding that participants receiving buprenorphine for OUD reported less cannabis use compared to participants receiving naltrexone is novel. There is no previous literature investigating the association between buprenorphine as MOUD and its impact on participant cannabis use for an OUD treatment seeking population. A possible explanation for this finding is that buprenorphine’s partial agonism of the opioid receptor provides reinforcement and addresses underlying anxiety or mood problems, therefore patients on buprenorphine may not feel the need to use cannabis, in contrast to those on naltrexone. We also considered the possibility that patients on naltrexone tend to increase cannabis use. Naltrexone was associated with less opioid use over the course of this study (Lee et al., 2018) and produces a strong blockade of opioid effect. It may be the case that some patients on naltrexone, who stop using opioids due to naltrexone’s blockade, substitute cannabis as a drug of choice. We hoped to test this possibility by considering the crossed lagged effects of opioid use on subsequent cannabis use and vice versa. No meaningful evidence was found that it was higher opioid use that mediated the effect of buprenorphine on cannabis use. However, the latter finding may have been due to lack of power and does not definitely mean there is no mediation effect of opioid use on cannabis use.
The finding that cannabis use, but no other substance use, increased over the trial period was previously reported in a description of other illicit substances and alcohol outcomes in the CTN-0051 trial(Bunting et al., 2022). That analysis also noted no association between cannabis use at baseline or in the first four weeks of the trial and later opioid outcomes.
Those findings, along with our findings on the lack of significant mediating effects between opioid use and cannabis use in this study are consistent with previous clinical trial literature(Budney et al., 1998; Hill et al., 2013; Lake & St. Pierre, 2020) and may reflect the complex relationship between the two substances. Studies have shown the cannabinoid and opioid pathways in the brain are interconnected (Flexon et al., 2019; Wiese & Wilson-Poe, 2018; Williams, 2020), although the clinical significance of this interconnectivity is still not clear(Bleyer et al., 2022; Cooper & Haney, 2010; Navarro et al., 2001; Powell et al., 2018). For example, in terms of stimulant use, literature has clearly shown that OUD participants using stimulants who initiate MOUD tend to relapse and have poor treatment outcomes (Tsui et al., 2022,Foot et al., 2023). In contrast, this analysis shows no statistically significant mediation between cannabis use and outcome of MOUD. These findings imply that clinicians treating patients with opioid use disorder with MOUD may not need to view continued use of cannabis as a major risk factor for relapse to opioids, as opposed to stimulants such as crystal methamphetamine, that have shown distinct associations with opioid relapse(Foot et al., 2023), but these findings should be confirmed in larger datasets as the current trial was not designed to test the relationship between cannabis an opioid outcomes and likely was underpowered to detect an interaction.
4.1. Limitations
The findings of this study are an important contribution to literature considering the relationship between CUD and OUD as well as the impact of OUD treatment. However it is crucial to consider that the X:BOT trial, upon which this data was based, was not designed for this analysis. It is possible that our analysis was under powered to provide accurate data on the mediating effects of cannabis on opioid use and the treatment effects of the different forms of MOUD. Additionally, the choice to analyze the cannabis and opioid use mediation data on a week to week and 4-week basis may be excluding mediation effects that are present in shorter time frames, such as on a day-to-day scale. Unfortunately, the original trial in this analysis did not collect data on a daily basis, so testing mediation on a shorter time scale was not possible. Another limitation is that only self-report TLFB data was used to determine cannabis use, although this is commonly used as the primary outcome in cannabis trials due to the long persistence of cannabis in urine after cessation of use. The study also did not assess CUD severity which may be an important factor in treatment outcomes. Lastly, the initial trial did not collect data after relapse or once participants reached primary outcomes. This factor means some long-term data on cannabis use that would have been informative is not available.
5.0. Conclusions
Through this study, based on data from the initial X:BOT trial, it appears that individuals assigned to buprenorphine had modestly less cannabis use than those assigned to naltrexone. Cannabis use increased modestly over the course of the trial, perhaps consistent with some patients substituting cannabis for opioid use after the medications reduce opioid use. There does not appear to be a strong association between cannabis use and opioid use during the trial.
Highlights.
Comorbid cannabis use and OUD is highly prevalent.
This secondary analysis considered cannabis outcomes in the X-BOT randomized trial.
Buprenorphine was associated with reduced cannabis use compared to XR-naltrexone.
No significant mediation between opioid use and cannabis use was found.
Role of Funding Source
The original study and secondary analyses were supported by grants from the National Institute on Drug Abuse (NIDA): UG1 DA013035 and T32 DA007294. Nothing declared.
Declarations of Competing Interest:
Dr. Edward V Nunes has been a Principal Investigator or Co-Investigator on studies that received donated or discounted medication from Alkermes, Inc., Indivior Inc. (formerly Reckitt-Benckiser) and Braeburn-Camurus, Inc. (CAM-2038), and donated digital therapeutic from Pear Therapeutics and CHESS Health. Dr. Nunes has served as an uncompensated consultant to Alkermes, Inc., Braeburn-Camurus Inc., Indivior, and Pear Therapeutics. He has no relevant equity, intellectual property, compensated consulting, travel, or other arrangements with any of these entities.
Dr. John Rotrosen has been a Principal Investigator or a Co-Investigator on studies for which support in the form of donated or discounted medication, smartphone apps, and/or funds has been, or is provided by Alkermes, Inc. (Vivitrol®, extended-release injectable naltrexone), Indivior, Inc. (formerly Reckitt-Benckiser; Suboxone®, buprenorphine/naloxone combination), Braeburn-Camurus, Inc. (extended-release injectable buprenorphine), Pear Therapeutics (smartphone apps ReSET and ReSET-O), CHESS Health (Connections smartphone app), and Data Cubed (smartphone apps SOAR and mSAPPORT). None of this support has gone, or will go, directly to Dr. Rotrosen, rather to either NYU, or to NIDA/NIH, or to NIDA’s contractor The Emmes Company, LLC. Dr. Rotrosen recently served in a non-paid capacity as a member of an Alkermes, Inc. study Steering Committee. He has no relevant equity, intellectual property, compensated consulting, travel or other arrangements with any of these entities.
The remaining authors have no conflicts of interest to report.
Footnotes
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