Impact of Chronic Nabilone Self-administration on Body Weight, Metabolic Markers, Gut Microbiota, and Neural Circuitry in Human Obesity
Phase: PHASE2
Conditions: Obesity
Sponsor: Centre for Addiction and Mental Health

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
1 
 
 
Impact of chronic nabilone self-administration on body weight, metabolic 
markers, gut microbiota, and neural circuitry in human obesity 
 
Protocol Number: 084/2018 
Principal and Qualified Investigator: Bernard Le Foll1,2 
Co-Investigators:  
Dr. Saima Malik3  
(343) 552-2940 
 
 
 
 
Dr. Alain Dagher4  
(514) 398-1726 
Dr. Valerie Taylor5     (416) 323-6400 ext. 4596 
Dr. Sean Wharton6  
(416) 240-7608 
Collaborators: 
Dr. Keith Sharkey7 
(403) 220-4601 
Dr. Michael Surette8    (905) 525-9140 ext. 21964 
Dr. Sofia Chavez9    (416) 535-8501 ext. 34718 
1Department of Psychiatry, University of Toronto, Toronto, ON, Canada 
2Translational Addiction Research Lab, CAMH, Toronto, ON, M5S-2S1 
3Canadian Institutes of Health Research, Ottawa, ON, Canada 
4Montreal Neurological Institute & Hospital, McGill University, Montréal, Québec, Canada  
5Women’s College Hospital, Toronto, Ontario 
6Wharton Medical Clinic for Weight and Diabetes Management, Ontario, Canada 
7Hotchkiss Brain Institute, University of Calgary, Alberta, Canada 
8McMaster University, Ontario, Canada 
9MRI Suite, CAMH, Toronto, ON, M5S-2S1 
Name of the Sponsor: Dr. Bernard Le Foll/Centre for Addiction and Mental Health (CAMH) 
Address of Trial Site: Centre for Addiction and Mental Health (CAMH), 100 Stokes Street and/or 
33 Ursula Franklin Street, Toronto Ontario, M5S 2S1 
_____________________________________________________________________________________ 
The signature below denotes confirmation that this research study will be conducted according to all 
stipulations of the protocol, and according to local legal and regulatory requirements and ICH GCP 
guidelines. 
 
 
___________________________                                  ___________________________ 
PI: Bernard Le Foll, MD PhD                                         Date 
 
 
NCT04801641

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
2 
 
Introduction and Rationale 
Obesity is a serious and growing public health issue. Body Mass Index (BMI) is a common 
diagnostic measure of body fat calculated by dividing an individual’s mass (kg) by the square of 
their height (m2).  As per the standards of the World Health Organization (WHO), a BMI greater 
than or equal to 25 kg/m2 is classified as overweight and a BMI exceeding 30 kg/m2 is categorized 
as obese. The WHO estimates that in 2014, 39% of adults were overweight and 13% were obese 
[1]. Obesity elevates the risk of developing numerous ailments including diabetes mellitus and 
cardiovascular disease, thereby posing a significant economic burden on society [2]. Developing 
therapeutic strategies effective for the treatment of obesity is therefore of tremendous importance. 
The endocannabinoid system has previously been investigated as a possible target for anti-obesity 
drugs. Rimonabant, an inverse agonist of the CB1 receptor developed for managing obesity, was 
effective in producing weight loss. Unfortunately, the presence of this anorectic drug on the 
European market was short-lived due to the high incidence of psychiatric side effects [3]. Like 
Rimonabant, cannabis also targets the CB1 receptor.  We have recently shown that the incidence 
of obesity is reduced in chronic cannabis users [3] and that exposure to the main active ingredient 
of cannabis (i.e. delta-9 tetrahydrocannabinol or THC) reduces the weight of obese animals [4]. 
Here, we would like to explore for the first time the direct impact of a drug that is analog to THC 
called nabilone (used to reduce nausea and vomiting) in human obese subjects. A positive outcome 
may potentially drive the development of novel pharmacological approaches for the treatment of 
this disorder. 
 
Background  
The Endocannabinoid System and Appetite Regulation: The endocannabinoid system comprises 
two cannabinoid receptor subtypes, CB1 and CB2, their corresponding endogenous ligands and 
the processes responsible for their biosynthesis, cellular uptake and metabolism [5-8]. This system 
has been implicated in the regulation of appetitive behavior [9]. Preclinical research reinforces the 
role of the endocannabinoid system in metabolic regulation, and the presence of CB1 receptors in 
the hypothalamus as well as in limbic regions favors the modulation of both homeostatic and 
hedonic feeding by cannabinoids [9, 10]. These receptors may also regulate energy metabolism 
via their distribution in the periphery (e.g. gastrointestinal tract, liver, adipose tissue) [10]. In 
rodents, acute energy intake is increased by CB1 receptor agonists [11], and is inhibited by CB1 
receptor inverse agonists or neutral antagonists [12-16]. In agreement with these findings, acute 
cannabis consumption has been known to stimulate appetite [17], and this has led to the assessment 
of its use for the treatment of HIV/AIDS-related cachexia [18-20]. It is likely that these feeding-
related effects are mediated by cannabis’ primary psychoactive component THC, which is a CB1 
receptor partial agonist.   
 
The Endocannabinoid System and Body Weight: A few years ago, we recognized that there was 
no clear data exploring the relationship between cannabis use and body weight in humans. Using 
data from 2 adult US epidemiological studies, namely the National Epidemiological Survey on 
Alcohol and Related Conditions (NESARC) and the National Comorbidity Survey-Replication 
(NCS-R) study, our group probed the incidence of obesity as a function of cannabis use. 
Surprisingly, the rate of obesity was found to be significantly lower (p<0.001) in frequent (>3 
times/week) self-reported cannabis users (14/ 17%) as compared to individuals who did not use 
cannabis in the last 12 months (22/ 25%) (first value in each set is for NESARC and the second 
for NCS-R) [3]. This effect was retained even post correction for age, sex, and tobacco 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
3 
 
consumption in both data sets (Table 1). Indeed, these findings are impressively robust given the 
large number of respondents in these surveys [3] and have now been duplicated by other groups 
[21-23].  It would appear then that the risk of being overweight or obese decreases as frequency of 
cannabis intake increases [21], as we had initially described. More recently, a lower waist 
circumference has also been reported in current versus former or never users [24]. Interestingly, a 
meta-analysis with eight independent replication samples showed an inverse association between 
active cannabis smoking and diabetes mellitus as well [25]. 
 
 
 
 
 
 
 
 
 
 
Table 1: Association between cannabis use and obesity in multivariate analyses using NESARC 
data (2001-2002).  (Extracted from [3]). 
 
Obesity and the brain: There are multiple factors that contribute to obesity (e.g. excessive food 
intake and lack of physical activity). However, it appears that obesity is also associated with certain 
neurobiological changes. It has been proposed that there is an enhanced endocannabinoid tone in 
this disorder [26-28].  Further, over the last decade, a wealth of information has been obtained on 
the importance of brain dysregulation in obesity, as it can facilitate enhanced desire for food and 
hyper-response to food-cues [29, 30].  Brain imaging technologies such as Blood Oxygen Level 
Dependent (BOLD) MRI has enabled exploration of the neural response to food stimuli in humans 
[31-34]. Indeed, human imaging studies implicate the hypothalamus, limbic, paralimbic, cortical 
and prefrontal brain systems in the regulation of ingestive behavior [31-33, 35]. These systems 
comprise brain regions involved in reward, motivation, emotion, memory and executive control; 
namely the striatum, orbitofrontal cortex, insula, hippocampus, amygdala and prefrontal cortex 
[33-35]. Importantly, responsivity of this network to food cues is modulated by weight status [34-
37]. Obesity is consistently associated with exaggerated or abnormal regional responses to food 
stimuli [34, 36, 38, 39]. Evidence also shows that food cue-triggered brain activation in obesity is 
independent of hunger state, positively correlates with increasing BMI and is altered post-weight 
loss interventions [34, 38, 40, 41]. One MRI investigation showed that a 7-day treatment with the 
anti-obesity drug Rimonabant, a CB1 antagonist, decreased the neural response to hedonic food 
stimuli. Indeed, this may be the mechanism by which Rimonabant drives weight reduction [42]. 
 
Obesity and the Gut Microbiota: The gut microbiota has been tagged to play a role in obesity [43-
46]. Gut microbiota refers to the aggregate of microbial populations inhabiting the gastrointestinal 
tract. It consists mainly of bacterial species and to a much lesser degree, fungal organisms [47-50]. 
Inter-individual variation of the gut microbiota has recently been associated with 126 factors, 63 
of which are diet-related [51]. The gut flora also modulates host metabolism, influencing adiposity 
and energy homeostasis, thereby linking gut microbiota to obesity [52-54]. Relative to 
conventionally-raised (CR) mice, mice reared in the absence of microorganisms (germ-free, GF) 
 NESARC (n=41,633) 
 
 
 
Frequency of Cannabis Use 
Crude 
OR 
95% CI 
 
Adjusted 
OR 
95% CI 
 
No use in the past 12 months 
1 
Reference 
1 
Reference 
More than once a year 
0.71 
(0.54 
0.92) 
0.82 
(0.63 
1.05) 
(less than once a month) 
 
 
 
 
 
 
Once a month to 2 days per week 0.73 
(0.57 
0.93) 
0.79 
(0.62 
1.01) 
3 days per week to every day 
0.59 
(0.44 
0.79) 
0.61 
(0.46 
0.82) 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
4 
 
have significantly less body fat even though their nutrient intake is higher than their CR 
counterparts. Further, when GF mice are populated with gut bacteria from a CR animal, weight 
gain and adiposity are triggered. Extension of this work suggests that microbiota may mediate diet-
induced obesity as GF mice appear to be immune to the effects of a high-fat, high-sugar diet; 
potentially through mechanisms that increase fatty acid metabolism [43, 44]. Animal research has 
additionally shown that obesity-related insulin resistance and inflammation are normalized post 
treatment with broad spectrum antibiotics that reduce gut bacteria in obese mice, favoring a role 
for gut microbiota in glucose homeostasis and inflammation [55]. With the development of 
sophisticated assays, it is now possible to identify and quantify the various bacteria present in the 
microbiota.  Indeed, both preclinical obesity models and clinical research studies, suggest that the 
ratio of Firmicutes to Bacteriodetes, the 2 dominant phyla of the gut, is disrupted in obesity, 
seemingly driven by higher levels of Firmicutes and lower levels of Bacteriodetes [4, 48, 56].   
 
Obesity and Non-Alcoholic Steatohepatitis  
Obese individuals are at an increased risk of developing nonalcoholic fatty liver disease 
(NAFLD) [99]. The accumulation of fat in the liver can lead to inflammation and nonalcoholic 
steatohepatitis (NASH). NASH is characterized by hepatic injury, which can progress to fibrosis 
and cirrhosis. In response to hepatic inflammation and injury, cytokines and chemokines activate 
signaling cascades that mediate fibrogenesis and cirrhosis [100]. These cyto-chemokines could 
potentially represent diagnostic biomarkers for NASH. The endocannabinoid system has been 
implicated in NAFLD and NASH [101]. Epidemiological evidence indicates that cannabis use 
may be protective against NAFLD [102]. 
 
 
Nabilone (a cannabinoid drug similar to THC) 
Nabilone is a pharmaceutical drug product that is a synthetic cannabinoid agonist that is similar to 
THC. Nabilone is sold under the brand name Cesamet. It is approved for management of nausea 
and vomiting associated with cancer chemotherapy (i.e. antiemetic agent). Nabilone is available 
in capsules of 1 mg, 0.5 mg or 0.25 mg. By oral route it is twice as active as THC (see product 
monograph). Two final doses of nabilone (2 mg or 6 mg per day) will be used. These doses were 
chosen as they fall within the recommended daily doses of nabilone as per the product monograph 
(max 6 mg/day); maximum recommended daily dose is included given that the recruited 
participants are obese and thus will require larger doses of nabilone (a highly lipid-soluble 
compound) to achieve therapeutic effects.  
 
Research Question 
Can nabilone pharmacotherapy promote weight loss in obese individuals?   
 
Aims and Hypotheses  
This is a pilot clinical trial to collect preliminary data on the impact of nabilone on various 
outcomes related to obesity. As there is currently no available data on the impact of nabilone in 
obese subjects, this group of investigators would like to collect pilot data as a first step. The results 
of this study will help designing secondarily a fully powered RCT testing the impact of nabilone 
in obese patients. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
5 
 
Aims: 
Primary Aim: To determine the feasibility (e.g. number of completers, nabilone treatment 
adherence) and tolerability (e.g. number of SAEs per treatment group) of 12 weeks of daily 
treatment with nabilone in adults with obesity. 
 
Secondary Aim 1: To compare changes in body weight in individuals with obesity receiving daily 
nabilone treatment versus those receiving the placebo treatment, for 12 weeks.  
 
Secondary Aim 2: To compare changes in abdominal fat in individuals with obesity receiving daily 
nabilone treatment versus those receiving placebo treatment for 12 weeks. 
 
Secondary Aim 3: To explore potential underlying mechanisms by analyzing the following 
between the two groups: metabolic biomarkers (glucose, insulin, triglycerides, cholesterol (total, 
LDL, HDL) and appetite-related peptides (ghrelin, leptin, PYY)), gut microbiota and brain 
response to visual food/control stimuli.  
 
Secondary Aim 4: To compare changes in biomarkers of nonalcoholic steatohepatits in individuals 
with obesity receiving daily nabilone treatment versus those receiving the placebo treatment, for 
12 weeks. 
 
 
Hypothesis:  
We hypothesize that nabilone will be well tolerated with few SAEs in this population. As one of 
our secondary outcomes, we will test for the first time the hypothesis that exposure to nabilone 
versus placebo promotes weight loss in the human obesogenic state. The data collected in this 
study will be used to design a fully powered RCT to test the hypothesis that nabilone is an effective 
pharmacotherapeutic strategy to lower body weight in adults with obesity. 
 
Other secondary objectives will be to collect information on metabolic biomarkers, the 
microbiome, biomarkers of nonalcoholic steatohepatitis, and neural response to food stimuli (in a 
subset of participants), where we expect to find that nabilone versus placebo attenuates the neural 
response to hedonic food stimuli.  
 
Study Design 
Overview: This is a double blinded randomized controlled pilot trial.  Obese participants (n=60) 
will be randomized to three treatment groups: low dose nabilone (n=20), high dose nabilone (n=20) 
or placebo (n=20).  Subjects will self-administer nabilone or placebo orally, for a 12 week period.  
To assess our primary feasibility and tolerability outcomes, we will monitor medication adherence, 
number of completers per treatment group, and medical safety and tolerability for the duration of 
the trial. At baseline and weekly thereafter, body weight will be measured for the secondary 
outcome analysis.  To obtain exploratory data in regards to the potential mechanisms mediating 
any observed changes in weight, subjects will also provide blood and fecal samples to quantify 
blood markers and gut microbiome, respectively, and complete questionnaires at specific time 
points.  Food intake information will also be collected (via Food Frequency Questionnaire (FFQ)).  
Participants will eat their regular meals and itemize the food using a validated form developed by 
the Fred Hutchinson Cancer Research Center [57].  Completed forms (records for 3 days (2 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
6 
 
weekdays, 1 weekend day)) will be collected at each post-enrolment visit.  Participants will also 
be able to opt in to 2 magnetic resonance imaging scan sessions during the course of the trial. 
Standardized dietary modifications and/or exercise-related strategies will be provided to 
complement the pharmacotherapy.    We expect to complete this study in 2 years (30 subjects per 
year).     
 
Participants: Study subjects will be obese adults (males and females) between the ages of 25 and 
45.   Obesity will be defined as a BMI > 30.0 kg/m2.  The maximum weight of the obese 
participants opting in to the imaging component of the trial is capped at 315 lbs due to the weight 
capacity limit of the Magnetic Resonance Imaging scanner. Girth will also be measured to ensure 
fit in the machine (60 cm horizontal, 45 cm vertical). Participants will be assessed to otherwise 
have good general health with no physical or psychiatric disorders.   
 
Recruitment:  
(1) Recruitment will primarily be organized by Dr. Sean Wharton, Medical Director of the 
Wharton Medical Clinic (WMC).  This clinic (with 6 locations in Ontario) caters 
exclusively to individuals that are obese (BMI>30; population of interest for this study), or 
significantly overweight (BMI>27) with co-morbidity.  Several studies have recruited 
individuals with obesity from the WMC or used clinic-generated data in publications 
related to weight or obesity [58, 59].  Logistically, new or returning patients arriving to the 
WMC, who meet basic inclusion criteria, will be approached for study participation by 
WMC staff.  Patients will not be provided weight loss medications during this time.  
 
(2) In addition to the WMC, participants may recruited through general advertising (online or 
posters in the Toronto area).  Other recruitment approaches include: posting on the CAMH 
website (CAMH Research Connect), and sharing/distributing brochures with other obesity 
clinics, hospitals, or community health centres. Written approval (in the form of an email 
or letter from a relevant clinic administrator or other management) will be sought from any 
clinics, hospitals, or community health centres prior to distributing the brochures.   
 
Interventions and Procedures:  
 
Participants will be pre-screened for eligibility by telephone or using the REDCap survey (see 
REDCap section). During pre-screening participants will be deemed eligible to come for Eligibility 
Assessment if they meet the inclusion criteria, and deemed ineligible to come for Eligibility 
Assessment if they report any of the exclusion criteria. 
 
Screening Assessment and Consent:  
Following the review and signing of the Informed Consent Form, the following measures and 
assessments will be administered at the screening visit to confirm eligibility will be performed. If 
the information obtained on all of the measures below is within the specified qualifying range, 
subjects will be enrolled in the study.  The following information will be collected and reviewed 
during this visit: (1) Medical exam including psychiatric evaluation (with family history), (2) Vital 
signs (temperature, blood pressure, heart rate, respiration rate), (3) Height/weight (for BMI 
calculation) and waist circumference, (4) Structured Clinical Interview for DSM V, (5) 12-Lead 
Electrocardiogram, (6) Blood work (complete blood count, glucose, electrolytes, liver enzymes 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
7 
 
(ALT, AST, ALP, GGT), urea, creatinine, etc), (7) Toxicology screen (urine drug cup), (8) Expired 
breath carbon monoxide level (Pico smokerlyzer), (9) Pregnancy testing (females), (10) 
Information on alcohol and caffeinated beverage use (Time Line Follow Back (TLFB) for the past 
one week) [60], (11) Beck Depression Inventory (BDI)  [61], (12) Hamilton Depression Rating 
Scale (HDRS, 21-item version) [62], (13) Questions related to food likes, aversions and/or 
allergies, (14) Pittsburgh Sleep Quality Index (PSQI) [63], (15) Berlin sleep questionnaire (BSQ) 
[64], (16) Eating Attitudes Test (Eat-26 [65], and (17) MRI eligibility to assess there are no MRI 
scanning contraindications. Selective questionnaires will serve as “baseline data” whereby repeat 
administration during the trial will facilitate comparison post-dosing.  These data (BDI, HDRS, 
PSQI, and/or BSQ) will contribute to the assessment of tolerability of nabilone pharmacotherapy 
for obesity (e.g. nabilone-induced changes in mood or sleep patterns). 
 
Randomization:  
CAMH’s pharmacy will establish the randomization code and maintain the blind. Once enrolled, 
subjects will be randomized into one of three study arms: (1) low dose nabilone (2 mg/day), high 
dose nabilone (6 mg/day) or (3) placebo. 2 randomization tables will be created with 30 codes in 
each, one table for females and one for males. Each table will have 2 blocks of 15. In each block, 
the assignments will be equally distributed between low dose, high dose and placebo (1:1:1). 
 
After each participant is randomized and assigned a code, an emergency unblinding envelop will 
be created by the pharmacy. Envelops will be sealed with tamper proof tape. The envelope is sent 
to the night cabinet/ADU at Queen Street.  
 
If an emergency occurs during pharmacy hours, the QI or delegate will contact research pharmacy 
staff to unblind the code for that participant. In the event of an emergency after hours, the QI or 
delegate will contact the after hours site manager at Queen Street who will go to the night 
cabinet/ADU and open the envelop to unblind the code. 
 
Subjects and research team will be blinded.  Notably, during the course of the trial (during the final 
study visit) we will administer a questionnaire asking participants whether they believe they are 
consuming placebo or active product.  i.e. their perception of the design. 
 
Study Visits: 
In addition to the screening assessment, there will be a total of 14 study visits.  The first post-
enrolment visit will involve the pickup of a stool specimen collection kit and the first food 
frequency questionnaire. For those opting in to the imaging component a brief mock MRI session 
will be conducted at the screening or first post-enrolment visit to make sure that participants will 
be comfortable in the space. Thereafter there will be 13 study visits, each ~1 week apart. For those 
opting in to the imaging component of the trial there will be two MRI scans scheduled within the 
study visits. At all of the 13 visits: The following information will be collected: Height/weight 
measurements, waist circumference, FFQ from previous week, vitals, AEs/ medical monitoring 
(SAFTEE scale (validated method for the systematic assessment of side effects in clinical trials) 
[65] and general inquiries by health professional), alcohol and caffeinated beverage use (TLFB for 
the past week [60]), toxicology screen (via urine drug cup), urine pregnancy test (females), visual 
analog scales to measure mood and appetite, BDI, HDRS, PSQI, BSQ and EAT-26.  Visit 1:  For 
those opting in, subjects will undergo their first MRI scan (baseline) with up to 1.5 hours of 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
8 
 
acquisition. Subjects will bring in their first fecal sample for microbiome analysis. Subjects will 
be dispensed a 1 week supply of drug or placebo.  A blood sample will be drawn that could be 
used to measure levels of nabilone, endocannabinoids and specific metabolic biomarkers (glucose, 
insulin, cholesterol (total, LDL, HDL), triglycerides, ghrelin, leptin and PYY). The sample will 
also be used to measure levels of 7 cyto-chemokines (i.e. adiponectin, tumor necrosis factor, CL-
2, IL-17, IL-23, IL-37, and MCP) as biomarkers of NASH. Visits 2 to 12: A one week supply of 
product/placebo will be dispensed.  Visits 5 and 9: Blood samples will be drawn to quantify 
measures listed in Visit 1. Visit 12: For those opting in, subjects will undergo their second MRI 
scan with up to 1.5 hours of acquisition. This visit will occur while subjects are still under 
treatment. Ideally, this visit will occur 1 week after visit 11; however, due to scheduling (both 
participant and MRI availability), a margin of approximately ±3 days will be allowed. Subjects 
will bring in their 2nd fecal sample.  A blood sample will be drawn to quantify measures listed in 
Visit 1 as well as routine blood measures from the eligibility assessment (complete blood count, 
glucose, electrolytes, liver/heart enzymes, urea, creatinine, etc).  Visit 13: This visit will be post 
treatment completion. Subjects will return their excess capsules, last food intake form, be 
examined, compensated and discharged.   
 
Primary Endpoint:  
Feasibility (number of completers and medication adherence per treatment group) and tolerability 
(number of SAEs per group) 
 
Secondary Endpoint 1: 
Change in body weight over 12 week period to assess efficacy of nabilone as weight loss agent.  
 
Secondary Endpoint 2:  
Change in abdominal fat over 12 weeks in those participants opting in to the imaging component 
of the study. 
 
Secondary Endpoint 3:  
Exploration of underlying mechanisms of obesity by comparing changes in metabolic biomarkers, 
appetite-related peptides, gut microbiota, and response to visual food/control stimuli between 
groups over 12 week period. 
Secondary Endpoint 4: 
Change in levels of cyto-chemokines as biomarkers of nonalcoholic steatohepatitis over 12 weeks. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
9 
 
 
Overview of Study Visits: 
 
 
 
Imaging Sessions: 
If subjects consent for the optional imaging component of the study, they will be scheduled for the 
two MRI session (Visit 1 and Visit 12) described above. These sessions will include a brain fMRI 
scan and abdominal imaging. Brain MRI acquisition: Consenting subjects will undergo two BOLD 
functional MRI scans at the Centre for Addiction and Mental Health. The first scan will be prior 
to initiation of treatment and the second, after the 11th week (and before the end of the 12th week) 
of dosing. Subjects will be scanned at the same time of day, after overnight fasting followed by 
breakfast consumed 4 hours prior to scans. Participants will be instructed what to consume for 
breakfast during scheduling of their study sessions and will record the contents of their breakfast 
In-Person 
Screening/
Eligibility
Post-
Enrollment 
Session
1
2
3
4
5
6
7
8
9
10
11
12
13/Discharge
ICF
X
Eligibility 
Assessment
X
Mock MRI 
Session
X
Stool Collection 
Kit Pickup
X
X
Stool Sample 
Drop-Off
X
X
Blood Draw
X
X
X
X
X
Genetic 
Sampling Blood 
Draw
X
Baseline MRI 
Scan
X
Final MRI scan
X
FFQ
X
X
X
X
X
X
X
X
X
X
X
X
X
1 week supply 
of capsules 
provided
X
X
X
X
X
X
X
X
X
X
X
X
Return Excess 
Capsules
X
Submit Final 
FFQ
X
Examination & 
Discharge
X
To be completed weekly at  13 Post-Enrollment Sessions: Height/weight measurements, waist 
circumference, FFQ from previous week, vitals, AE log, TLFB (alcohol & caffeine), toxicology, 
pregnancy test, VAS to measure mood & appetite, BDI, HDRS, PSQI, BSQ, EAT-26
Assessment & Measures
Post-Enrollment

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
10 
 
in the FFQ. .  Each imaging session will last approximately 1.5 hours in length.  Following a high-
resolution structural scan, BOLD data will be collected. Details of this BOLD paradigm have 
previously been described [31, 32]. Briefly, the BOLD imaging protocol will consist of multiple 
functional runs in which food and control picture stimuli will be presented, using a block design. 
In addition, we will administer an auction task to assess monetary valuation of the food items 
presented in the images. Subjects will also be asked to respond to questions regarding their mood 
and appetite (e.g. how hungry are you right now?) on a 10 point visual analog scale.  Presentation 
software will be used for stimulus presentation. Participants will view the same set of images.  
Compliance with the task will be monitored using in-bore cameras. Following the BOLD 
sequence, Arterial Spin Labelling will be performed to measure brain perfusion.  Abdominal 
imaging: MRI is considered the gold standard for measuring body composition [66, 67]. We will 
use an abdominal coil and a state-of-the-art water-triglyceride fat separation method available on 
our scanner that uses a chemical-shift-based, three-dimensional, volumetric pulse sequence. It 
enables accurate estimation of relative triglyceride fat fraction maps by correcting for T2* and 
performing multi-peak fat spectrum modeling [68, 69]. Both subcutaneous and visceral fat will be 
measured. If time permits, we will also incorporate quantitative T1 mapping, which has been used 
to improve segmentation [70] and better characterize adipose tissue [71] since qT1 is sensitive to 
cell swelling, among other things. 
 
Investigational Pulse Sequences: The CAMH MRI Unit is a research site, and one of our mandates 
is to develop and test new MRI pulse sequences that will advance our understanding of brain 
function and structure.  CAMH has established a research agreement with General Electric (GE) 
to help achieve these goals.  This research agreement allows us to modify the stock pulse sequences 
to generate higher quality data, and to operate the scanner in “research mode”, which gives us the 
ability to alter certain parameters of the stock pulse sequences. MRI machines are designed to 
operate with patient safety in mind.  Our GE MR750 has three operating levels: Normal Level, 
First Level and Second Level.  All GE scanners in Canada can operate in Normal and First Level 
mode, and ours is operated at First Level mode for all studies.  Second Level mode is available 
only if a research agreement is in place with GE and REB approval is in place for any changes to 
safety thresholds beyond First Level.  No studies at CAMH are operated at Second Level.  When 
a pulse sequence is prescribed and loaded into memory, the scanner determines whether the 
parameters selected will exceed the safety limits for First Level.  If they do, the scanner will not 
allow the scan to proceed as prescribed, and the technologist must change the parameters so that 
the First Level limits are not exceeded. Some of the images we collect use new methods or 
“investigational” protocols that we have developed.  These do not pose any additional risk to the 
participant – we can only acquire the images if we are within the established safety limits. The 
additional sequences will not impact the overall duration of time the participant will spend in the 
scanner. In addition, these sequences are being added as exploratory outcomes and will not affect 
the study endpoints. Any software associated with investigational sequences will be installed and 
maintained by the PI of this study. 
 
Diet and Fitness Strategies 
Standardized dietary modifications and/or exercise-related strategies will be provided to 
complement the pharmacotherapy.  The Wharton Medical Clinic will assist with this aspect of the 
study. 
 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
11 
 
Pharmacotherapy: Treatment and Dosing: 
Generic nabilone (0.5 mg pms-nabilone) will be purchased through the CAMH Pharmacy and 
placebo will be prepared by CAMH Pharmacy. The formulation will be capsules (0.5 mg 
nabilone/capsule), which will be dispensed by the CAMH research pharmacy. One week’s supply 
of capsules will be provided to participants at each weekly visit. Quantity of nabilone/placebo 
capsules provided to participants will be measured and compared to that at end of each week to 
monitor participant compliance. Two final doses of nabilone (2 and 6 mg/day) will be used. The 
nabilone dose in all non-placebo arm subjects will be titrated up to 2 mg/day (1 mg twice a day, in 
the morning and at bedtime) over a 1 week period: 2 capsules at bedtime for 3 days then addition 
of 2 capsules in the morning for the following 4 days. Thereafter, low-dose participants will be 
maintained on the 2 mg/day regimen and high-dose participants will be escalated to 6 mg/day (3 
mg, twice a day): addition of 4 capsules at bedtime for 3 days then addition of 4 capsules in the 
morning for the following 4 days. There will be no down-titration as this is not usually done in 
nabilone trials. 
 
All subjects will take 12 capsules each day, 6 in the morning and 6 at bedtime: placebo arm will 
take 6 placebo capsules in the morning and 6 at bedtime, low dose nabilone group will take 2 
nabilone and 4 placebo capsules in the morning and 2 nabilone and 4 placebo  capsules at bedtime, 
and high dose nabilone group will take 6 nabilone capsules in the morning and 6 at bedtime. 
Subjects will be instructed to consume nabilone/placebo capsules daily for a period of 12 weeks.   
 
Genetic Sampling: 
Participants will be asked to review an additional consent form that will ask if they are willing to 
provide an extra blood sample (~20 mL) for a future genetic analysis experiment that could aid in 
furthering this research. Blood will be drawn during the first weekly visit, during the routine blood 
draw. Genetic areas of interest will be identified and genotyping will be done using standard 
molecular biology techniques to analyze the genetic makeup of these areas of interest. Genetic 
testing will be performed at CAMH and/or with external collaborators. Samples are stored and de-
identified without any personal health information. Samples will be destroyed within 20 years of 
the study start. If the Principal Investigator moves or retires, the samples will be either transferred 
or destroyed. These samples may be shared with external collaborators for the purposes of pooling 
data (e.g., ENIGMA). No feedback regarding genotyping results will be given back to the 
participants. Participants may choose not to participate as this will have no influence on the rest of 
the study.  
 
Accountability Procedures: 
The nabilone capsules (Drug Identification Number 02380900) will be purchased through the 
CAMH Pharmacy and transported to CAMH pharmacy following the manufacturer requirements 
(e.g. for handling, transport, and storage) in order to maintain the stability of the investigational 
product as per the Product Monograph. Storage and handling procedures will be documented by 
CAMH pharmacy as applicable and will be in accordance with the Product Monograph (i.e. 
nabilone will be stored at stable room temperature of 15-30°C). The nabilone presents as a white 
crystalline powder and is formulated into No. 4 hard gelatin capsules with opaque red cap and 
white body.  
 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
12 
 
The placebo capsules will be packaged the same way as the nabilone capsules and participants will 
not be able to tell whether they are receiving active or placebo. CAMH pharmacy will maintain 
drug accountability logs for both active and placebo, in addition to subject dispensing logs as per 
CAMH pharmacy SOP. Regular reconciliation checks of investigational product and placebo 
between CAMH pharmacy and study staff will take place during the study. At the end of the study, 
there will be a final reconciliation (shipped, used, and remaining) and any discrepancies noted will 
be investigated, resolved, and documented. Unused investigational product will be destroyed and 
documentation of destruction will be retained in the study files. 
 
Subject Eligibility Criteria 
Inclusion criteria:  
 Obese adults (BMI > 30.0 kg/m2).  
 Males and females   
 Aged between 25 and 45  
 For the optional imaging component of the study, a maximum weight (315 lbs) and a 
maximum girth in line with capacity of the machine (60 cm horizontal and 45 cm vertical; 
therefore, circumference of scanner is 166.6 cm) 
 For women of reproductive potential (WORP) and men whose sexual partners are WORP: 
use of adequate methods of contraception (effective barrier methods such as male condoms, 
female condoms, cervical caps, diaphragms, or contraceptive sponges; and highly effective 
methods of contraception such as oral hormonal contraceptives, intrauterine devices 
(IUDs), vasectomy, or tubal ligation) 
 AST/ALT, bilirubin, and kidney function tests within normal limits at screening.  
  
Exclusion criteria: 
 Unstable gastrointestinal, respiratory, endocrinological, cardiovascular or cerebrovascular 
diseases that would prevent participation in the trial at QI (or its delegate) discretion, 
 Unstable major psychiatric disorder(s) (i.e. Axis I Disorders) that would prevent 
participation in the trial at QI (or its delegate) discretion,  
 Current substance use disorders (DSM-V) (excluding tobacco and caffeine), 
 History of, or current neurological illnesses, that would prevent participation in the trial, 
 Current use or use during the previous month of antipsychotic medications, 
 Learning disability, amnesia or other conditions that impede memory and attention, 
 Visual impairments that prevent participation in the study,  
 Personal or family history of schizophrenia, or psychosis (or psychosis-related)  disorders,  
 Antibiotic use in the last 4 weeks,  
 Previous bariatric surgery,  
 Current use or use in the past month of other weight-loss pharmaceuticals,  
 Cannabis use in last 6 months,  
 Known sensitivity to cannabis or other cannabinoid agents, 
 Pregnancy or lactation (females), and 
 For the optional imaging component of the study: 
o Presence of metal implants or objects unsafe for MRI such as cardiac pacemakers, 
metal fragments in the eye, and aneurysm clips in your brain 
o Piercings or jewelry that are unable to be removed 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
13 
 
o Tattoos inked with metal dyes 
Concomitant medications: 
The following medications are contraindicated: 
 Antipsychotic medications 
 Weight-loss pharmaceuticals 
 Cannabis 
 Medications that would affect participant safety in trial as assessed by the Qualified 
Investigator 
 
In addition, antibiotics are a relative contraindication at the discretion of the QI. 
 
Based on the product monograph, there is a potential for interactions between nabilone and 
diazepam, sodium secobarbital, alcohol, and codeine. Thus, participants will be instructed not to 
take nabilone with alcohol or any sedative-hypnotics or other psychotomimetic substances. 
 
Screened participants’ medications, treatments, and procedures both past and present will be 
assessed by the Qualified Investigator. Permission to enroll and partake in the study will be up to 
the discretion of the Qualified Investigator. 
 
Rescue Medication: In the event of adverse side effects to the nabilone, appropriate management 
will be provided to the participant. No rescue medications will be used. 
 
Consent 
All subjects will provide written informed consent prior to study enrolment.  i.e. before undergoing 
any study-related procedures. 
 
Data Collection 
Data for this study will be collected via paper forms and/or using REDCap.  Any documents from 
the participant binder including questionnaires completed by the participants and information 
collected by study personnel using data collection tools will be considered source documents. 
REDCap may be used as an electronic data capture tool and data collected directly on REDCap 
will also be considered as source. If REDCap is implemented, all necessary procedures will be 
followed to ensure compliance with guidelines for regulated studies. 
 
The study results will be stored under a REDCap database in the Krembil Center for 
Neuroinformatics at CAMH. This will allow us to perform analysis combining multiple modalities 
(phenotype, genetic, imaging) and to compare with other samples collected either by CAMH 
investigators or by international collaborators. Anonymized data may be shared with other 
consortiums of investigators for analysis. 
 
REDCap may be used for electronic data capture. If it is, no personal health information will be 
entered into REDCap except for a Project that contains only Personal Identifiable Information 
(PII). The PII collected will consist of name and phone number or email address. The purpose of 
collecting this PII will be to contact the participant after the screening survey. The participant will 
access the survey via a provided URL and complete the initial screen. This screen will be piped to 
a separate project that contains only the PII. No data will be stored with the PII. The screening 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
14 
 
survey and PII survey will be linked by piping the participant ID from the screening survey to a 
unique field code in the PII survey. The use of a REDCap survey will facilitate recruitment because 
it will provide participants with an efficient means of preliminary screening.  It can be problematic 
to reach by telephone after answering an advertisement because participants often do not answer 
the phone when the call number is not known. REDCap may be used as Source Documents and 
CRFs. 
 
Sample Size and Power Calculation 
Our proposed ‘pilot’ sample size is 60 completers (placebo (n=20), low dose nabilone (n=20) and 
high dose nabilone (n=20)).  Combining mice data showing that chronic treatment with both THC 
[4] and SR141716 (Rimonabant) [72], reduced energy intake and prevented diet-induced obesity 
(with the response being ~36% greater with Rimonabant), with a 1 year controlled human 
Rimonabant trial promoting weight reduction [73], we performed a power calculation.  A sample 
of 20 completers (high dose nabilone) was found to be sufficient to achieve 45% power to detect 
an effect equivalent to a drop of 3.0% in the nabilone arm as compared to a drop of 1.8% in the 
placebo arm.  The power analysis was conducted based on a series of Mont Carlo simulations 
where synthetic data was generated that mimic the change in the outcome that we expect to find 
in our trial, and mixed effect models are adjusted to each replication, with the power being defined 
as the proportion of the replications in which the specified effect was detected. 5000 replications 
were generated for each sample size.  The analysis also assumed a significance level of 0.05, two 
tailed tests and a correlation between baseline and post of 0.9.  We are confident that this pilot 
study will not only generate an ‘effect’ but will also yield preliminary safety and feasibility data 
regarding the use of nabilone for obesity, facilitating a larger trial. 
 
Data Analysis 
An initial descriptive and exploratory analysis of the sample will be performed where differences 
between groups at baseline will be accessed with chi-square tests for categorical variables and 
One-way ANOVA for continuous variables.  Non-parametric tests may be used if the normality 
assumption is found to be violated. This approach will be taken to test the primary aims of the 
study (feasibility and tolerability).  A mixed effect model, where subject is the random effect and 
treatment (Nabilone/Placebo), time (baseline, week 1, week 2 …week 12) and treatment by time 
interaction will enter the model as categorical fixed effect.  The hypothesis that nabilone will 
reduce body weight in adults with obesity will be tested by a contrast that involves the interaction 
term and compares both treatments regarding their weight at week 12 versus weight at baseline.  
Intention to Treat analysis will be used and drop-outs will not be removed from the analysis.  
Mixed Effect models can handle missing values through full maximum likelihood estimation 
which does not drop any subject but rather uses all available information.  Missing values analysis 
will be conducted by comparing drop-outs with completers in terms of their baseline information.  
Waist circumference data will be analyzed in a similar fashion.  Glucose, insulin, cholesterol, 
triglycerides, ghrelin, PYY, leptin, endocannabinoids, and/or nabilone between the 3 groups 
(low/high dose nabilone and placebo), at the 4 time points will be analyzed using a repeated 
measures ANOVA. Repeated measures ANOVA will also be employed to examine the microbiota 
data.  The criterion for significance for all analyses will be a two-tailed alpha of 0.05.  
Questionnaire data will be scored as per the validated guidelines of the specific questionnaire 
(references previously provided).  Food intake data will be analyzed using NUTRITIONIST 
PRO™ DIET ANALYSIS SOFTWARE (Axxya Systems) to assess the intake of macro- and 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
15 
 
micronutrients.  Depending on the findings, exploratory regression analyses (using general linear 
models) will be applied to study the relationship between body weight and microbiome, food 
intake and/or metabolic (markers) data.  AEs will be compiled and analyzed as per our previously 
published clinical trial with Sativex [74].  Sex and age will be used as covariates in the analysis 
process.  SPSS (SPSS Inc., IL, USA) and/or Graphpad Prism will be used to conduct the analyses 
and for graphing.  Interim data analysis may occur.   
 
Imaging data analysis: BOLD fMRI analyses have been described in detail before [31, 32].  
Briefly, functional BOLD images will be spatially smoothed with a 6 mm Gaussian filter and 
motion corrected. A general linear model will then be designed using separate regressors for food 
and control pictures, consisting of boxcar functions convolved with a standard hemodynamic 
response function. Regional brain activation will be determined by calculating a contrast of food 
minus control and generating effect and standard deviation at each brain voxel for each individual. 
These parametric images will be transformed into Montreal Neurological Institute space [75] and 
a group analysis conducted using a mixed effects statistical model. Using SPM, individual T-maps 
will be corrected for multiple comparisons by exclusively listing brain regions containing clusters 
of voxels with p < 0.001 and a volume > 100 ml. This will effectively reduce the risk of false 
positives to less than 1 in 20 (i.e., p < 0.05) for the study. Significant peaks in MNI coordinates 
will be identified and reported in tables with corresponding t-values.  ASL data will be analyzed 
as per validated methods [76-81]. Change from baseline abdominal fat imaging data will be 
assessed between nabilone and placebo groups. 
  
Microbiome Profiling: Microbiome profiling will be performed at two time points: (1) before 
pharmacological intervention and (2) during the later part of the intervention phase.  Shotgun 
metagenomic libraries will be constructed using standard protocols and paired-end sequencing 
(2x150nt) will be carried out on an Illumina HiSeq at 30x106 reads/ sample. Sequences will be 
processed through in-house bioinformatics pipelines to remove low quality sequence and human 
DNA.  Filtered reads will be assembled using metaSPades [89] and binned using MetaBat [90]. 
Bins will be evaluated using CheckM [91] and taxonomy assigned using Kraken [92].  Assembled 
contigs and bins will be annotated using Prokka [93]. Raw (filtered) reads will also be evaluated 
for genes and functional predictions and comparisons across sample groups will be computed using 
HUMAnN [94].  All analyses will occur under the direction of collaborator Dr. Michael Surette, 
Director of both the McMaster Genomics Facility and the Laboratory of Interdisciplinary 
Microbiome Research.   
 
Study Monitoring and Access to Study Documents  
The PI/ QI will permit trial-related monitoring, audits, REB review, and/or regulatory inspections, 
by providing direct access to source data/documents. This will be mentioned in the Informed 
Consent Form.  Monitoring will be conducted according to the study monitoring plan. 
 
Ethical Considerations 
Prior to study start, the Investigator will address all review comments from the CAMH REB to the 
satisfaction of the CAMH REB. The Investigator will also obtain approval from Health Canada, 
then obtain final approval from the CAMH REB as well as meeting all other Health Canada 
requirements for initiating the study (Clinical Trial Site Information Form). 
 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
16 
 
Risks and Inconveniences 
Blood Collection: Blood collection may cause some bruising and discomfort at the site of needle 
stick, and rarely, a small infection at the skin puncture site. These risks are minimized by using 
proper techniques. 
 
MRI: Study staff will conduct MRI safety screening to determine whether it is safe for the 
participant to be scanned. Some people may feel uncomfortable lying still in the confined space of 
the MRI scanner. A mock MRI session will be conducted to consenting participants. Tingling 
sensations are felt by some people during certain scans or occasionally, some participants feel 
dizzy for a few minutes at the end of the MRI study.  These are infrequent, but expected sensations. 
In the case of an incidental finding arising from imaging, the procedures in the MRI Unit Incidental 
Findings Policy will be followed. 
 
Cannabinoid exposure: Acute and chronic exposure to cannabinoids (recreational or medicinal) 
has been reported to have adverse effects, including the possibility of addiction [95-98].  However, 
a Canadian systematic review examining adverse effects of medical cannabinoids found that in 23 
randomized controlled trials with oral or oromucosal administration, 96.6% of the adverse events 
(AEs) were not serious, with dizziness being the most frequently reported in the cannabinoid-
exposed arm.  Of the serious AEs (SAEs), the most common were relapse of a previous medical 
condition (e.g. multiple sclerosis), vomiting and urinary tract infection.  Notably, the rate of non-
serious AEs was higher in the cannabinoid-exposed group than controls but did not significantly 
differ between groups for SAEs.  The range of cannabinoid exposure was 8 hours to 12 months 
(median: 2 weeks) [98]. As per the nabilone Product Monograph, the most commonly observed 
adverse reactions to nabilone as reported in the course of clinical trials include drowsiness, vertigo, 
psychological high (e.g. euphoria), dry mouth, depression, psychomotor impairment, blurred 
vision, and sensation disturbance. In addition, the following rare AEs have been reported in less 
than 1% of patients administered nabilone in previous clinical trials: tachycardia, tremors, syncope, 
nightmares, distortion in the perception of time, confusion, dissociation, dysphoria, psychotic 
reactions and seizures. Weekly medical monitoring will allow the ongoing assessment of the any 
emerging effects of the pharmacotherapy.  Any medical events will be promptly evaluated by the 
QI.  Further, participants will be provided a physician contact card for any urgent medical inquiries. 
 
Questionnaires:  There are no risks associated with the questionnaires, except possibly fatigue.  
Breaks will be provided as required.    
 
Benefit to participants: Should the nabilone pharmacotherapy be successful for weight loss, obese 
subjects will directly benefit from participation in the study.   
 
Study Documentation 
Investigators will retain a participant identification code list if they need to contact participants 
after the study. This list will contain the complete name, identification number, address, phone 
number and email of all participants and will be held confidentially at the investigator’s site after 
completion of the study. 
 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
17 
 
Archiving of Study Documentation 
Study data and other essential documents will be retained in a secure setting by the investigators for 
a period of 15 years as required by current regulations. 
 
Confidentiality 
All personal study participant data collected and processed for the purposes of this study will be 
managed by the investigators and their research staff with adequate precautions to ensure the 
confidentiality of this data, and in accordance with applicable national and local laws and 
regulations on personal data protection. The Ethics Committees approving this research, monitors 
and Health Canada will be granted direct access to all source documents for verification of clinical 
trial procedures and/or data, without violating the confidentiality of the participants, to the extent 
permitted by the law and regulations. In any presentation of study results (at meetings or in 
publications), participant identity will remain confidential. 
 
Participant Safety and Adverse Events 
As nabilone is already an approved drug and is available on the Canadian market, this is not a 
safety study. However, the occurrence of adverse events resulting from study-related 
pharmacotherapy is a possibility.  In this proposed 12 week study, possible side effects will be 
monitored on a weekly basis in accordance with GCP, and subjects will be advised to seek prompt 
medical attention for any (serious) adverse effects.  Further, the Qualified Investigator (QI) will 
ensure patient safety. Potential safety concerns and associated solutions will be discussed at regular 
study meetings.  The QI (along with any medical professionals delegated by the QI) will monitor, 
treat and follow-up on any emerging side/adverse effects.  In the event of AEs, the QI will 
determine severity and expectedness of the event along with any causal association to the study 
interventions.  A physician contact card will also be provided.   
 
Additional Safety Procedures: 
1. Participants will be provided with the QI contact information, in case of any unexpected 
side effects.  
2. If necessary, the participants will be transferred home via taxi. 
 
Adverse Events Reporting 
AEs will be assessed at each study visit.  Study staff will question the subject directly asking: how 
they are feeling and how have they have been feeling since their last visit.  All AEs, whether 
reported by the subject or observed by study staff/investigators, will be recorded on the AE log 
along with a brief description, start date/resolution date and any action taken.  The AE log will be 
initialed by the QI, who will make the determination on relationship of the AE to the 
investigational drug/study procedures. All unexpected AEs determined by the QI to have a causal 
relationship with the investigational product or as a result of study procedures, will be reported to 
CAMH REB as part of the annual ethics approval renewal process.  Study personnel will manage 
and report AEs as per CAMH’s Standard Operating Procedures.    
   
AEs and SAEs will be reported to the REB consistent with their policy. The Qualified 
Investigator will report all Serious and Unexpected Adverse Drug Reactions (SUADR) to Health 
Canada as per Division 5 regulations. All AEs (including SUADRs) will be recorded and 
described in the AE log.  

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
18 
 
 
Type and duration of the follow-up of subjects after adverse event: The Qualified 
Investigator is responsible for determining the duration of follow-up required for any adverse 
event dependent on the seriousness of the event. AEs will be followed to resolution if possible. 
 
Termination of the Study 
Reasons for withdrawing individual subjects from the study may include one or more of the following: 
1) 
Failure to continue to meet inclusion criteria; 
2) 
Severe side effects related to pharmacotherapy; 
3) 
Major protocol violation; 
4) 
Subject lost to follow-up; 
5) 
Withdrawal of consent; 
6) 
Pregnancy 
 
Notably, any subject may be discontinued from the study at the discretion of the Qualified Investigator 
if it is deemed to be in the best interest of the subject.   
 
Sixty participants will be enrolled.  Dropouts or withdrawn participants will not be replaced. 
Enrolment will continue until the recruitment target is met or the trial is stopped. Participants 
withdrawing from the study will be contacted by the study research team requesting to follow up 
with any unresolved adverse events. Once withdrawn from the study, no further study data will be 
collected. However, every effort will be made to obtain permission to document the reason for 
withdrawal. Data collected until the time of withdrawal/dropout may be used in analyses.   
 
Follow-up for subjects withdrawn from investigational product treatment/trial treatment: The 
Qualified Investigator will determine the duration of follow-up required for subjects withdrawn 
from investigational product treatment/trial treatment (e.g. if the reason is any adverse event 
dependent on the seriousness of the event). 
 
Criteria for the Termination of the Trial 
The study will be terminated upon completion of the recruitment targets.  The study may also be 
terminated due to adverse events or at the discretion of the QI/Sponsor. 
 
Funding 
This study is funded by the Physician Services Incorporated Foundation and a Canadian Institutes of 
Health Research (CIHR) Catalyst Grant.    
 
 Participant Compensation 
 
1 Assessment visit: $35 
1 Pick-up Visit: $10 
9 Routine Visits: $180 ($20/ visit) 
4 Routine Visits with blood sampling $140 ($35 per visit) 
2 Imaging Sessions: $230 ($115 per visit) 
1 Genetic Sampling blood draw: $25 
Should participants have to come in for any extra time they will be compensated $15/hour.    

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
19 
 
 
TOTAL: $620 
 (Taxi vouchers or tokens will be provided when/if needed). 
 
 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
20 
 
References 
1. 
World Health Organization. Obesity and overweight Fact Sheet No 311, 
http://www.who.int/mediacentre/factsheets/fs311/en/. 2015 January 2015. 
2. 
Spieker, E.A. and N. Pyzocha, Economic Impact of Obesity. Prim Care, 2016. 43(1): p. 83-95. 
3. 
Le Strat, Y. and B. Le Foll, Obesity and cannabis use: results from 2 representative national 
surveys. Am J Epidemiol, 2011. 174(8): p. 929-33. 
4. 
Cluny, N.L., et al., Prevention of Diet-Induced Obesity Effects on Body Weight and Gut Microbiota 
in Mice Treated Chronically with Delta9-Tetrahydrocannabinol. PLoS One, 2015. 10(12): p. 
e0144270. 
5. 
Di Marzo, V., A brief history of cannabinoid and endocannabinoid pharmacology as inspired by 
the work of British scientists. Trends Pharmacol Sci, 2006. 27(3): p. 134-40. 
6. 
Di Marzo, V., L. De Petrocellis, and T. Bisogno, Endocannabinoids Part I: molecular basis of 
endocannabinoid formation, action and inactivation and development of selective inhibitors. 
Expert Opin Ther Targets, 2001. 5(2): p. 241-65. 
7. 
Piomelli, D., The molecular logic of endocannabinoid signalling. Nat Rev Neurosci, 2003. 4(11): p. 
873-84. 
8. 
Sugiura, T. and K. Waku, Cannabinoid receptors and their endogenous ligands. J Biochem, 2002. 
132(1): p. 7-12. 
9. 
Gamage, T.F. and A.H. Lichtman, The endocannabinoid system: role in energy regulation. Pediatr 
Blood Cancer, 2012. 58(1): p. 144-8. 
10. 
Matias, I. and V. Di Marzo, Endocannabinoids and the control of energy balance. Trends 
Endocrinol Metab, 2007. 18(1): p. 27-37. 
11. 
Jarbe, T.U. and N.V. DiPatrizio, Delta9-THC induced hyperphagia and tolerance assessment: 
interactions between the CB1 receptor agonist delta9-THC and the CB1 receptor antagonist SR-
141716 (rimonabant) in rats. Behav Pharmacol, 2005. 16(5-6): p. 373-80. 
12. 
Chambers, A.P., et al., A neutral CB1 receptor antagonist reduces weight gain in rat. Am J Physiol 
Regul Integr Comp Physiol, 2007. 293(6): p. R2185-93. 
13. 
Cluny, N.L., et al., A novel peripherally restricted cannabinoid receptor antagonist, AM6545, 
reduces food intake and body weight, but does not cause malaise, in rodents. Br J Pharmacol, 
2010. 161(3): p. 629-42. 
14. 
Colombo, G., et al., Appetite suppression and weight loss after the cannabinoid antagonist SR 
141716. Life Sci, 1998. 63(8): p. PL113-7. 
15. 
McLaughlin, P.J., et al., The cannabinoid CB1 antagonist AM 251 produces food avoidance and 
behaviors associated with nausea but does not impair feeding efficiency in rats. 
Psychopharmacology (Berl), 2005. 180(2): p. 286-93. 
16. 
Sink, K.S., et al., The novel cannabinoid CB1 receptor neutral antagonist AM4113 suppresses 
food intake and food-reinforced behavior but does not induce signs of nausea in rats. 
Neuropsychopharmacology, 2008. 33(4): p. 946-55. 
17. 
Foltin, R.W., J.V. Brady, and M.W. Fischman, Behavioral analysis of marijuana effects on food 
intake in humans. Pharmacol Biochem Behav, 1986. 25(3): p. 577-82. 
18. 
Bedi, G., et al., Efficacy and tolerability of high-dose dronabinol maintenance in HIV-positive 
marijuana smokers: a controlled laboratory study. Psychopharmacology (Berl), 2010. 212(4): p. 
675-86. 
19. 
Haney, M., et al., Dronabinol and marijuana in HIV(+) marijuana smokers: acute effects on 
caloric intake and mood. Psychopharmacology (Berl), 2005. 181(1): p. 170-8. 
20. 
James, J.S., Marijuana safety study completed: weight gain, no safety problems. AIDS Treat 
News, 2000(348): p. 3-4. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
21 
 
21. 
Hayatbakhsh, M.R., et al., Cannabis use and obesity and young adults. Am J Drug Alcohol Abuse, 
2010. 36(6): p. 350-6. 
22. 
Smit, E. and C.J. Crespo, Dietary intake and nutritional status of US adult marijuana users: results 
from the Third National Health and Nutrition Examination Survey. Public Health Nutr, 2001. 4(3): 
p. 781-6. 
23. 
Warren, M., K. Frost-Pineda, and M. Gold, Body mass index and marijuana use. J Addict Dis, 
2005. 24(3): p. 95-100. 
24. 
Racine, C., et al., Metabolic Effects of Marijuana Use among Blacks. J Dis Glob Health, 2015. 4(1): 
p. 9-16. 
25. 
Alshaarawy, O. and J.C. Anthony, Cannabis Smoking and Diabetes Mellitus: Results from Meta-
analysis with Eight Independent Replication Samples. Epidemiology, 2015. 26(4): p. 597-600. 
26. 
Bello, N.T., et al., Dietary conditions and highly palatable food access alter rat cannabinoid 
receptor expression and binding density. Physiol Behav, 2012. 105(3): p. 720-6. 
27. 
Di Marzo, V. and I. Matias, Endocannabinoid control of food intake and energy balance. Nat 
Neurosci, 2005. 8(5): p. 585-9. 
28. 
Monteleone, P., et al., Blood levels of the endocannabinoid anandamide are increased in 
anorexia nervosa and in binge-eating disorder, but not in bulimia nervosa. 
Neuropsychopharmacology, 2005. 30(6): p. 1216-21. 
29. 
Schlogl, H., et al., Functional neuroimaging in obesity and the potential for development of novel 
treatments. Lancet Diabetes Endocrinol, 2016. 4(8): p. 695-705. 
30. 
Val-Laillet, D., et al., Neuroimaging and neuromodulation approaches to study eating behavior 
and prevent and treat eating disorders and obesity. Neuroimage Clin, 2015. 8: p. 1-31. 
31. 
Malik, S., et al., Ghrelin modulates brain activity in areas that control appetitive behavior. Cell 
Metab, 2008. 7(5): p. 400-9. 
32. 
Malik, S., F. McGlone, and A. Dagher, State of expectancy modulates the neural response to 
visual food stimuli in humans. Appetite, 2011. 56(2): p. 302-9. 
33. 
Neseliler, S., J.E. Han, and A. Dagher, The Use of Functional Magnetic Resonance Imaging in the 
Study of Appetite and Obesity, in Appetite and Food Intake: Central Control, nd and R.B.S. Harris, 
Editors. 2017: Boca Raton (FL). p. 117-134. 
34. 
Pursey, K.M., et al., Neural responses to visual food cues according to weight status: a 
systematic review of functional magnetic resonance imaging studies. Front Nutr, 2014. 1: p. 7. 
35. 
Dagher, A., Functional brain imaging of appetite. Trends Endocrinol Metab, 2012. 23(5): p. 250-
60. 
36. 
Burger, K.S. and L.A. Berner, A functional neuroimaging review of obesity, appetitive hormones 
and ingestive behavior. Physiol Behav, 2014. 136: p. 121-7. 
37. 
Makaronidis, J.M. and R.L. Batterham, Obesity, body weight regulation and the brain: insights 
from fMRI. Br J Radiol, 2018. 91(1089): p. 20170910. 
38. 
Carnell, S., et al., Neuroimaging and obesity: current knowledge and future directions. Obes Rev, 
2012. 13(1): p. 43-56. 
39. 
Rangel, A., Regulation of dietary choice by the decision-making circuitry. Nat Neurosci, 2013. 
16(12): p. 1717-24. 
40. 
Filbey, F.M., U.S. Myers, and S. Dewitt, Reward circuit function in high BMI individuals with 
compulsive overeating: similarities with addiction. Neuroimage, 2012. 63(4): p. 1800-6. 
41. 
Rothemund, Y., et al., Differential activation of the dorsal striatum by high-calorie visual food 
stimuli in obese individuals. Neuroimage, 2007. 37(2): p. 410-21. 
42. 
Horder, J., et al., Reduced neural response to reward following 7 days treatment with the 
cannabinoid CB1 antagonist rimonabant in healthy volunteers. Int J Neuropsychopharmacol, 
2010. 13(8): p. 1103-13. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
22 
 
43. 
Backhed, F., et al., The gut microbiota as an environmental factor that regulates fat storage. 
Proc Natl Acad Sci U S A, 2004. 101(44): p. 15718-23. 
44. 
Backhed, F., et al., Mechanisms underlying the resistance to diet-induced obesity in germ-free 
mice. Proc Natl Acad Sci U S A, 2007. 104(3): p. 979-84. 
45. 
Duca, F.A. and T.K. Lam, Gut microbiota, nutrient sensing and energy balance. Diabetes Obes 
Metab, 2014. 16 Suppl 1: p. 68-76. 
46. 
Everard, A. and P.D. Cani, Diabetes, obesity and gut microbiota. Best Pract Res Clin 
Gastroenterol, 2013. 27(1): p. 73-83. 
47. 
Gill, S.R., et al., Metagenomic analysis of the human distal gut microbiome. Science, 2006. 
312(5778): p. 1355-9. 
48. 
Ley, R.E., et al., Microbial ecology: human gut microbes associated with obesity. Nature, 2006. 
444(7122): p. 1022-3. 
49. 
Qin, J., et al., A human gut microbial gene catalogue established by metagenomic sequencing. 
Nature, 2010. 464(7285): p. 59-65. 
50. 
Turnbaugh, P.J., et al., The human microbiome project. Nature, 2007. 449(7164): p. 804-10. 
51. 
Zhernakova, A., et al., Population-based metagenomics analysis reveals markers for gut 
microbiome composition and diversity. Science, 2016. 352(6285): p. 565-9. 
52. 
Rosenbaum, M., R. Knight, and R.L. Leibel, The gut microbiota in human energy homeostasis and 
obesity. Trends Endocrinol Metab, 2015. 26(9): p. 493-501. 
53. 
Saad, M.J., A. Santos, and P.O. Prada, Linking Gut Microbiota and Inflammation to Obesity and 
Insulin Resistance. Physiology (Bethesda), 2016. 31(4): p. 283-93. 
54. 
Tremaroli, V. and F. Backhed, Functional interactions between the gut microbiota and host 
metabolism. Nature, 2012. 489(7415): p. 242-9. 
55. 
Membrez, M., et al., Gut microbiota modulation with norfloxacin and ampicillin enhances 
glucose tolerance in mice. FASEB J, 2008. 22(7): p. 2416-26. 
56. 
Parnell, J.A. and R.A. Reimer, Prebiotic fibres dose-dependently increase satiety hormones and 
alter Bacteroidetes and Firmicutes in lean and obese JCR:LA-cp rats. Br J Nutr, 2012. 107(4): p. 
601-13. 
57. 
Kwan, M.L., et al., A practical method for collecting food record data in a prospective cohort 
study of breast cancer survivors. Am J Epidemiol, 2010. 172(11): p. 1315-23. 
58. 
Jiandani, D., et al., Predictors of early attrition and successful weight loss in patients attending 
an obesity management program. BMC Obes, 2016. 3: p. 14. 
59. 
Christensen, R.A., et al., The associations of resting metabolic rate with chronic conditions and 
weight loss. Clin Obes, 2017. 7(2): p. 70-76. 
60. 
Sobell, L.C., et al., Reliability of a timeline method: assessing normal drinkers' reports of recent 
drinking and a comparative evaluation across several populations. Br J Addict, 1988. 83(4): p. 
393-402. 
61. 
Beck, A.T. and R.A. Steer, Beck depression Inventory. 1987, Philadelphia, PA: Center for Cognitive 
Therapy,. 
62. 
Hamilton, M., A rating scale for depression. J Neurol Neurosurg Psychiatry, 1960. 23: p. 56-62. 
63. 
Buysse, D.J., et al., The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice 
and research. Psychiatry Res, 1989. 28(2): p. 193-213. 
64. 
Chung, F., et al., Validation of the Berlin questionnaire and American Society of Anesthesiologists 
checklist as screening tools for obstructive sleep apnea in surgical patients. Anesthesiology, 
2008. 108(5): p. 822-30. 
65. 
Levine, J. and N.R. Schooler, SAFTEE: a technique for the systematic assessment of side effects in 
clinical trials. Psychopharmacol Bull, 1986. 22(2): p. 343-81. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
23 
 
66. 
Seidell, J.C., C.J. Bakker, and K. van der Kooy, Imaging techniques for measuring adipose-tissue 
distribution--a comparison between computed tomography and 1.5-T magnetic resonance. Am J 
Clin Nutr, 1990. 51(6): p. 953-7. 
67. 
Shuster, A., et al., The clinical importance of visceral adiposity: a critical review of methods for 
visceral adipose tissue analysis. Br J Radiol, 2012. 85(1009): p. 1-10. 
68. 
Yu, H., et al., Combination of complex-based and magnitude-based multiecho water-fat 
separation for accurate quantification of fat-fraction. Magn Reson Med, 2011. 66(1): p. 199-206. 
69. 
Yu, H., et al., Multiecho water-fat separation and simultaneous R2* estimation with 
multifrequency fat spectrum modeling. Magn Reson Med, 2008. 60(5): p. 1122-34. 
70. 
Hu, H.H., J. Chen, and W. Shen, Segmentation and quantification of adipose tissue by magnetic 
resonance imaging. Magma, 2016. 29(2): p. 259-76. 
71. 
Garnov, N., et al., Comparison of T1 relaxation times in adipose tissue of severely obese patients 
and healthy lean subjects measured by 1.5 T MRI. NMR Biomed, 2014. 27(9): p. 1123-8. 
72. 
Ravinet Trillou, C., et al., Anti-obesity effect of SR141716, a CB1 receptor antagonist, in diet-
induced obese mice. Am J Physiol Regul Integr Comp Physiol, 2003. 284(2): p. R345-53. 
73. 
Van Gaal, L.F., et al., Effects of the cannabinoid-1 receptor blocker rimonabant on weight 
reduction and cardiovascular risk factors in overweight patients: 1-year experience from the RIO-
Europe study. Lancet, 2005. 365(9468): p. 1389-97. 
74. 
Trigo, J.M., et al., Effects of fixed or self-titrated dosages of Sativex on cannabis withdrawal and 
cravings. Drug Alcohol Depend, 2016. 161: p. 298-306. 
75. 
Collins, D.L., et al., Automatic 3D intersubject registration of MR volumetric data in standardized 
Talairach space. J Comput Assist Tomogr, 1994. 18(2): p. 192-205. 
76. 
Dai, W., et al., Continuous flow-driven inversion for arterial spin labeling using pulsed radio 
frequency and gradient fields. Magn Reson Med, 2008. 60(6): p. 1488-97. 
77. 
Jarnum, H., et al., Perfusion MRI of brain tumours: a comparative study of pseudo-continuous 
arterial spin labelling and dynamic susceptibility contrast imaging. Neuroradiology, 2010. 52(4): 
p. 307-17. 
78. 
Lu, H., et al., Determining the longitudinal relaxation time (T1) of blood at 3.0 Tesla. Magn Reson 
Med, 2004. 52(3): p. 679-82. 
79. 
Strang, N.M., et al., Dose-dependent effects of intravenous alcohol administration on cerebral 
blood flow in young adults. Psychopharmacology (Berl), 2015. 232(4): p. 733-44. 
80. 
Wu, W.C., et al., In vivo venous blood T1 measurement using inversion recovery true-FISP in 
children and adults. Magn Reson Med, 2010. 64(4): p. 1140-7. 
81. 
Ye, F.Q., et al., Noise reduction in 3D perfusion imaging by attenuating the static signal in 
arterial spin tagging (ASSIST). Magn Reson Med, 2000. 44(1): p. 92-100. 
82. 
Stearns, J.C., et al., Culture and molecular-based profiles show shifts in bacterial communities of 
the upper respiratory tract that occur with age. ISME J, 2015. 9(5): p. 1268. 
83. 
Whelan, F.J. and M.G. Surette, A comprehensive evaluation of the sl1p pipeline for 16S rRNA 
gene sequencing analysis. Microbiome, 2017. 5(1): p. 100. 
84. 
Bokulich, N.A. and D.A. Mills, Improved selection of internal transcribed spacer-specific primers 
enables quantitative, ultra-high-throughput profiling of fungal communities. Appl Environ 
Microbiol, 2013. 79(8): p. 2519-26. 
85. 
Caporaso, J.G., et al., QIIME allows analysis of high-throughput community sequencing data. Nat 
Methods, 2010. 7(5): p. 335-6. 
86. 
Schloss, P.D., et al., Introducing mothur: open-source, platform-independent, community-
supported software for describing and comparing microbial communities. Appl Environ 
Microbiol, 2009. 75(23): p. 7537-41. 

QI: Bernard Le Foll, MD PhD 
Nabilone Obesity Study 
Version 6.0 October 18, 2022 
24 
 
87. 
McMurdie, P.J. and S. Holmes, phyloseq: an R package for reproducible interactive analysis and 
graphics of microbiome census data. PLoS One, 2013. 8(4): p. e61217. 
88. 
Li, D., et al., MEGAHIT v1.0: A fast and scalable metagenome assembler driven by advanced 
methodologies and community practices. Methods, 2016. 102: p. 3-11. 
89. 
Nurk, S., et al., metaSPAdes: a new versatile metagenomic assembler. Genome Res, 2017. 27(5): 
p. 824-834. 
90. 
Kang, D.D., et al., MetaBAT, an efficient tool for accurately reconstructing single genomes from 
complex microbial communities. PeerJ, 2015. 3: p. e1165. 
91. 
Parks, D.H., et al., CheckM: assessing the quality of microbial genomes recovered from isolates, 
single cells, and metagenomes. Genome Res, 2015. 25(7): p. 1043-55. 
92. 
Wood, D.E. and S.L. Salzberg, Kraken: ultrafast metagenomic sequence classification using exact 
alignments. Genome Biol, 2014. 15(3): p. R46. 
93. 
Seemann, T., Prokka: rapid prokaryotic genome annotation. Bioinformatics, 2014. 30(14): p. 
2068-9. 
94. 
Abubucker, S., et al., Metabolic reconstruction for metagenomic data and its application to the 
human microbiome. PLoS Comput Biol, 2012. 8(6): p. e1002358. 
95. 
FDA, Marinol: Product Monograph. 
https://www.accessdata.fda.gov/drugsatfda_docs/label/2006/018651s025s026lbl.pdf, 2006. 
USA. 
96. 
Ford, T.C., et al., Cannabis: an overview of its adverse acute and chronic effects and their 
implications. Curr Drug Abuse Rev, 2017. 
97. 
Volkow, N.D., et al., Effects of Cannabis Use on Human Behavior, Including Cognition, 
Motivation, and Psychosis: A Review. JAMA Psychiatry, 2016. 73(3): p. 292-7. 
98. 
Wang, T., et al., Adverse effects of medical cannabinoids: a systematic review. CMAJ, 2008. 
178(13): p. 1669-78. 
99. 
Fabbrini, E., Sullivan, S., & Klein, S. (2010). Obesity and nonalcoholic fatty liver disease: 
biochemical, metabolic, and clinical implications. Hepatology (Baltimore, Md.), 51(2), 679–689. 
https://doi.org/10.1002/hep.23280 
100. 
Neuman, M. G., Voiculescu, M., Nanau, R. M., Maor, Y., Melzer, E., Cohen, L. B., Opris, M., & 
Malnick, S. (2016). Non-Alcoholic Steatohepatitis: Clinical and Translational Research. Journal of 
Pharmacy & Pharmaceutical Sciences, 19(1), 8–24. https://doi.org/10.18433/J3F61F 
101. 
Tam, J., Liu, J., Mukhopadhyay, B., Cinar, R., Godlewski, G. and Kunos, G. (2011), 
Endocannabinoids in liver disease. Hepatology, 53: 346-355. https://doi.org/10.1002/hep.24077 
102. 
Kim D, Kim W, Kwak MS, Chung GE, Yim JY, et al. (2017) Inverse association of marijuana use 
with nonalcoholic fatty liver disease among adults in the United States. PLOS ONE 12(10): 
e0186702. https://doi.org/10.1371/journal.pone.0186702