The acute and chronic pharmacokinetics and pharmacodynamics of oral cannabidiol with and without low doses of delta-9-tetrahydrocannabinol
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
RTI International, Research Triangle Park, NC 27709, United States
RTI International, Research Triangle Park, NC 27709, United States
Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States
Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States
Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States
Clinical Reference Laboratory, Lenexa, KS 66214, United States
Charlotte’s Web, Louisville, CO 80027, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States
Abstract
Hemp products [cannabis with ≤0.3% Δ9-tetrahydrocannabinol (Δ9-THC)] are federally legal, but few controlled experiments have explored drug test results, pharmacokinetics, or pharmacodynamics. Healthy adults (n = 60) self-administered 1.5 mL medium-chain triglyceride (MCT) oil containing 100 mg cannabidiol (CBD) and either 0, 0.5, 1, 2, 2.8, or 3.7 mg Δ9-THC (n = 10 per group). The study included an 8-hour acute dose laboratory session (Phase 1), a 14-day outpatient drug exposure period with twice daily dosing (Phase 2) and a 7-day washout period (Phase 3). Measures including urine, blood, subjective drug effects, and cognitive and psychomotor performance were assessed repeatedly throughout the experiment. At least one participant receiving Δ9-THC doses of 1.0 mg or greater had at least 1 positive urine drug test (Δ9-THC-COOH immunoassay screen ≥50 ng/mL and LC-MS/MS confirmation ≥15 ng/mL) during Phase 1 and the number of positive urine samples increased with Δ9-THC dose. Positive urine drug tests were observed during the Phase 2 outpatient drug exposure period from at least one participant in each dose condition that contained any amount of Δ9-THC. One urine specimen in the CBD only dose condition tested positive during Phase 2. Two positive urine samples were observed after the 1-week washout (Day 21). Blood concentrations of Δ9-THC were very low in all dose conditions, and there were no significant differences between the CBD only dose group and Δ9-THC-containing dose groups on any pharmacodynamic outcome. Individuals subject to drug testing should recognize that hemp products contain detectable amounts of Δ9-THC. Conventional drug testing cannot reliably distinguish between illicit cannabis and legal hemp-derived product use, and a positive urine Δ9-THC test may result from low doses that do not produce intoxication or impairment.
Article notes
Untitled section
Collection date 2026 Jan.
Introduction
The 2018 Agriculture Improvement Act, or “Farm Bill,” legalized the possession, cultivation, and use of hemp in the U.S. and defined it as cannabis containing no more than 0.3% delta-9-tetrahydrocannabinol (Δ9-THC) by dry weight.1 Similar changes in cannabis policy have been enacted in many other countries and collectively has yielded a proliferative hemp industry of which a major sector consists of consumable retail products that contain cannabidiol (CBD) and other cannabinoids, including Δ9-THC. However, drug testing programs for cannabis use remain prevalent in the workplace, military, criminal justice programs and athletics.2
Urine drug testing remains the gold standard to detect the use of cannabis, though other biological matrices (ie, oral fluid or blood) may also be used. Δ9-THC is the phytocannabinoid most associated with impairment and abuse liability of cannabis3–6; thus, Δ9-THC, or metabolites of Δ9-THC such as 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (Δ9-THC-COOH), are often the target analytes of conventional drug tests. Many retail hemp/CBD products contain low concentrations of Δ9-THC, though, and prior studies have indicated that use of these products can cause positive urine drug tests.7–10 Questions remain regarding use of hemp products and testing outcomes, including the identification of the threshold dose of Δ9-THC that reliably produces positive drug tests and an evaluation of the pharmacodynamic effects of these types of products, especially related to abuse liability and impairment.
This study utilized a double-blind, between-subjects outpatient design to examine acute and chronic pharmacokinetics and pharmacodynamics of a medium-chain triglyceride (MCT)-oil-based product containing 100 mg CBD alone or in combination with a low dose of Δ9-THC (0.5–3.7 mg). Results from this study are critical to informing policy decisions about cannabis and hemp products and could directly inform guidelines for drug-testing standards.
Materials and methods
All study procedures were completed at the Cannabis Science Laboratory, a sub-division of the Johns Hopkins Behavioral Pharmacology Research Unit (BPRU), in Baltimore, MD. Experimental procedures were approved by the Institutional Review Board of the Johns Hopkins University School of Medicine and were conducted in accordance with the Declaration of Helsinki. This study was registered on ClinicalTrials.gov (NCT04283019).
Participants
Participants were recruited for the study via media advertising (e.g. flyers and internet) and word-of-mouth communication. Eligibility was determined by short phone or web-based questionnaire followed by a physical examination, assessment of mental health/substance use status, qualitative urine drug testing and determination of concomitant medications. Written informed consent to participate in the study was obtained. Study participants were healthy adults with a history of cannabis use, but no use in the prior 30 days (confirmed by urine drug testing). See Appendix 1 in the Supplementary Data for complete inclusion and exclusion criteria.
Study design and procedures
The study utilized a between-subjects, double-blind design with 6 experimental drug conditions: 100 mg CBD plus one of the following: 0 mg Δ9-THC, 0.5 mg Δ9-THC, 1.0 mg Δ9-THC, 2.0 mg Δ9-THC, 2.8 mg Δ9-THC, or 3.7 mg Δ9-THC (herein after referred to as CBD alone, 0.5, 1.0, 2.0, 2.8, and 3.7 mg Δ9-THC, respectively). 60 participants completed the study, with 10 participants randomly assigned to each dose condition. All participants completed the protocol in three phases, lasting a total of 21 days. In Phase 1 (Day 1), participants completed an acute drug dosing session in the laboratory lasting approximately 8 hours. During this session, participants were given a high-fat breakfast (e.g. sausage, egg and cheese sandwich), had an indwelling intravenous catheter placed for repeat blood draws, completed baseline assessments (described below), orally self-administered their assigned study drug, and then completed repeated assessments for 8 hours. Pre- and post-dose assessments included biospecimen (ie, blood, oral fluid, and urine) collection, subjective drug effect questionnaires, vital signs measurement, and cognitive/psychomotor task performance. Oral fluid results will be reported elsewhere.
Phase 2 (Days 1–14) involved an outpatient dosing period in which participants took the assigned study drug twice daily in their home environment. This period started the evening of Day 1 and participants were instructed to take the study drug with breakfast and dinner each day through breakfast on Day 14. Participants filmed themselves self-administering each dose and uploaded the videos to a secure database (REDCap) to confirm adherence with dosing procedures. There was 97% compliance across all participants for dosing procedure adherence. One individual in the 2.0 mg Δ9-THC condition missed 12 doses due to study drug spillage during Phase 2; this individual was excluded from all Phase 2 analyses. Missed doses were rare for other participants. During Phase 2, participants returned to the laboratory for brief visits on Days 2, 7, and 14 to complete assessments. Participants were instructed not to drive during Phase 2 and to use care in performing daily activities as they would when taking a prescription medication that could impair functioning or cause sedation.
Phase 3 (Days 15–21) consisted of a 1-week washout from study drug use and concluded with a final follow-up visit on Day 21, during which a final round of assessments was completed.
Study drug and materials
The study drug was compounded by the Johns Hopkins BPRU Pharmacy. Hemp-derived CBD (>99% purity purchased from Open Book Extracts) and synthetic Δ9-THC (>99% purity purchased from THC Pharm GmbH) were added separately to commercial MCT oil and sonicated into solution and stored in silanized amber glass jars with Teflon lids. The 100 mg dose of CBD was selected because that is the unit dose of the FDA-approved botanically-derived CBD medication Epidiolex, and to be consistent with a prior laboratory study that involved single acute doses of CBD by our group.7 The 3.7 mg Δ9-THC dose was selected to replicate the dose administered via vaporization in our prior acute dosing study and the lower Δ9-THC doses (0.5, 1.0, 2.0, and 2.8 mg) were selected to represent a range of low THC doses found in retail “full-spectrum” CBD oils.11
Pharmacy staff dispensed a 1-week supply of the study drug for participants on Days 1 and 7. Participants were provided a glass dropper with graduated lines to draw the study drug out of the glass vial. Participants were instructed to keep the jar refrigerated when not in use to minimize degradation of the cannabinoids due to exposure to light or heat. During Phase 1, participants were trained to draw the appropriate dose and self-administered the drug under staff observation. Study staff monitored the volume of liquid drawn for each dose in Phase 2 via the medication adherence videos.
Assessments
During Phase 1, pharmacodynamic assessments [including Drug Effects Questionnaire (DEQ) and SF-36], vitals, cognitive measures [including Divided Attention Task (DAT), Digit Symbol Substitution Task (DSST), Paced Serial Addition Task (PASAT), and Driving Under the Influence of Drugs (DRUID)]12 and blood/oral fluid collection occurred at baseline (prior to product use) and again at 0.5, 1, 1.5, 2, 3, 4, 5, and 6 h after product use. The exception to this is the Short-Form 36 (SF-36), which was only collected at baseline. Spot urine samples were collected at baseline and 1, 2, 3, 4, 5, and 6 h after Phase 1 dosing. Blood and urine samples were analyzed using LC-MS/MS for CBD, Δ9-THC and their primary metabolites. During Phases 2 and 3, assessments were completed at brief laboratory visits on Days 2, 7, 14, and 21. See Appendices 2 and 3 in the Supplementary Data for detailed descriptions of pharmacokinetic and pharmacodynamic assessments and methods, respectively.
Data presentation and analysis
Descriptive statistics were used to summarize participant demographics and LC–MS/MS urine and whole blood results. All pharmacokinetic data are presented as raw values. For urine and whole blood analyses, the six analytes of interest were Δ9-THC, 11-OH-Δ9-THC, Δ9-THC-COOH, CBD, 7-OH-CBD and 7-COOH-CBD. For each participant, maximum concentrations (Cmax) of each analyte were determined by selecting the highest concentration following the acute drug administration (Phase 1), and time to maximum concentrations (Tmax) was determined when Cmax occurred (these individual values were then averaged to produce mean Cmax and Tmax for each condition). Area under the curve (AUC) for each analyte was determined by using the trapezoidal method across the 6-h sampling window.13 Cmax, Tmax, and AUC values were based on measurements taken during the initial acute dosing session only, as follow-up sessions in Phase 2 occurred at variable times relative to outpatient drug dosing. Nonparametric tests were employed for all pharmacokinetic statistical analyses due to non-normal data distributions. Specifically, Cmax, Tmax, and AUC values were compared using the Kruskal–Wallis test, followed by Dunn’s multiple comparison test to compare each drug condition for which analytes were detected. To assess analyte accumulation over time, a ratio-based approach was used. For each analyte and participant, concentrations on Days 2, 7, and 14 were divided by the corresponding Cmax value from Day 1 (Phase 1), producing a Day/Cmax ratio. These ratios were analyzed separately within each drug condition using a repeated-measures one-way ANOVA, with Day (1, 2, 7, and 14) as the within-subject factor. Dunnett’s multiple comparisons were used to compare each follow-up day to Day 1. By definition, Day 1 ratios equal 1; values significantly greater than 1 suggest accumulation of the analyte over time.
Sensitivity, specificity and agreement between IA and LC-MS/MS results were conducted for urinary Δ9-THC-COOH for all conditions. Three IA screening cutoffs were employed for these analyses: 20, 50, and 100 ng/mL. A confirmatory LC–MS/MS cutoff of 15 ng/mL was used for all analyses, which is consistent with the mandatory guidelines for federal workplace drug testing established by the Substance Abuse and Mental Health Services Administration (SAMHSA)14. Urinary Δ9-THC-COOH test results were categorized as either true positive (TP; IA response ≥ cutoff concentration and LC–MS/MS positive), true negative (TN; IA response < cutoff concentration and LC–MS/MS negative), false positive (FP; IA response ≥ cutoff concentration and LC–MS/MS negative) or false negative (FN; IA response < cutoff concentration and LC–MS/MS positive). Sensitivity, specificity and agreement were calculated as follows: sensitivity (100 × [TP/(TP + FN)]), specificity (100 × [TN/(TN + FP)]) and agreement (100 × [(TP + TN)/(TP + TN + FP + FN)]).
For all pharmacodynamic effects, values were converted to change-from-baseline values. All pharmacodynamic outcomes were analyzed using two-way, repeated-measures analysis of variance (ANOVA) with the between-subject factor of Drug Condition and the within-subject factor of Time. To assess the effects of acute drug administration, pharmacodynamic assessments from Day 1 were analyzed using a one-way ANOVA with Drug Condition as the between-subjects factor. When a significant main effect of Drug Condition or a Drug Condition × Time interaction was detected for any ANOVA, Bonferroni’s multiple comparisons test was used to compare Δ9-THC dose conditions with the CBD only condition. Statistical analyses for both pharmacokinetic and pharmacodynamic outcomes were conducted using Prism 10 for macOS (Version 10.3.0, GraphPad Software, LLC); the α level was set at 0.05 for all analyses.
Results
Participants
Participant demographics are shown in Table 1. Participants were predominantly white (N = 38; 63% of total sample) and female (N = 35; 59% of total sample). Participants did not differ on their mean age, BMI, alcohol consumption, tobacco use, or time since last use of a cannabis product (all p’s > 0.05).
| 100 mg CBD + | |||||||
|---|---|---|---|---|---|---|---|
| Characteristics | 0 mg Δ9-THC (N = 10) | 0.5 mg Δ9-THC (N = 10) | 1.0 mg Δ9-THC (N = 10) | 2.0 mg Δ9-THC (N = 10) | 2.8 mg Δ9-THC (N = 10) | 3.7 mg Δ9-THC (N = 10) | |
| Age (in years) | Mean (SD) | 29.2 (7.7) | 24.0 (3.4) | 28.0 (7.1) | 28.8 (9.4) | 32.6 (9.3) | 28.6 (9.0) |
| Gender | n (% Male) | 3 (30%) | 3 (30%) | 4 (40.0%) | 4 (40%) | 3 (30%) | 8 (80%) |
| Race n (%) | Caucasian | 6 (60%) | 8 (80%) | 5 (50%) | 8 (80%) | 7 (70%) | 4 (40%) |
| African American | 4 (40%) | 0 (0%) | 2 (20%) | 2 (20%) | 2 (20%) | 2 (20%) | |
| Asian | 0 (0%) | 2 (20%) | 3 (30%) | 0 (0%) | 1 (10%) | 4 (40%) | |
| Hispanic | n % | 0 (0%) | 1 (10%) | 0 (0%) | 1 (10%) | 0(0%) | 0 (0%) |
| BMI | Mean (SD) | 25.4 (4.5) | 25.2 (3.3) | 24.6 (3.8) | 26.6 (3.6) | 25.7 (2.8) | 27.1 (4.1) |
| Average number alcoholic drinks per week | Mean (SD) | 1.5 (1.6) | 1.1 (1.1) | 1.6 (2.3) | 0.9 (1.5) | 2.1 (4.0) | 2.0 (1.5) |
| Average number of cigarettes per day | Mean (SD) | 0.1 (0.3) | 0.2 (0.3) | 0.0 (0.0) | 0.1 (0.3) | 0.0 (0.0) | 0.0 (0.0) |
| Time in days since last cannabis product use | Mean (SD) | 158.9 (144.5) | 115.1 (127.5) | 70.6 (61.9) | 100.2 (102.4) | 110.6 (128.40) | 149.5 (145.0) |
Urine pharmacokinetics
Figure 1 illustrates the mean urinary concentrations of CBD, its metabolites, and Δ9-THC-COOH (the primary target of urine drug tests for cannabis use). CBD (Figure 1A), 7-OH-CBD (Figure 1B), and 7-COOH-CBD (Figure 1C) were detected in all study conditions following drug administration. All conditions containing Δ9-THC produced measurable levels of Δ9-THC, 11-OH-Δ9-THC, and Δ9-THC-COOH (Figure 1D). IA and LC-MS/MS results for all analytes are provided in Supplementary Table 1.
Five participants (one from the 100 mg CBD alone group, one from the 2.0 mg Δ9-THC group, two from the 2.8 mg Δ9-THC group, and one from the 3.7 mg Δ9-THC group) screened negative but had low levels of cannabinoids (0.5–18.4 ng/mL) detected in urine at baseline. Their last self-reported cannabis use ranged from 33 to 112 days before the Day 1 session. None exceeded federal workplace drug test thresholds (≥50 ng/mL for IA screening and ≥15 ng/mL for LC-MS/MS confirmatory testing)14 and likely reflect low-level excretion of residual cannabinoids from pre-study exposure.
Phase 1
CBD and 7-OH-CBD were detected within 1 hour of drug administration, peaking at 4–5 hours, with concentrations ranging from 20.1–11,432.5 ng/mL and 71.9–13,867.7 ng/mL, respectively (Table S2). 7-COOH-CBD was generally detected by Hour 2 and continued to rise throughout the session, peaking at 5–6 hours (1.8–983.2 ng/mL). No significant differences were observed in Cmax, Tmax, or AUC values between conditions for CBD, 7-OH-CBD, or 7-COOH-CBD during Phase 1 (all p’s > 0.05; Table S2). No effects of Δ9-THC on the pharmacokinetics of CBD or its metabolites were observed at any dose of Δ9-THC.
Formulations containing Δ9-THC produced dose-dependent increases in Δ9-THC, 11-OH-Δ9-THC, and Δ9-THC-COOH concentrations (Table S2). 11-OH-Δ9-THC and Δ9-THC-COOH showed dose-dependent increases in Cmax and AUC as indicated by a main effect of Drug Condition. 2.0, 2.8, and 3.7 mg Δ9-THC dose conditions had significantly higher Cmax and AUC values of 11-OH-Δ9-THC than CBD alone. 2.8 and 3.7 mg Δ9-THC also exceeded the 0.5 mg Δ9-THC condition. 2.8 and 3.7 mg Δ9-THC produced greater Δ9-THC-COOH Cmax values than CBD alone and the 0.5 mg Δ9-THC condition.
Generally, Δ9-THC and 11-OH-Δ9-THC were detected between 1 and 2 hours post-administration and peaked at 3–5 hours while Δ9-THC-COOH first appeared at 2–3 hours and peaked at 5–6 hours after dosing. Based on the SAMHSA mandatory guidelines, positive urine tests for Δ9-THC-COOH were observed in one, four, six, and seven participants after single acute doses of 1.0, 2.0, 2.8, and 3.7 mg Δ9-THC, respectively; no positive tests occurred during Phase 1 in the CBD alone or 0.5 mg Δ9-THC conditions.
Phase 2
CBD and its primary metabolites showed increased concentrations over the 14-day administration period (Table S3). Observed Phase 2 peak values ranged from 79.8–11,432.5 ng/mL for CBD, 307.7–14,923.5 ng/mL for 7-OH-CBD, and 51.8–3420.8 ng/mL for 7-COOH-CBD. The highest concentrations of CBD and 7-OH-CBD occurred earlier in Phase 2, on average, compared with 7-COOH-CBD, suggestive of accumulation of 7-COOH-CBD with repeated dosing. An analysis of Day/Cmax accumulation ratio values revealed a significant increase in 7-COOH-CBD concentrations by Day 14 in the CBD-alone condition, with trends toward significance observed across all Drug Conditions for this metabolite.
Δ9-THC and its primary metabolites increased in concentration during Phase 2 (Table S3; Figure 1). Day/Cmax accumulation ratio values revealed a significant increase in Δ9-THC-COOH concentrations by Day 14 in the 1.0 mg Δ9-THC condition, with trends toward significance observed across all Drug Conditions containing Δ9-THC for this metabolite. Based on SAMHSA criteria, positive urine tests for Δ9-THC-COOH were observed in one, one, four, six, nine, and ten participants during the chronic dose phase of the study for the CBD alone, 0.5, 1.0, 2.0, 2.8, and 3.7 mg Δ9-THC dose conditions, respectively.
Phase 3
Following the 7-day washout period, CBD and its metabolites remained detectable in most participants (>95%), with concentrations ranging from 0.7–246.7 ng/mL (CBD), 0.0–511.7 ng/mL (7-OH-CBD), and 1.3–196.0 ng/mL (7-COOH-CBD). Only one positive urine test for Δ9-THC-COOH was observed after the 7-day washout (a participant in the 2.0 mg Δ9-THC dose condition).
Sensitivity, specificity and agreement
Results from sensitivity, specificity, and agreement analyses comparing IA and LC-MS/MS for urinary Δ9-THC-COOH are summarized in Table S4. IA screening cutoffs (20, 50, and 100 ng/mL) were evaluated against LC-MS/MS confirmatory results (≥15 ng/mL). Sensitivity was highest at the 20 ng/mL cutoff and declined at 50 and 100 ng/mL, while specificity and agreement peaked at the 100 ng/mL cutoff.
Whole blood pharmacokinetics
Figure 2 shows mean whole blood concentrations of CBD, Δ9-THC, and metabolites over time. LC-MS/MS results for all analytes are provided in Table S5.
Phase 1
CBD and its metabolites were detected in all participants post-administration. CBD, 7-OH-CBD, and 7-COOH-CBD appeared within 0.5–3 hours, peaked at 3–6 hours, and Cmax concentrations ranged from 0–138.7 ng/mL, 0–28.8 ng/mL, and 1.5–217.4 ng/mL, respectively (Table S2). There were no significant effects of Drug Condition on Cmax, Tmax, or AUC values for CBD or its metabolites, indicating Δ9-THC did not alter CBD metabolism in this experiment.
The number of participants below the LOQ for Δ9-THC was ten, nine, eight, seven, three, and two for CBD alone, 0.5, 1.0, 2.0, 2.8, and 3.7 mg Δ9-THC, respectively. When detected, Δ9-THC, 11-OH-Δ9-THC, and Δ9-THC-COOH peaked at 3–6 hours and Cmax concentrations, on average, were dose-dependent (Table S3). Given the limited number of participants with detectable concentrations of Δ9-THC in the CBD alone, 0.5, and 1.0 mg Δ9-THC conditions, comparisons between Cmax, Tmax, and AUC values could not be conducted. For 11-OH-Δ9-THC, ANOVAs showed a main effect of Drug Condition for Cmax and AUC, with 3.7 mg producing higher values than 1.0 mg Δ9-THC condition; CBD alone and 0.5 mg Δ9-THC were detected in zero and one participant, respectively, and could not be compared. For Δ9-THC-COOH, an ANOVA revealed a main effect of Drug Condition for Cmax and AUC, with 3.7 mg Δ9-THC being significantly greater than the 0.5 mg Δ9-THC condition.
Phase 2
CBD and 7-OH-CBD concentrations were similar to Phase 1. Comparisons of the Day/Cmax accumulation ratio values revealed a significant increase in 7-COOH-CBD concentrations on Days 2, 7, and 14 for CBD alone and 3.7 mg Δ9-THC, with trends toward significance observed across all Drug Conditions for this metabolite, suggesting accumulation compared to Phase 1 (Table S3).
Δ9-THC and its metabolites varied by dose. The number of participants with detectable Δ9-THC concentrations was zero for CBD alone, 0.5 mg, and 1.0 mg Δ9-THC; one for 2.0 mg Δ9-THC; four for 2.8 mg Δ9-THC; and two for 3.7 mg Δ9-THC. Similarly, 11-OH-Δ9-THC was not detected in the 0 or 0.5 mg Δ9-THC dose conditions but was detected in one participant at 1.0 mg Δ9-THC, four participants at 2.0 mg Δ9-THC, six participants at 2.8 mg Δ9-THC, and nine participants at 3.7 mg Δ9-THC. Δ9-THC-COOH was detected in six participants at 0.5 mg Δ9-THC, ten at 1.0 mg and 2.0 mg Δ9-THC, seven at 2.8 mg Δ9-THC, and nine at 3.7 mg Δ9-THC. Neither Δ9-THC or either metabolite was detected in blood during Phase 2 for the CBD only dose condition. Comparisons of the Day/Cmax accumulation ratio values revealed a significant increase in Δ9-THC-COOH concentrations on Day 14 for 1.0 mg Δ9-THC, with trends toward significance observed across all Drug Conditions containing Δ9-THC for this metabolite, suggesting accumulation compared to Phase 1 (Table S3).
Phase 3
After a 7-day washout, CBD and 7-COOH-CBD remained detectable in most participants (>95%), ranging from 2.4–37.1 ng/mL (CBD) and 1.43–90.5 ng/mL (7-COOH-CBD). No Δ9-THC or 11-OH-Δ9-THC was detected in any blood samples on Day 21. Δ9-THC-COOH was detected post-washout in one, two, three, and five participants from the 1.0, 2.0, 2.8, and 3.7 mg Δ9-THC conditions, respectively, but all concentrations were <1.0 ng/mL.
Subjective drug effects
There was no significant main effect of Drug Condition across any DEQ item, while there was a significant main effect of Time observed for the following ten items: “Feel Drug Effect,” “Pleasant Drug Effect,” “Drug Liking,” “Anxious/Nervous,” “Relaxed,” “Sleepy/Tired,” “Alert,” “Restless,” “Hungry/Have Munchies,” and “Dry Mouth” (see Figure S1, Table 2, and Table S6). Significant Drug Condition × Time interactions were observed for “Feel Drug Effect,” “Dry Mouth,” and “Trouble with Memory.” Following acute drug administration, there were no significant differences in subjective drug effect ratings across any of the 21 DEQ items based on the one-way ANOVAs, except for overall drug effect ratings during the acute dosing session. Specifically, a main effect of Drug Condition was observed for drug effect (F[5, 54]=2.771; p < 0.05). However, planned comparisons revealed there were no differences between any of the five Δ9-THC dose conditions and the CBD alone condition.
| 100 mg CBD + | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 mg Δ9-THC (N = 10) | 0.5 mg Δ9-THC (N = 10) | 1.0 mg Δ9-THC (N = 10) | 2.0 mg Δ9-THC (N = 10) | 2.8 mg Δ9-THC (N = 10) | 3.7mg Δ9-THC (N = 10) | |||||||
| Cmax | T peak (hour) | C max | T max (hour) | C max | T max (hour) | C max | T max (hour) | C max | T max (hour) | C max | T max (hour) | |
| Subjective measures | ||||||||||||
| DEQ | ||||||||||||
| Drug effect | 17.6 (20.5) | 0.9 (0.4) | 11.3 (21.3) | 1.8 (1.6) | 15.5 (24.8) | 1.5 (1.3) | 12.8 (11.3) | 1.9 (2.0) | 3.5 (6.7) | 2.4 (1.9) | 35.2 (27.6) | 2.5 (1.6) |
| Unpleasant | 5.6 (15.7) | 0.5 (0.0) | 1.5 (2.5) | 1.8 (1.9) | 11.3 (22.0) | 2.8 (2.1) | 1.6 (2.4) | 0.9 (0.2) | −0.1 (0.6) | 1.0 (0.0) | 14.8 (25.8) | 2.4 (1.8) |
| Pleasant | 22.3 (28.5) | 1.9 (2.0) | 23.4 (30.2) | 2.2 (1.8) | 12.4 (21.6) | 1.4 (1.5) | 12.4 (15.8) | 2.8 (1.6) | 5.3 (15.7) | 1.7 (2.0) | 32.5 (26.6) | 1.6 (1.4) |
| Drug liking | 28.6 (30.7) | 1.2 (1.1) | 12.9 (30.8) | 1.4 (1.3) | 16.9 (21.6) | 1.3 (1.4) | 21.9 (25.0) | 2.2 (2.0) | 20.9 (26.4) | 1.0 (1.1) | 45.6 (21.9) | 1.8 (1.5) |
| Sick | 0.0 (0.0) | NR | 0.7 (4.1) | 2.1 (2.2) | 3.3 (6.0) | 3.4 (2.5) | 1.3 (3.8) | 1.7 (1.3) | 0.4 (1.3) | 0.5 (0.0) | 9.2 (16.3) | 2.9 (1.0) |
| Heart racing | −0.4 (2.5) | 0.5 (0.0) | −1.3 (4.5) | 1.2 (0.4) | 0.8 (2.2) | 0.9 (0.5) | 3.2 (6.0) | 1.5 (0.0) | −0.7 (3) | 2.5 (2.1) | 7.4 (13.5) | 2.8 (1.7) |
| Anxious/nervous | −0.3 (5.4) | 1.2 (1.1) | −7.2 (12.8) | 1.8 (2.1) | 4.3 (8.3) | 2.6 (1.8) | −0.4 (13.5) | 1.5 (1.3) | −1.1 (7.8) | 3.5 (2.1) | 9.1 (17.3) | 2.8 (1.2) |
| Relaxed | −11.7 (40.1) | 3.1 (2.1) | 4.0 (32.4) | 2.8 (2.4) | 13.4 (48.9) | 2.9 (2.0) | −23.2 (36.5) | 2.5 (2.2) | 5.5 (44.3) | 2.8 (2.2) | −18 (40.8) | 2.6 (1.9) |
| Paranoid | 1.0 (1.7) | 2.0 (2.7) | −0.6 (1.9) | 0.8 (0.3) | 0.6 (1.3) | 1.8 (1.8) | 0.1 (0.3) | 3.0 (0.0) | 2.5 (5.4) | 0.5 (0.0) | 1.1 (7.1) | 3.1 (1.6) |
| Sleepy/Tired | 26.5 (41.3) | 3.1 (1.9) | 24.3 (31) | 2.6 (1.6) | 38.6 (33.0) | 3.1 (1.8) | 30.2 (28.8) | 1.6 (1.4) | 26.7 (17.5) | 4.3 (1.7) | 34.6 (41.4) | 3.6 (2.1) |
| Alert | −20.7 (37.7) | 3.7 (1.9) | −26 (32.8) | 3.0 (1.7) | −24.9 (31.4) | 2.7 (1.9) | −18 (37.8) | 3.1 (2.3) | −18.8 (32.8) | 2.8 (2.0) | −29.9 (26.5) | 4.2 (1.7) |
| Irritable | −1.5 (3.6) | 2.5 (3.0) | 1.5 (3.6) | 1.0 (0.0) | 1.0 (2.0) | 2.2 (2.5) | 2.2 (4.7) | 5.5 (0.7) | −0.4 (2.9) | 1.1 (1.2) | 1.8 (23.8) | 2.8 (2.5) |
| Vigorous/Motivated | −8.6 (23.4) | 2.4 (1.4) | −6.5 (35.9) | 3.6 (1.9) | 6.2 (39.3) | 3.6 (2.4) | −4.5 (23.3) | 2.6 (1.9) | −13.9 (20.8) | 2.1 (1.9) | −16.3 (21.9) | 2.7 (1.6) |
| Restless | 0.8 (4.5) | 2.5 (3.0) | 2.2 (15.3) | 2.1 (1.3) | 1.5 (12.4) | 1.6 (1.7) | 0.2 (25.4) | 2.8 (2.5) | −3.7 (23.1) | 2.8 (2.1) | −10.2 (33.5) | 1.9 (2.0) |
| Hungry/Had Munchies | 11.9 (27.6) | 1.9 (1.3) | 25.6 (28.8) | 2.6 (1.5) | 10.9 (18.2) | 2.0 (1.4) | 21.0 (26.3) | 3.0 (1.4) | 6.4 (10.3) | 3.2 (2.2) | 35.1 (37.6) | 3.1 (1.8) |
| Cannabis Craving | −0.5 (2.0) | 2.5 (2.1) | −0.1 (0.6) | 0.7 (0.3) | 5.0 (13.2) | 4.0 (2.6) | 0.0 (0.0) | NR | 0.1 (0.3) | 0.5 (0.0) | 0.4 (1.2) | 3.8 (2.9) |
| Dry Mouth | 17.6 (26.7) | 1.9 (2.1) | 18.1 (31.4) | 1.0 (0.3) | 20.3 (31.5) | 3.4 (2.0) | 20.6 (26.5) | 2.2 (2.2) | −3.9 (20.6) | 2.9 (2.0) | 39.0 (37.0) | 3.4 (1.5) |
| Dry/Red Eyes | 3.4 (10.4) | 1.2 (0.4) | −0.3 (1.3) | 2.8 (3.2) | 10.1 (23.7) | 2.4 (1.9) | 1.5 (4.7) | 1.0 (0.0) | −1.6 (4.7) | 2.8 (3.2) | 12.2 (18.6) | 3.2 (1.8) |
| Memory Impairment | 2.1 (4.2) | 0.8 (0.6) | 0.7 (3.1) | 0.8 (0.3) | 5.3 (6.2) | 1.6 (1.9) | 3.5 (7.6) | 2.5 (2.2) | 0.4 (1.0) | 3.8 (3.2) | 11.5 (21.3) | 2.4 (1.4) |
| Throat Irritation/Coughing | 2.2 (6.6) | 3.8 (3.2) | −0.3 (1.3) | 2.8 (3.2) | 6.1 (18.6) | 2.3 (3.2) | 5.1 (15.8) | 2.8 (1.8) | 0.2 (0.6) | 3.0 (0.0) | 1.2 (6.6) | 2.0 (1.8) |
| Difficulty Performing Routine Tasks | 1.2 (2.3) | 2.5 (2.0) | 1.6 (7.2) | 0.6 (0.2) | 2.0 (9.2) | 2.9 (1.9) | 6.3 (12.1) | 2.5 (2.2) | 0.4 (1.3) | 1.5 (0.0) | 10.4 (15.8) | 2.2 (1.4) |
| Cognitive/psychomotor outcomes | ||||||||||||
| DSST | 10.1 (13.8) | 2.8 (1.4) | 7.3 (18.2) | 3.2 (2.1) | 6.5 (8.3) | 3.3 (2.1) | 5.5 (8.5) | 3.4 (1.8) | 6.2 (9.9) | 4.0 (2.4) | −3.6 (12.3) | 2.1 (1.7) |
| PASAT | 0.1 (4.7) | 2.9 (1.8) | 7.8 (19.6) | 3.9 (1.9) | 0.6 (4.0) | 3.4 (2.3) | 1.7 (3.7) | 2.6 (2.0) | 0.7 (4.5) | 3.7 (1.5) | 3.1 (8.7) | 2.3 (1.3) |
| DAT | 6.5 (8.6) | 3.9 (1.9) | 6.6 (16.9) | 3.7 (2.1) | 2.4 (13.9) | 2.2 (1.7) | −2.6 (12.6) | 3.6 (1.3) | 2.6 (11.1) | 2.6 (1.6) | −0.3 (12.4) | 3.0 (2.1) |
| DRUID | 2.1 (4.7) | 3.0 (1.9) | 2.6 (7.8) | 3.5 (2.2) | 0.4 (7.5) | 2.7 (2.0) | 0.2 (6.0) | 2.9 (1.9) | 3.1 (6.3) | 3.2 (1.5) | 7.3 (7.7) | 3.5 (2.2) |
| Physiological function | ||||||||||||
| Heart rate (beats/min) | −1.5 (24.3) | 2.6 (1.2) | −5.6 (16.7) | 2.9 (2.3) | 1.3 (10.9) | 2.2 (1.8) | −2.0 (15.2) | 3.0 (1.8) | −1.2 (13.2) | 3.2 (2.0) | 3.8 (14.3) | 3.6 (1.8) |
| Diastolic blood pressure (mmHg) | 8.4 (14.1) | 2.6 (2.0) | −3.5 (14.9) | 3.6 (2.1) | 4.6 (15.5) | 1.6 (1.2) | −5.5 (8.8) | 4.1 (1.5) | −9.5 (11.1) | 3.2 (1.9) | −7.0 (14.1) | 2.5 (1.8) |
| Systolic blood pressure (mmHg) | 2.5 (20.1) | 3.1 (2.1) | 9.7 (17.2) | 3.4 (2.0) | 10.4 (18.9) | 2.4 (1.6) | 0.6 (13.7) | 2.2 (1.5) | −4.5 (16.5) | 3.4 (2.2) | 0.0 (22.2) | 3.2 (1.8) |
Health and functioning
A significant main effect of Time was observed for “Emotional Well-Being” on the SF-36 (Table S6); no significant effects were observed for other factors. There were no unanticipated or serious adverse events during the study. In all dose conditions, including CBD alone, one-to-two participants experienced minor adverse effects including nausea, headache, and dizziness. One participant in the CBD alone condition reported constipation that resolved by Day 21 (ie, after the washout period). Most of these events occurred in the acute dosing stage (Phase 1). One individual in the 3.7 mg Δ9-THC dose condition developed hives on Day 12 of the study that were most likely not related to the study drug and another participant in the same condition withdrew from the study due to concerns about the drug’s effects and potential impact on daily functioning; this participant was replaced in the study because they did not complete Phases 2 or 3 and, thus, was not included in data analyses.
Cognitive/psychomotor performance
There were significant main effects of time observed for all four cognitive tasks, and a significant Drug Condition × Time interaction for performance on the DAT (Figure 3, Table S6). However, planned comparisons revealed that there were no significant differences between any of the Δ9-THC-containing dose conditions and CBD alone (Table 2).
Physiological effects
Discussion
This study extends previous work9,10, 15,16 assessing urine drug test results among people using CBD-dominant cannabis products by expanding the frequency and timing of testing relative to drug exposure as well as the range of Δ9-THC doses included in the CBD-dominant product. Previous work by Dahlgren et al.9 and Ferretti et al.10 showed that positive urine drug test results are common among adults chronically using CBD-dominant cannabis oils. Consistent with that, this study showed that positive urine drug test results were observed in at least one participant after a single acute dose for the Δ9-THC dose conditions at or greater than 1.0 mg Δ9-THC and at least one participant in all dose conditions during the twice-daily outpatient dose phase, with rates of positive tests correlating with Δ9-THC content. Similar to the study by Peters et al.,15 few participants had positive urine drug tests after the washout period, suggesting that a one-week washout is sufficient for a negative urine test in most individuals taking CBD-dominant products with relatively low doses (0.5–3.7 mg Δ9-THC in this study and 5.4–21.6 mg Δ9-THC in the Peters et al. study) in the short term (exposure was 7–14 days across the two studies). Note, however, that results may vary with higher Δ9-THC doses or longer periods of exposure due to the lipophilic nature of cannabinoids.
Whole blood pharmacokinetics of CBD in the present study are similar to results seen in other studies in that peak concentrations are highest for the metabolite 7-COOH-CBD, followed by CBD and then 7-OH-CBD.17,18 The notably higher accumulation of 7-COOH-CBD with chronic administration over 14 days compared to 7-OH-CBD reflects and extends the findings from Taylor et al.17 that illustrated increasing concentrations of 7-COOH-CBD after 7 days of use. CBD and its metabolites showed consistent blood concentrations across the different Δ9-THC doses indicating that Δ9-THC does not influence CBD’s pharmacokinetics at these doses, contrasting with CBD’s known impact on Δ9-THC concentrations.19 The detection of Δ9-THC in the blood of most individuals in this study suggests that consumers of federally legal CBD-dominant cannabis products could be penalized if they are driving in one of the eighteen states that enforce either zero tolerance or non-zero per se laws in which the detection of Δ9-THC at certain concentrations (or at all) in the blood of drivers would be considered a crime.20 The relevance of this finding is also notable given the lack of interoceptive drug effects and absence of impairment on tests of cognitive or psychomotor performance in this study, which is consistent with prior research with CBD-dominant cannabis products.15, 21
Drawing conclusions about the pharmacodynamic effects of high CBD, low Δ9-THC products from this study are limited by the between-subjects design and variability of the data. A more accurate assessment of pharmacodynamic effects should occur in future studies powered to identify minimal doses of CBD-dominant cannabis that can consistently produce psychoactive effects. Another limitation is that some participants missed drug doses during Phase 2. However, only one participant missed more than four out of 29 possible doses and that participant was excluded from the Phase 2 and 3 analyses. Overall, 97% of doses were administered and verified, aligning with adherence in a similar chronic dosing study.22 Further, though the battery of neuropsychiatric assessments offers helpful insights into the cognitive effects of oral hemp products, additional research, including the use of driving simulators and other measures that better replicate occupational activities, would help ascertain the threshold dose of Δ9-THC likely to meaningfully impact daily functioning in healthy adults. Lastly, this project involved one formulation (ie, MCT oil) that is common in hemp-based products; the results of this study may not generalize to hemp products with different methods of administration, formulations (e.g. nano-emulsions) or cannabinoid content beyond Δ9-THC and CBD. Additional controlled studies are needed to address these gaps.
As the legal landscape of cannabis and hemp evolves, it is expected that rates of use in the general population will continue to increase. This research highlights the urgent need to develop novel strategies to differentiate between the use of THC-dominant cannabis products (which are federally illegal in the U.S. and many other jurisdictions) versus CBD-dominant “hemp” products (that are federally legal in the U.S. and many other jurisdictions) on drug test outcomes. Further, there is a need to continue to explore policies that differentially regulate products likely to engender a high risk of adverse behavioral or health consequences versus those with low risk and potential therapeutic benefit.
Supplementary Material
Acknowledgments
Dr Zamarripa had full access to the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. We thank the support staff of the Johns Hopkins University Behavioral Pharmacology Research Unit, and Martin Jacques and Melissa Beals from Clinical Reference Laboratory for outstanding contributions to the implementation of this study. We thank ElSohly Laboratories Inc. for critical services and material support.
Contributor Information
David Wolinsky, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
C Austin Zamarripa, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
Tory R Spindle, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
McKenna Klausner, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
Edward J Cone, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
Ruth E Winecker, RTI International, Research Triangle Park, NC 27709, United States.
Svante Vikingsson, RTI International, Research Triangle Park, NC 27709, United States.
Ronald R Flegel, Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States.
Eugene D Hayes, Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States.
Lisa S Davis, Division of Workplace Programs (DWP), Substance Abuse and Mental Health Services Administration (SAMHSA), Rockville, MD 20857, United States.
David Kuntz, Clinical Reference Laboratory, Lenexa, KS 66214, United States.
Marcel Bonn-Miller, Charlotte’s Web, Louisville, CO 80027, United States.
George E Bigelow, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
Ryan Vandrey, Behavioral Pharmacology Research Unit, Johns Hopkins University School of Medicine, Baltimore, MD 21224, United States.
Supplementary data
Supplementary data are available at Journal of Analytical Toxicology online.
Conflict of interest
Dr Bonn-Miller is an employee of Charlotte’s Web, prior employee of Canopy Growth Corporation, and board member of DeFloria. Dr Vandrey has been paid as a consultant or scientific advisory board member for Syqe Medical Ltd, Jazz Pharmaceuticals, Charlotte’s Web, Schedule 1 Therapeutics, and WebMD outside the submitted work. Dr Spindle has been a paid consultant for Canopy Health Innovations Inc. and has received funding from Cultivate Biologics for an unrelated study.
Funding
This research was supported by the Substance Abuse and Mental Health Services Administration (SAMHSA). Ronald Flegel, Eugene Hayes, and Lisa Davis have prepared or contributed to this article in their personal capacity. The views and opinions expressed are the author’s/authors’own and do not necessarily represent the views, opinions, or policies of the Substance Abuse and Mental Health Administration, the Department of Health and Human Services, or the United States government.
Data availability
The data underlying this article are available in the article and its supplementary materials.
References
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Associated Data
Supplementary Materials
Data Availability Statement
The data underlying this article are available in the article and its supplementary materials.