Pharmacogenetic-guided cannabis usage in the community pharmacy: evaluation of a pilot program
Bibliographic record
Abstract
BACKGROUND: Pharmacists possess a skillset suited to provide evidence-based guidance to current and potential users of cannabis. Clinical pharmacogenomics research has made significant progress in defining which genetic variations are important for influencing inter-patient variability in response to cannabis. This study aims to evaluate the practicality and impact of pharmacogenetic testing in the community pharmacy to help guide in the safe use of cannabis. METHODS: The pilot program was designed as open-label, non-randomized, and observational. Two busy, urban community pharmacies, operating under the brand Shoppers Drug Mart, in Toronto, Ontario, Canada offered pharmacogenomic testing to cannabis users as part of their professional services program over a period of 2 months. Eligible patients received buccal swabs using a DNA cheek swab kit. De-identified, barcoded samples were then sent by regular mail to an off-site CLIA-certified laboratory for analysis in Mississauga, Canada. A pharmacogenetic testing platform from Lobo Genetics® was utilized for translation of participants' DNA with respect to CYP2C9, AKT1 and COMT genetic polymorphisms. Following genomic data translation, personalized, evidence-based recommendations were generated. Pharmacists provided a cannabis pharmacogenetic consultation to patients via telephone or in-person. RESULTS: Twenty patients enrolled in the study. Pharmacogenetic screening identified 95% as having the CYP2C9*1/*1 genotype (suggesting normal THC metabolism); 35 and 25% had AKT1 genotypes suggesting intermediate risk (C/T genotype) or high risk (C/C genotype), respectively, for cannabis-induced psychosis; and 45 and 10% had COMT genotypes suggesting intermediate risk (Val/Met genotype) or high risk (Val/Val genotype), respectively for cannabis-induced neurocognitive impairment. After the pharmacogenetic consultation, 65% of patients reported an increased comfort level in choosing a specific strength/strain of cannabis for use in the future; 75% considered the consultation of high value providing information potentially vital to their health and wellbeing. CONCLUSION: Although the study did not find any CYP2C9 variants associated with highly diminished THC metabolism, most of these patients do carry genetic variants that may potentially predispose them to the development of psychosis and memory impairment. Similar initiatives can potentially improve patient safety and empower individuals to make informed decisions about cannabis use and possible complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".