Development of Liquid Chromatography-Tandem Mass Spectrometry Methods of Cannabinoids for Pediatric Patient Samples
Bibliographic record
Abstract
Thirty percent of pediatric epilepsies become resistant to conventional treatments, such as antiepileptic drugs and ketogenic diets. Growing anecdotal evidence of using Cannabis for treating epilepsy has prompted parents to acquire Cannabis products for their children without the consent or guidance of their pediatrician. Limited scientific based evidence exists for pediatric epilepsy and Cannabis therapy. Establishing a standard dosage regimen to ensure the safety and efficacy with Cannabis based medicine for pediatric epilepsy requires conducting a pharmacokinetic (PK) study to define the age-dependent pharmacokinetic parameters.\n The Cannabidiol and Children with Refractory Epileptic Encephalopathy (CARE-E) open-labelled dose escalation study utilizing a 1:20 delta9-tetrahydrocannabinol (THC): cannabidiol (CBD) Cannabis herbal extract containing 4% cannabichromene (CBC) will establish a recommended dose for the PK study and define the relationship between the minimum cannabinoid plasma concentration at steady state (Css,min) and dose. A sensitive and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was utilized to quantify the Css,min. Participant A-04 exhibited a greater than proportional increase in Css,min relative to the dose (10-12 mg/kg/day), indicating non-linear PK. No THC intoxication was observed during the study. All participants displayed linear pharmacokinetics and seizure frequency reductions at 5-6 mg/kg/day, recommending the 5-6 mg/kg/day dose to be used for the PK study. \n Ketogenic diets, a high fat diet used for pediatric epilepsy, may alter the plasma levels of lipoproteins, a major plasma protein in cannabinoid plasma protein binding. The unbound cannabinoid concentration is only able to produce a pharmacological effect; therefore, it is imperative to determine the effects ketogenic diets impart on protein binding to conclude if dosage adjustments are necessary. Cannabinoids may exhibit non-specific binding or buffer solubility issues observed with the commonly used plasma protein binding assays. A novel 3-extraction technique was developed for lipophilic compounds to avoid these issues. A comparative analysis was conducted between commonly used techniques (ultrafiltration and rapid equilibrium dialysis) and the 3-solvent extraction technique, with the 3-solvent extraction technique providing higher cannabinoid recovery and assay reproducibility, indicating 82.7%, 82.1%, 87.0%, and 93.4% plasma protein binding of 11-OH-THC, CBD, THC, and CBC, respectively. \n With legalization of recreational Cannabis, there has been growing concern over pregnant women consuming Cannabis. Cannabinoids can cross the blood placental barrier and reach the fetal systemic circulation. Increased Cannabis use during pregnancy would be a public health concern; therefore, it is crucial to determine the prevalence of prenatal Cannabis exposure. This was determined using residual neonate dried blood spot (DBS) screening cards collected from April, May, and June 2018 (pre-legalization) and April, May, and June 2019 (post-legalization). Due to its long half-life 11-nor-9- carboxy-delta9-tetrahydrocannabinol (THC-COOH), an inactive THC metabolite, is a suitable drug marker for Cannabis exposure. A quantitative LC-MS/MS assay was initially developed, however, factors such as hematocrit effect, chromatographic effect, and sample heterogeneity contributed to inaccurate and imprecise cannabinoid quantification. Alternatively, a qualitative LC-MS/MS assay, which solely utilizes a limit of detection (LOD), was applied, establishing a LOD of 1.47 ng/mL. Currently, we detected THC-COOH in 11 of 220 Saskatchewan residual neonate DBS cards collected pre-legalization, indicating a 5% prenatal Cannabis exposure rate. \n The recommended dose obtained from the CARE-E dose escalation study and the LC-MS/MS assay will be utilized in single oral dose pharmacokinetic studies in the pediatric population to characterize the required age dependent pharmacokinetic parameters for establishing a standard dosage regimen. The 3-solvent extraction technique will determine the influence ketogenic diets have on the cannabinoid plasma protein binding profile and if dosage adjustments are necessary. Complete analysis of the pre- and post-legalization Saskatchewan, Manitoba, and British Columbia residual neonate dried blood spot samples will establish the prevalence of prenatal Cannabis exposure in each province.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.006 |
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 source (direct Gemma or distilled Codex), 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".