Population pharmacokinetics of cannabidiol and the impact of food and formulation on systemic exposure in children with drug‐resistant developmental and epileptic encephalopathies
Bibliographic record
Abstract
Abstract Objective Identifying factors influencing cannabidiol (CBD) exposure can optimize treatment efficacy and safety. We aimed to describe the population pharmacokinetics of CBD in children with drug‐resistant developmental and epileptic encephalopathies (DEEs) and assess the influence of environmental, pharmacological, and clinical characteristics on CBD systemic exposure. Methods Data from two pharmacokinetic studies of patients aged 2–18 years with DEEs were included (N = 48 patients). Serial blood samples were collected during maintenance treatment, before and after the morning dose, and up to 6 h after a dose of a purified CBD oil formulation, with or without a normocaloric breakfast. CBD plasma concentrations were also available following administration of a CBD‐enriched formulation. Samples were quantified using a validated liquid chromatography/tandem mass spectrometry assay. A CBD population pharmacokinetic model was developed using nonlinear mixed‐effects modeling. The effects of formulation, concomitant food intake, and demographic, clinical, and pharmacological factors on CBD pharmacokinetics were evaluated. Simulated maximum plasma concentration (Cmax) and area under the concentration–time curve between 0 and 12 h (AUC0‐12) were calculated. Results A one‐compartment model with transit compartments and first‐order elimination best described CBD pharmacokinetics. Mean values for CBD apparent clearance (CL/F) and volume of distribution (V/F) were 143.5 L/h and 1892.4 L, respectively. Weight was allometrically scaled for V/F and CL/F, sex was associated with V/F, and both formulation and food condition were associated with F (relative bioavailability). CBD Cmax increased by 41% and AUC0‐12 by 45% when CBD was administered with food compared to fasting. Dose‐normalized AUC0‐12 was approximately 50% lower with CBD‐enriched oil compared to purified CBD. Significance In the present study, we described the effects of food and formulation on CBD exposure in children with DEEs. Increased CBD exposure with food intake and significant changes in drug exposure when switching between CBD formulations should be considered in patient management.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".