The Influence of Pharmacogenetic Factors on the Pharmacokinetics of Morphine and Its Metabolites in Pediatric Patients: A Systematic Review
Bibliographic record
Abstract
Morphine is a potent analgesic used for treating surgical and cancer pain. Despite being the drug of choice for the management of severe pain in children, the high interindividual variability in morphine pharmacokinetics limits its clinical utility to effectively relieve pain without adverse effects. This review was conducted to identify and describe all studies that have assessed the effect of genetic factors on the pharmacokinetics of morphine and its main metabolites in children. Embase and Medline databases were used to conduct the literature search, and the systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Of the 188 articles screened and after the application of specific inclusion and exclusion criteria, the review identified 8 studies. These studies suggest that genetic variants of selected metabolic enzymes and transporters may play a role in the observed interindividual variability in morphine plasma concentrations. Variants of the genes SLC22A1 and ABCC3 had the most supporting evidence for genetic variants that influence morphine and morphine metabolites pharmacokinetics. Although the available evidence suggests a potential genetic contribution to the variability in morphine concentration, the heterogeneity of the included studies in terms of experimental design and small sample sizes in some studies makes it challenging to propose the use of genetic biomarkers to personalize morphine dosing. This underscores the need to conduct more comprehensive and large-scale pharmacokinetic-pharmacogenetic studies to determine how or if genetic testing can optimize morphine safety and effectiveness in children.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".