Sex Differences in Pharmacokinetics of Doxylamine–Pyridoxine Combination
Bibliographic record
Abstract
INTRODUCTION: Most bioequivalence studies are conducted in males, even for drugs aimed exclusively for women, assuming that bioequivalence variability is similar between sexes. To examine this assumption, we compared the bioequivalence and pharmacokinetics of Diclectin and Diclegis (doxylamine–pyridoxine combination), exclusively aimed at nausea and vomiting of pregnancy, between health young men and women. METHODS: A single dose (2×10–10 mg) bioavailability study. Healthy young males (n=12) and nonpregnant females (n=12). After a 21-day washout, dose administration and blood sampling were repeated. Doxylamine, pyridoxine, and its metabolites were measured. Differences in pharmacokinetic parameters and their variances between males and females were assessed. RESULTS: Females had significantly larger area under the curve at time 0 for doxylamine (1,550.0 ng*hr/mL±289.8 compared with 1,272.4 ng*hr/mL±265.1) (P=.001) and pyridoxine (35.2 ng*hr/mL±15.3 compared with 25.2 ng*hr/mL±7.8) (P=.006) compared with males. Males (2,352 ng*hr/mL±513) had a significantly larger area under the curve at time 0 for pyridoxal-5′-phosphate (1726 ng*hr/mL±603) (P<.001). A higher maximum concentration for doxylamine was observed in females (106.9 ng/mL±17.1 compared with 86.3 ng/mL±13.2) (P<.001). The maximum concentration for pyridoxal-5′-phosphate was higher in males (49.3 ng/mL±9.8) compared with females (41.0 ng/mL±16.2) (P=.037). Bioequivalence variability of doxylamine, pyridoxine, and pyridoxal-5′-phosphate was different between the sexes. CONCLUSION: As a result of pharmacokinetic differences, large variability, and lack of bioequivalence between sexes, our results support the claim that bioequivalence of drugs aimed for women should not be conducted in males, because they are clinically irrelevant in predicting clinical reality.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".