Physiologically‐Based Pharmacokinetic Modeling Characterizes the CYP3A‐Mediated Drug‐Drug Interaction Between Fluconazole and Sildenafil in Infants
Why this work is in the frame
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Bibliographic record
Abstract
Physiologically‐based pharmacokinetic (PBPK) modeling can potentially predict pediatric drug‐drug interactions (DDIs) when clinical DDI data are limited. In infants for whom treatment of pulmonary hypertension and prevention or treatment of invasive candidiasis are indicated, sildenafil with fluconazole may be given concurrently. To account for developmental changes in cytochrome P450 (CYP) 3A, we determined and incorporated fluconazole inhibition constants ( K I ) for CYP3A4, CYP3A5, and CYP3A7 into a PBPK model developed for sildenafil and its active metabolite, N‐desmethylsildenafil. Pharmacokinetic (PK) data in preterm infants receiving sildenafil with and without fluconazole were used for model development and evaluation. The simulated PK parameters were comparable to observed values. Following fluconazole co‐administration, differences in the fold change for simulated steady‐state area under the plasma concentration vs. time curve from 0 to 24 hours (AUC ss,0–24 ) were observed between virtual adults and infants (2.11‐fold vs. 2.82‐fold change). When given in combination with treatment doses of fluconazole (12 mg/kg i.v. daily), reducing the sildenafil dose by ~ 60% resulted in a geometric mean ratio of 1.01 for simulated AUC ss,0–24 relative to virtual infants receiving sildenafil alone. This study highlights the feasibility of PBPK modeling to predict DDIs in infants and the need to include CYP3A7 parameters.
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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 | 0.000 |
| 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 | 0.002 |
| 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 it