Use of a Physiologically Based Pharmacokinetic Model for Rats to Study the Influence of Body Fat Mass and Induction of CYP1A2 on the Pharmacokinetics of TCDD
Bibliographic record
Abstract
2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a highly lipophilic chemical that distributes into adipose tissue, especially at low doses. However, at high doses TCDD sequesters in liver because it induces cytochrome P450 1A2 (CYP1A2) that binds TCDD. A physiologically based pharmacokinetic (PBPK) model was developed that included an inducible elimination rate of TCDD in the Sprague-Dawley rat. Objectives of this work were to characterize the influence of induction of CYP1A2 and adipose tissue mass fraction on the terminal elimination half-life (t1/2) of TCDD using this PBPK model. When the model assumes a fixed elimination of TCDD, t1/2 increases with dose, due to hepatic sequestration. Because experimental data indicate that the t1/2 of TCDD decreases with dose, the model was modified to include an inducible elimination rate. The PBPK model was then used to compare the t1/2 after an increase of adipose tissue mass fraction from 6.9 to 70%. The model suggests that at low exposures, increasing adipose tissue mass increases the terminal t1/2. However, at higher exposures, as CYP1A2 is induced, the relationship between adipose tissue mass and t1/2 reaches a plateau. This demonstrates that an inducible elimination rate is needed in a PBPK model in order to describe the pharmacokinetics of TCDD. At low exposures these models are more sensitive to parameters related to partitioning into adipose tissue.
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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 | 0.000 |
| 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 | 0.001 |
| 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".