Prediction of Phase I single-dose pharmacokinetics using recombinant cytochromes P450 and physiologically based modelling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
1. Ten compounds from the Merck Research Laboratories pipeline were selected to evaluate the utility of using intrinsic clearance derived from recombinantly expressed cytochromes P450 (CYP) and physiologically based pharmacokinetic modelling to predict Phase I pharmacokinetics using simCYP. The compounds selected were anticipated to be eliminated predominantly by P450 metabolism. 2. There was a reasonable agreement between the predicted and actual clinical exposure with 80% of the predicted exposures being within three-fold of the observed values. Furthermore, prediction of C(t) (plasma concentration at a specified time point) and T(max) were acceptable with greater than or equal to 70% of the predicted data being within three-fold of the observed values. However, prediction of C(max) was unreliable and may have been due to error in predicting the time-dependent change in volume of distribution and/or error in estimating absorption rate. 3. Although it is acknowledged that research is needed to improve predictive performance, the data presented are supportive of using recombinant P450 intrinsic clearance and physiologically based pharmacokinetic modelling to predict Phase I pharmacokinetics for compounds eliminated by P450 metabolism.
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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) | 0.000 | 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 | 0.001 |
| 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 it