Prediction of Milk/Plasma Concentration Ratio of Drugs
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
OBJECTIVE: The milk to plasma (m/p) concentration ratio of drugs is used to estimate the amount of drug offered to the suckling infant. Published literature was reviewed to identify drugs for which sufficient data exist for calculation of m/p ratio and to examine whether the existing empiric data agree with the published method of Atkinson for mathematical prediction of m/p ratios based on physiochemical characteristics. METHODS: Using a comprehensive reference text, we identified studies reporting sufficient data to calculate m/p ratio based on the AUC for milk and plasma. Subsequently, we calculated the m/p ratio with Atkinson's formula based on pKa, lipophilicity, and protein binding. We then correlated the empiric versus predicted (calculated) m/p ratios. RESULTS: Of 192 drugs of which at least some data on milk accumulation have been published, there were sufficient data to quantify m/p ratios for only 69 medications (78 studies). There was no significant correlation between the empiric m/p ratios and the predicted values using the Atkinson's model. CONCLUSIONS: Reliable data on m/p concentration ratios exist for few medications. Presently, there is no appropriate model to predict milk concentrations of drugs in humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| 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) | 0.001 | 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