Investigation of utility of cerebrospinal fluid drug concentration as a surrogate for interstitial fluid concentration using microdialysis coupled with cisternal cerebrospinal fluid sampling in wild-type and Mdr1a(−/−) rats
Bibliographic record
Abstract
In drug discovery, the cerebrospinal fluid (CSF) drug concentration (CCSF) has been used as a surrogate for the interstitial fluid (ISF) concentration (CISF). However, the CCSF-to-CISF gradient suggested for P-glycoprotein (P-gp) substrates in rodents causes uncertainty in CISF estimations and subsequent pharmacokinetic-pharmacodynamic analyses. To evaluate the utility of CCSF as a surrogate for CISF, this study directly compared the CCSF with the CISF of 12 compounds, including P-gp substrates, under steady-state conditions in wild-type and Mdr1a(-/-) rats using microdialysis coupled with cisternal CSF sampling. In wild-type rats, the ISF-to-unbound plasma (Kp,uu,ISF) and CSF-to-unbound plasma (Kp,uu,CSF) concentration ratios of the P-gp substrates, except for metoclopramide, were lower than those of the non-P-gp substrates, and the Kp,uu,CSF values were within or close to 3-fold of the Kp,uu,ISF values for all the compounds examined. The Kp,uu,CSF values of the selected P-gp substrates increased in Mdr1a(-/-) rats with a similar magnitude to the Kp,uu,ISF values, resulting in the Kp,uu,CSF-to-Kp,uu,ISF ratios being unchanged. These results suggested that P-gp-mediated active efflux at the blood-brain barrier is a major determinant not only for CISF, but also for CCSF, and that CCSF can be used as a surrogate for CISF even for P-gp substrates in rats.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), 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".