Sub-cellular sequestration of alkaline drugs in lysosomes
Bibliographic record
Abstract
Background and purpose: Lysosomal-targeted drug delivery can open a new strategy for drug therapy. However, there is currently no universally accepted simulated or artificial lysosomal fluid utilized in the pharmaceutical industry or recognized by the United States Pharmacopeia (USP). Experimental procedure: We prepared a simulated lysosomal fluid (SLYF) and compared its composition to a commercial artificial counterpart. The developed fluid was used to test the dissolution of a commercial product (Robitussin ® ) of a lysosomotropic drug (dextromethorphan) and to investigate in-vitro lysosomal trapping of two model drugs (dextromethorphan and (+/-) chloroquine). Findings/Results: The laboratory-prepared fluid or SLYF contained the essential components for the lysosomal function in concentrations reflective of the physiological values, unlike the commercial product. Robitussin ® passed the acceptance criteria for the dissolution of dextromethorphan in 0.1 N HCl medium (97.7% in less than 45 min) but not in the SLYF or the phosphate buffer media (72.6% and 32.2% within 45 min, respectively). Racemic chloroquine showed higher lysosomal trapping (51.9%) in the in-vitro model than dextromethorphan (28.3%) in a behavior supporting in-vivo findings and based on the molecular descriptors and the lysosomal sequestration potential of both. Conclusion and implication: A standardized lysosomal fluid was reported and developed for in-vitro investigations of lysosomotropic drugs and formulations.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".