Peptide-Chlorambucil Conjugates Combat Pgp-Dependent Drug Efflux
Bibliographic record
Abstract
Cancer drugs, such as the ovarian cancer drug adriamycin, are effective at slowing disease progression and improving remission rates in patients. However, drug resistance often arises, limiting the activity of these agents in some patients. In particular, efflux pumps, which export drugs out of cells, limit the efficacy of a variety of anticancer agents. While inhibitors to block these pumps currently exist, they are usually not used clinically because they alter other drug properties. Here, we report a novel inhibitor of drug efflux that only reduces pump activity temporarily. This decreases the risk that it will alter drug function and cause nonspecific toxicity. P-glycoprotein efflux pumps are commonly overexpressed by malignant cells and are a major contributing factor to the development of drug resistance. Many therapeutics containing basic nitrogens, hydrophobic character, or aromaticity are efficiently eliminated from cells, and Pgp inhibitors must often be coadministered to limit this process. However, currently available inhibitors often alter the pharmacokinetic profiles of therapeutics or increase off-target toxicity, limiting their clinical utility. Here, we report the development of a novel panel of peptide-chlorambucil conjugates capable of efficiently decreasing efflux of Pgp substrates. These conjugates selectively improve adriamycin toxicity and uptake for short, but not prolonged, periods reducing the risk of altered pharmacokinetics and off-target effects.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".