Synthesis of a Gemcitabine Prodrug for Remote Loading into Liposomes and Improved Therapeutic Effect
Bibliographic record
Abstract
The chemotherapeutic gemcitabine was actively and stably loaded into lipid nanoparticles through the formation of a prodrug. Gemcitabine was chemically modified to increase the lipophilicity and introduce a weak base moiety for remote loading. Several derivatives were synthesized and screened for their potential to be good liposomal drug candidates for remote loading by studying their solubility, stability, cytotoxicity, and loading efficiency. Two morpholino derivatives of GEM (22 and 23) were chosen as the preferred prodrugs for this purpose as they possessed the best loading efficiencies (100% for drug-to-lipid ratio of 0.36 w/w). This is a considerable improvement over a passive loading strategy where typical loading efficiencies are on the order of ∼10-20% for a drug-to-lipid ratio of ∼0.01. Liposomes loaded with these two prodrugs were studied in an s.c. tumor model in vivo and showed improved therapeutic effect over free GEM (∼2-fold) and saline control (8- to 10-fold). This work demonstrates how chemical modification of a known hydrophilic drug can lead to improved loading, stability, and drug delivery in vivo.
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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 | 0.001 |
| 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 | 0.000 |
| 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".