<b> <i>In Vitro</i> </b> and <b> <i>in Vivo</i> </b> Characterization of Doxorubicin and Vincristine Coencapsulated within Liposomes through Use of Transition Metal Ion Complexation and pH Gradient Loading
Bibliographic record
Abstract
PURPOSE: There is an opportunity to augment the therapeutic potential of drug combinations through use of drug delivery technology. This report summarizes data obtained using a novel liposomal formulation with coencapsulated doxorubicin and vincristine. The rationale for selecting these drugs is due in part to the fact that liposomal formulations of doxorubicin and vincristine are being separately evaluated as components of drug combinations. EXPERIMENTAL DESIGN: Doxorubicin and vincristine were coencapsulated into liposomes using two distinct methods of drug loading. A manganese-based drug loading procedure, which relies on drug complexation with a transition metal, was used to encapsulate doxorubicin. Subsequently the ionophore A23187 was added to induce formation of a pH gradient, which promoted vincristine encapsulation. RESULTS: Plasma elimination studies in mice indicated that the drug:drug ratio before injection [4:1 doxorubicin:vincristine (wt:wt ratio)] changed to 20:1 at the 24-h time point, indicative of more rapid release of vincristine from the liposomes than doxorubicin. Efficacy studies completed in MDA MB-435/LCC6 tumor-bearing mice suggested that at the maximum tolerated dose, the coencapsulated formulation was therapeutically no better than liposomal vincristine. This result was explained in part by in vitro cytotoxicity studies evaluating doxorubicin and vincristine combinations analyzed using the Chou and Talalay median effect principle. These data clearly indicated that simultaneous addition of vincristine and doxorubicin resulted in pronounced antagonism. CONCLUSION: These results emphasize that in vitro drug combination screens can be used to predict whether a coformulated drug combination will act in an antagonistic or synergistic manner.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".