Drug ratio–dependent antitumor activity of irinotecan and cisplatin combinations <i>in vitro</i> and <i>in vivo</i>
Why this work is in the frame
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Bibliographic record
Abstract
Irinotecan and cisplatin are two established anticancer drugs, which together constitute an effective combination for treating small-cell lung cancer. We investigated whether the efficacy of this combination could be improved by controlling drug ratios following in vivo administration. Irinotecan and cisplatin combinations were evaluated systematically for drug ratio-dependent synergy in vitro using a panel of 20 tumor cell lines. In vitro screening informatics on drug ratio-dependent cytotoxicity identified a consistently antagonistic region between irinotecan/cisplatin molar ratios of 1:2 to 4:1, which was bordered by two synergistic regions. Liposomal co-formulations of these two agents were developed that exhibited plasma drug half-lives of approximately 6 hours and maintained a fixed drug ratio for more than 24 hours. Drug ratio-dependent antitumor activity was shown in vivo for these liposome formulations, and irinotecan/cisplatin ratios between 5:1 and 10:1 were identified as therapeutically optimal. The relationship between irinotecan/cisplatin ratio and in vivo efficacy was consistent with in vitro drug ratio dependency results. Superior antitumor activity was observed for the liposome-encapsulated 7:1 molar ratio of irinotecan/cisplatin (designated CPX-571) compared with the free-drug cocktail in all models tested. Further efficacy studies in a range of human tumor xenografts, including an irinotecan-resistant model, showed that both liposomal agents contributed to the overall efficacy in a manner consistent with in vivo synergy. These results show the ability of drug delivery technology to enhance the therapeutic activity of irinotecan/cisplatin combination treatment by maintaining synergistic ratios in vivo. CPX-571, a fixed-ratio formulation of irinotecan and cisplatin, is a promising candidate for clinical development.
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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 | 0.000 | 0.000 |
| 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 it