Abstract A020: Liposomal topotecan with low-intensity focused ultrasound utilization to improve drug penetration with brain parenchyma in pediatric brain tumors
Bibliographic record
Abstract
Abstract The blood-brain barrier (BBB) remains a significant obstacle in delivering effective chemotherapeutics to treat pediatric brain tumors, limiting drug penetration and reducing therapeutic outcomes. To overcome this challenge, we investigated the use of liposomal topotecan (TPT), encapsulated in a sonosensitive formulation, designed for controlled release triggered by low-intensity focused ultrasound (LIFU). In this study, we evaluated the in vitro efficacy of a sonosensitive liposomal topotecan formulation. The liposomal topotecan was created using remote loading with an ammonium sulfate gradient. TPT was loaded at a drug-to-lipid ratio of 1:10. The liposome was composed of hydrogenated soy PC, cholesterol, and DSPE-PEG2000. IC50 assay comparing free topotecan to the liposomal topotecan indicated that the cytoxicity of free TPT is lower than liposomal TPT indicating a sustained release of drug which would decrease long term toxicity. In addition, pharmcokinetic fluorescent quantification of liposomal topotecan showed linear increase in free drug (ug/uL) as liposomal TPT concentration is increased in brain homogenates. We hypothesize that tumor growth inhibition and overall survival would be significantly improved in mice receiving LIFU-mediated liposomal topotecan delivery. Our future work includes additional pharmokinetics with survival analysis in vivo with and without low intensity focused ultrasound. These results highlight the potential of combining liposomal drug formulations with focused ultrasound to overcome the challenges of BBB permeability, offering a promising therapeutic strategy for improving drug accumulation and survival outcomes in pediatric brain tumor models. Citation Format: Avani Mangoli, Sarah Kim, Kathryn Blethen, Angela Everhart, Sasha Nikiforov, Gerry Grant, Luke Avigliano. Liposomal topotecan with low-intensity focused ultrasound utilization to improve drug penetration with brain parenchyma in pediatric brain tumors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Optimizing Therapeutic Efficacy and Tolerability through Cancer Chemistry; 2024 Dec 9-11; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(12_Suppl):Abstract nr A020.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".