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Record W7132883435

A Thermosensitive Liposome Formulation of Vinorelbine for the Treatment of Recurrent Rhabdomyosarcoma

2023· dissertation· W7132883435 on OpenAlexfundno aff
Maximilian Leo Regenold

Bibliographic record

VenueTSpace · 2023
Typedissertation
Language
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of Toronto
KeywordsVinorelbinePharmacokineticsDrugChemotherapyDrug deliveryCombination therapyImmunotherapyRhabdomyosarcoma
DOInot available

Abstract

fetched live from OpenAlex

Approximately one third of rhabdomyosarcoma (RMS) patients experience disease recurrence and subsequently face a dismal prognosis. In most cases, the disease recurrence involves or is confined to the primary disease site, highlighting the need for effective treatment approaches that can improve local control. Chemotherapy continues to play an important role in treating residual disease and preventing local recurrence but is often associated with severe adverse effects. Common strategies to improve efficacy and toxicity profiles of chemotherapy, including liposomal encapsulation, heavily rely on passive tumor targeting via the enhanced permeability and retention (EPR) effect. Due to the recognized heterogeneity associated with the EPR effect in humans, other approaches for achieving tumor targeted drug delivery are needed. This thesis aims (1) to develop a thermosensitive-liposome formulation of vinorelbine (ThermoVRL) to provide EPR-independent drug delivery targeted to the tumor, (2) to evaluate the therapeutic efficacy of ThermoVRL in combination with localized mild hyperthermia (HT) compared to treatment with a non-thermosensitive liposomal formulation of vinorelbine (NTSL-VRL) in murine models of RMS and to identify the underlying pharmacokinetics and biodistribution, and (3) to determine the therapeutic efficacy of ThermoVRL and HT in an immunocompetent model of RMS and to explore if the addition of immunotherapy (i.e., immune checkpoint inhibition therapy (ICI)) to this treatment approach can enhance systemic anti-tumor effects. In summary, this work successfully developed a ThermoVRL formulation. Treatment with ThermoVRL and HT afforded superior therapeutic efficacy relative to treatment with free drug in a mouse xenograft model of RMS. Importantly, pharmacokinetic and biodistribution assessments of vinorelbine revealed an increase in tumor specific drug delivery when administered as ThermoVRL compared to administration as NTSL-VRL. Studies employing a bilateral RMS tumor model in immunocompetent mice revealed that anti-tumor effects following treatment with ThermoVRL and HT remain largely localized to the primary tumor site. However, the addition of ICI significantly enhanced the systemic treatment effects of ThermoVRL in combination with HT. The results of these studies demonstrate that this delivery approach can confer targetability to an untargeted drug molecule and open the door to treatment combinations with ICI to enhance the systemic treatment capabilities of thermosensitive liposomes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.337
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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