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Overcoming the Road Blocks: Advancement of Block Copolymer Micelles for Cancer Therapy in the Clinic

2017· review· en· W2613525853 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecular Pharmaceutics · 2017
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchGlaxoSmithKlineU.S. Department of Defense
KeywordsCopolymerMicelleBlock (permutation group theory)Cancer therapyCancerChemistryMedicineNanotechnologyCombinatorial chemistryMaterials sciencePolymerInternal medicineOrganic chemistryMathematics

Abstract

fetched live from OpenAlex

With countless preclinical studies on block copolymer micelles (BCMs) successfully demonstrating the superiority of these advanced drug delivery formulations over conventional formulations, it remains somehow discouraging that only a few have reached clinical evaluation and practice. With a critical eye, this review aims to compare and summarize the preclinical and clinical data available on several BCM formulations and to identify their primary role in drug delivery as "carrier" or "solubilizer". This review focuses on polymeric micelles that have reached clinical evaluation and/or are being pursued commercially. Where available, we aim to compare the pharmacokinetics, toxicity, and efficacy data obtained in preclinical studies to identify the factors that likely played a key role in a decision to move these formulations forward from the bench to a first-in-human trial. Finally, we summarize clinical data obtained to date, where available, and conclude with the impact that each formulation has had on patients in terms of safety and efficacy.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.958
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.148
GPT teacher head0.448
Teacher spread0.300 · 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