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Record W4280541826 · doi:10.1039/d1bm01947c

Interplay between the linker and polymer molecular weight of a self-assembling prodrug on the pharmacokinetics and therapeutic efficacy

2022· article· en· W4280541826 on OpenAlexafffund
Anne Nguyen, Elham Rouhollahi, Roland Böttger, Chun Yat Ong, Po‐Han Chao, Jiamin Wu, Yao Chen, Shyh‐Dar Li

Bibliographic record

VenueBiomaterials Science · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of British Columbia
FundersScience and Engineering Research CouncilUniversity of TokushimaUniversity of British ColumbiaCanadian Institutes of Health ResearchMitacsDeutsche ForschungsgemeinschaftCanada Foundation for Innovation
KeywordsLinkerConjugateProdrugChemistryConjugated systemDrug deliveryCombinatorial chemistryAmphiphileAmideSmall moleculeSolubilityAqueous solutionPolymerOrganic chemistryCopolymerBiochemistry

Abstract

fetched live from OpenAlex

than free GA) and sufficient drug release (1.68 ± 0.13% per day), leading to superior anti-tumor efficacy compared to other formulations, while the corresponding amides (5000-A-NP) displayed the most prolonged circulation but only moderate efficacy likely due to insufficient drug release. Our work highlights the importance of diligently studying SAR on drug conjugates to improve drug delivery and confirms the robustness of using the click platform to generate a conjugate library with chemical diversity.

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 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)0.003
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.017
GPT teacher head0.283
Teacher spread0.267 · 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 teacher head, 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

Citations5
Published2022
Admission routes2
Has abstractyes

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