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Record W2792625060 · doi:10.2217/nnm-2017-0338

Are Existing Standard Methods Suitable for the Evaluation of Nanomedicines: Some Case Studies

2018· article· en· W2792625060 on OpenAlex
Sabrina Gioria, Fanny Caputo, Patricia Urbán, Ciarán Manus Maguire, Susanne Bremer‐Hoffmann, Adriele Prina‐Mello, Luigi Calzolai, Dóra Méhn

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.

Bibliographic record

VenueNanomedicine · 2018
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsTrinity College
FundersEuropean Commission
KeywordsCommercializationNanomedicineNanotechnologyRisk analysis (engineering)Quality (philosophy)Biochemical engineeringComputer scienceEngineeringMedicineBusinessMaterials scienceNanoparticlePhysics

Abstract

fetched live from OpenAlex

The use of nanotechnology in medical products has been demonstrated at laboratory scale, and many resulting nanomedicines are in the translational phase toward clinical applications, with global market trends indicating strong growth of the sector in the coming years. The translation of nanomedicines toward the clinic and subsequent commercialization may require the development of new or adaptation of existing standards to ensure the quality, safety and efficacy of such products. This work addresses some identified needs, and illustrates the shortcomings of currently used standardized methods when applied to medical-nanoparticles to assess particle size, drug loading, drug release and in vitro safety. Alternative physicochemical, and in vitro toxicology methods, with the potential to qualify as future standards supporting the evaluation of nanomedicine are provided.

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)0.015
metaresearch head score (Gemma)0.008
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 score0.028
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.192
GPT teacher head0.462
Teacher spread0.270 · 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