MétaCan
Menu
Back to cohort
Record W4379364740 · doi:10.1016/j.jpha.2023.06.001

Applications and safety of gold nanoparticles as therapeutic devices in clinical trials

2023· review· en· W4379364740 on OpenAlex
Leeann Yao, Dejan Bojic, Mingyao Liu

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

VenueJournal of Pharmaceutical Analysis · 2023
Typereview
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of TorontoToronto General HospitalUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsClinical trialNanotechnologyMedicineDrug deliveryMedical physicsPathologyMaterials science

Abstract

fetched live from OpenAlex

Use of gold nanoparticles (GNPs) in medicine is an emerging field of translational research with vast clinical implications and exciting therapeutic potential. However, the safety of using GNPs in human subjects is an important question that remains unanswered. This study reviews over 20 clinical trials focused on GNP safety and aims to summarize all the clinical studies, completed and ongoing, to identify whether GNPs are safe to use in humans as a therapeutic platform. In these studies, GNPs were implemented as drug delivery devices, for photothermal therapy, and utilized for their intrinsic therapeutic effects by various routes of delivery. These studies revealed no major safety concerns with the use of GNPs; however, the number of trials and total patient number remains limited. Multi-dose, multi-center blinded trials are required to deepen our understanding of the use of GNPs in clinical settings to facilitate translation of this novel, multifaceted therapeutic device. Expanding clinical trials will require collaboration between clinicians, scientists, and biotechnology companies.

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)0.013
metaresearch head score (Gemma)0.001
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 score0.989
Threshold uncertainty score0.658

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.299
GPT teacher head0.535
Teacher spread0.236 · 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