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A Pharmacokinetic Overview of Nanotechnology-Based Drug Delivery Systems: An ADME-Oriented Approach

2013· review· en· W1973881933 on OpenAlex
Mehrdad Hamidi, Amir Azadi, Pedram Rafiei, Hajar Ashrafi

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

VenueCritical Reviews in Therapeutic Drug Carrier Systems · 2013
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsADMEPharmacokineticsDrug deliveryDrugPharmacologyDistribution (mathematics)MedicineNanotechnologyMaterials scienceMathematics

Abstract

fetched live from OpenAlex

With the extensive progress in nanotechnology-based drug delivery systems, pharmacokinetic evaluations have gained much attention from researchers as a central part of the study of these systems. Because the fulfillment of any therapeutic goal(s) by a novel drug delivery system requires that the absorption, distribution, metabolism, and excretion (ADME) be considered from the early stages of the system design to the final clinical evaluations, extensive knowledge of the pharmacokinetic aspects related to ADME is a crucial part of research in this field. The main objectives of the nanotechnology-based drug delivery systems from a pharmacokinetic viewpoint are (1) an improved drug-release profile in vivo, (2) enhanced drug absorption, (3) site-directed drug distribution, (4) a modified drug metabolism pattern, (5) prolonged drug residence time in body (e.g., in blood circulation), and (6) delayed and/or decreased renal excretion of the drug. Accordingly, the purpose of the current review is to present an insightful summary of pharmacokinetic analyses of nanotechnology-based drug delivery systems along with a critical review of recent findings.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.901
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.090
GPT teacher head0.366
Teacher spread0.275 · 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