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Record W4380550592 · doi:10.1002/adhm.202301033

Enzyme‐Triggered Intestine‐Specific Targeting Adhesive Platform for Universal Oral Drug Delivery

2023· article· en· W4380550592 on OpenAlexaff
Ying Li, Jung Seung Lee, Ameya R. Kirtane, Mengyuan Li, Charles William Coffey, Kaitlyn Hess, Aaron Lopes, Joy Collins, Siddartha Tamang, Keiko Ishida, Alison Hayward, Jacob Wainer, Adam Wentworth, Giovanni Traverso

Bibliographic record

VenueAdvanced Healthcare Materials · 2023
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilMassachusetts Institute of TechnologyBill and Melinda Gates Foundation
KeywordsDrug deliveryPharmacokineticsDrugPharmacologyDosingProdrugSmall intestineTargeted drug deliveryMedicineGastrointestinal tractInternal medicineMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

Patient adherence to chronic therapies can be suboptimal, leading to poor therapeutic outcomes. Dosage forms that enable reduction in dosing frequency stand to improve patient adherence. Variation in gastrointestinal transit time, inter-individual differences in gastrointestinal physiology and differences in physicochemical properties of drugs represent challenges to the development of such systems. To this end, a small intestine-targeted drug delivery system is developed, where prolonged gastrointestinal retention and sustained release are achieved through tissue adhesion of drug pills mediated by an essential intestinal enzyme catalase. Here proof-of-concept pharmacokinetics is demonstrated in the swine model for two drugs, hydrophilic amoxicillin and hydrophobic levodopa. It is anticipated that this system can be applicable for many drugs with a diverse of physicochemical characteristics.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.139
GPT teacher head0.427
Teacher spread0.289 · 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.

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

Citations8
Published2023
Admission routes1
Has abstractyes

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