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Record W2056231252 · doi:10.2174/187221309789257414

Recent Development of Drug Delivery Systems for the Treatment of Asthma and Related Disorders

2009· review· en· W2056231252 on OpenAlexaboutno aff
Hajime Takizawa

Bibliographic record

VenueRecent Patents on Inflammation & Allergy Drug Discovery · 2009
Typereview
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAsthmaDrug developmentDrugDrug deliveryIntensive care medicinePharmacologyInternal medicineNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

It is well established that airway inflammatory processes are pivotal as the pathological features of asthma. Prominent infiltration of eosinophils and Th2 lymphocytes is a hallmark of the allergic inflammation, and inhaled corticosteroids markedly suppress such inflammatory changes, resulting in clinical beneficial effects. Aerosol delivery of anti-asthma drugs such as corticosteroids is ideal from the standpoint of maximizing local effects in the lung as well as minimizing systemic side effects compared with oral therapy. The 1987 Montreal protocol banned chlorofluorocarbon (CFC) propellant in pressurized metered-dose inhalers (pMDIs), which has been replaced with hydrofluoroalkane (HFA) propellant. The aerodynamic diameters of HFA are much smaller than those of CFC, suggesting a greater distribution in peripheral airways. New types of dry powder inhalers (DPIs) and nebulizers, that do not use propellants, also have been introduced. Performance of each drug delivery device depends on a variety of factors including the device type, particle size and distribution, the product formulation and patient-related factors. Therefore, drug delivery can differ even when the same drug is delivered via an HFA pMDI, a CFC pMDI, a DPI or a nebulizer. New and advanced devices can be helpful to maximize the advantages of these modes of drug delivery, and patents of novel invention of inhalation devices are described.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.033
GPT teacher head0.286
Teacher spread0.253 · 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 designOther design
Domainnot available
GenreReview

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

Citations9
Published2009
Admission routes1
Has abstractyes

Explore more

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