Cited by 31Granular flow and fluidized bedsAdditive Manufacturing and 3D Printing TechnologiesDrug Solubulity and Delivery Systems

Pharmaceutical formulation and manufacturing using particle/powder technology for personalized medicines

Tahara, Kohei·2020·Advanced Powder Technology

Integrity signals

Registry

Crossref · 10.1016/j.apt.2019.10.031

Cites

58 of 58 references verified0 citation errors · 0 not checkable

Statistics

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Claims the paper makes

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  • Large datasets can be analyzed and processed by AI algorithms, enabling nanoparticles to dynamically adapt and respond to specific requirements of individual patients.

    “Large datasets can be analyzed and processed by AI algorithms, enabling nanoparticles to dynamically adapt and respond to the specific requirements of individual patients.340”

    From Smart nanoparticles for cancer therapy (2023) · cites this paper as [340]

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Authors
Tahara, K.
Affiliations
Gifu Pharmaceutical University (JP)
Corresponding author
Tahara, Kohei
Venue
Advanced Powder Technology
Publisher
Elsevier BV
Published
2020-01
Volume
31
Issue
1
Pages
387-392
ISSN
0921-8831 (ISSN-L)
OpenAlex
W2991037649
Cited by
31
References
57
Citations by year
2026: 4 · 2025: 7 · 2024: 2 · 2023: 6 · 2022: 7 · 2021: 3 · 2020: 2
FWCI
2.05
Type
journal article
Language
en
Open access
closed
Locations
Advanced Powder Technology (publishedVersion)
Funders
  • Japan Society for the Promotion of Science (18K06753)
  • Institute of Infection and Immunity
Topics
  • Physical Sciences › Engineering › Computational Mechanics › Granular flow and fluidized beds
  • Physical Sciences › Engineering › Automotive Engineering › Additive Manufacturing and 3D Printing Technologies
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Drug Solubulity and Delivery Systems
Keywords
particle technology, powder technology, personalized medicine, precision medicine, nanoparticles, drug delivery systems, continuous production, process intensification, on-demand manufacturing, 3D printing, additive manufacturing, artificial intelligence, powder characterization, drug formulation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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