Storage stability of lipid nanoparticles: a curated benchmark dataset, systematic threshold analysis, and per-study machine learning prediction limits

Kodzo Prosper Adzavon, Weijian Zhao, Wang Sheng

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DOI: 10.1016/j.ijpharm.2026.127405
Published: 2026-09
Container: International Journal of Pharmaceutics
Publisher: Elsevier BV
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1016/j.ijpharm.2026.127405,
  title = {Storage stability of lipid nanoparticles: a curated benchmark dataset, systematic threshold analysis, and per-study machine learning prediction limits},
  author = {Kodzo Prosper Adzavon and Weijian Zhao and Wang Sheng},
  year = {2026},
  journal = {International Journal of Pharmaceutics},
  doi = {10.1016/j.ijpharm.2026.127405},
  url = {https://doi.org/10.1016/j.ijpharm.2026.127405}
}

RIS

TY  - JOUR
TI  - Storage stability of lipid nanoparticles: a curated benchmark dataset, systematic threshold analysis, and per-study machine learning prediction limits
AU  - Kodzo Prosper Adzavon
AU  - Weijian Zhao
AU  - Wang Sheng
PY  - 2026
JO  - International Journal of Pharmaceutics
DO  - 10.1016/j.ijpharm.2026.127405
UR  - https://doi.org/10.1016/j.ijpharm.2026.127405
ER  -

APA

Adzavon, K. P., Zhao, W., & Sheng, W. (2026). Storage stability of lipid nanoparticles: a curated benchmark dataset, systematic threshold analysis, and per-study machine learning prediction limits. International Journal of Pharmaceutics. https://doi.org/10.1016/j.ijpharm.2026.127405

Source records

crossref · retrieved 2026-09-26T13:22:27.737Z