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Peer-reviewedLicence not statedJournal of Pharmaceutical Innovation

Integrating DLVO Theory with Machine Learning for Predictive Toxicology and Multi-Objective Design of Quercetin-Loaded Nanocarriers

  • Sonia Fathi‐karkan1,2,3
  • Abbas Rahdar4
4 affiliations
  1. 1Department of Advanced Sciences and Technologies in Medicine, School of Medicine, North Khorasan University of Medical Sciences, Bojnurd, Iran
  2. 2Food and Drug Research Center, Food and Drug Administration, Ministry of Health and Medical Education, Tehran, Iran
  3. 3Natural Products and Medicinal Plants Research Center, North Khorasan University of Medical Sciences, Bojnurd, Iran
  4. 4Department of Physics, University of Zabol, Zabol, Iran
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Cite

BibTeXRIS
BibTeX
@article{fathikarkan2026integrating,
  title = {{Integrating DLVO Theory with Machine Learning for Predictive Toxicology and Multi-Objective Design of Quercetin-Loaded Nanocarriers}},
  author = {Sonia Fathi‐karkan and Abbas Rahdar},
  journal = {Journal of Pharmaceutical Innovation},
  year = {2026},
  month = jun,
  doi = {10.1007/s12247-026-10852-z},
  url = {https://doi.org/10.21203/rs.3.rs-8067561/v1},
}
RIS
TY  - JOUR
TI  - Integrating DLVO Theory with Machine Learning for Predictive Toxicology and Multi-Objective Design of Quercetin-Loaded Nanocarriers
AU  - Sonia Fathi‐karkan
AU  - Abbas Rahdar
PY  - 2026
DA  - 2026/06/13
JO  - Journal of Pharmaceutical Innovation
DO  - 10.1007/s12247-026-10852-z
UR  - https://doi.org/10.21203/rs.3.rs-8067561/v1
SN  - 1872-5120
SN  - 1939-8042
ER  -