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International Journal of Nanomedicine Volume 17, 2023 - Issue
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Original Research

Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches

Zhoumeng Lin1 Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA;2 Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL, USA;3 Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA;4 Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USACorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0002-8731-8366
ORCID Icon,
Wei-Chun Chou1 Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA;2 Center for Environmental and Human Toxicology, University of Florida, Gainesville, FL, USA;3 Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA;4 Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USAORCID Iconhttps://orcid.org/0000-0003-3355-6921
ORCID Icon,
Yi-Hsien Cheng3 Institute of Computational Comparative Medicine, Kansas State University, Manhattan, KS, USA;4 Department of Anatomy and Physiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
,
Chunla He5 Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USAORCID Iconhttps://orcid.org/0000-0002-8339-0096
ORCID Icon,
Nancy A Monteiro-Riviere6 Nanotechnology Innovation Center of Kansas State, Kansas State University, Manhattan, KS, USA;7 Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, Raleigh, NC, USAORCID Iconhttps://orcid.org/0000-0002-0132-0861
ORCID Icon &
Jim E Riviere7 Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, Raleigh, NC, USA;8 1Data Consortium, Kansas State University, Olathe, KS, USA
Pages 1365-1379 | Published online: 24 Mar 2022

Citations (14)

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Read on this site (1)

Jonathan Zaslavsky, Pauric Bannigan & Christine Allen. (2023) Re-envisioning the design of nanomedicines: harnessing automation and artificial intelligence. Expert Opinion on Drug Delivery 20:2, pages 241-257.
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Articles from other publishers (13)

Long Yuan, Qiran Chen, Jim E. Riviere & Zhoumeng Lin. (2023) Pharmacokinetics and tumor delivery of nanoparticles. Journal of Drug Delivery Science and Technology 83, pages 104404.
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Anita Bakrania, Narottam Joshi, Xun Zhao, Gang Zheng & Mamatha Bhat. (2023) Artificial intelligence in liver cancers: Decoding the impact of machine learning models in clinical diagnosis of primary liver cancers and liver cancer metastases. Pharmacological Research 189, pages 106706.
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Atchara Chinnakorn, Wiwat Nuansing, Mahdi Bodaghi, Bernard Rolfe & Ali Zolfagharian. (2023) Recent progress of 4D printing in cancer therapeutics studies. SLAS Technology.
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Wei-Chun Chou & Zhoumeng Lin. (2023) Machine learning and artificial intelligence in physiologically based pharmacokinetic modeling. Toxicological Sciences 191:1, pages 1-14.
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Warren C. W. Chan. (2023) Principles of Nanoparticle Delivery to Solid Tumors. BME Frontiers 4.
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Zhoumeng Lin, Santosh Aryal, Yi-Hsien Cheng & Andre J. Gesquiere. (2022) Integration of In Vitro and In Vivo Models to Predict Cellular and Tissue Dosimetry of Nanomaterials Using Physiologically Based Pharmacokinetic Modeling. ACS Nano 16:12, pages 19722-19754.
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Wei-Chun Chou, Yi-Hsien Cheng, Jim E. Riviere, Nancy A. Monteiro-Riviere, Wolfgang G. Kreyling & Zhoumeng Lin. (2022) Development of a multi-route physiologically based pharmacokinetic (PBPK) model for nanomaterials: a comparison between a traditional versus a new route-specific approach using gold nanoparticles in rats. Particle and Fibre Toxicology 19:1.
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Qiran Chen, Jim E. Riviere & Zhoumeng Lin. (2022) Toxicokinetics, dose–response, and risk assessment of nanomaterials: Methodology, challenges, and future perspectives. WIREs Nanomedicine and Nanobiotechnology 14:6.
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Elena O. Kutumova, Ilya R. Akberdin, Ilya N. Kiselev, Ruslan N. Sharipov, Vera S. Egorova, Anastasiia O. Syrocheva, Alessandro Parodi, Andrey A. ZamyatninJr.Jr. & Fedor A. Kolpakov. (2022) Physiologically Based Pharmacokinetic Modeling of Nanoparticle Biodistribution: A Review of Existing Models, Simulation Software, and Data Analysis Tools. International Journal of Molecular Sciences 23:20, pages 12560.
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Ying Chen, Jiawen He & Meihua Wang. (2022) A hybrid of long short-term memory neural network and autoregressive integrated moving average model in forecasting HIV incidence and morality of post-neonatal population in East Asia: global burden of diseases 2000–2019. BMC Public Health 22:1.
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Tingting Yang, Jingming Zhai, Dong Hu, Ruyue Yang, Guidan Wang, Yuanpei Li & Gaofeng Liang. (2022) “Targeting Design” of Nanoparticles in Tumor Therapy. Pharmaceutics 14:9, pages 1919.
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Zhoumeng Lin & Wei-Chun Chou. (2022) Machine Learning and Artificial Intelligence in Toxicological Sciences. Toxicological Sciences 189:1, pages 7-19.
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Jiunn-Diann Lin, Dee Pei, Fang-Yu Chen, Chung-Ze Wu, Chieh-Hua Lu, Li-Ying Huang, Chun-Heng Kuo, Shi-Wen Kuo & Yen-Lin Chen. (2022) Comparison between Machine Learning and Multiple Linear Regression to Identify Abnormal Thallium Myocardial Perfusion Scan in Chinese Type 2 Diabetes. Diagnostics 12:7, pages 1619.
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