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Integrating Artificial Intelligence and Nanotechnology for Precision Cancer Medicine
Open accessAbstract
Artificial intelligence (AI) and nanotechnology are two fields that are instrumental in realizing the goal of precision medicine—tailoring the best treatment for each cancer patient. Recent conversion between these two fields is enabling better patient data acquisition and improved design of nanomaterials for precision cancer medicine. Diagnostic nanomaterials are used to assemble a patient‐specific disease profile, which is then leveraged, through a set of therapeutic nanotechnologies, to improve the treatment outcome. However, high intratumor and interpatient heterogeneities make the rational design of diagnostic and therapeutic platforms, and analysis of their output, extremely difficult. Integration of AI approaches can bridge this gap, using pattern analysis and classification algorithms for improved diagnostic and therapeutic accuracy. Nanomedicine design also benefits from the application of AI, by optimizing material properties according to predicted interactions with the target drug, biological fluids, immune system, vasculature, and cell membranes, all affecting therapeutic efficacy. Here, fundamental concepts in AI are described and the contributions and promise of nanotechnology coupled with AI to the future of precision cancer medicine are reviewed.
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“AI can optimize multiple aspects of nanoparticle design, including nanoparticles’ size and charge, drug encapsulation efficiency, interactions with biological membranes, vasculature, biological fluids, and drug release kinetics through machine-learning algorithms and computational models.342”
From Smart nanoparticles for cancer therapy (2023) · cites this paper as [342]
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Metadata
- Authors
- Adir, O., Poley, M., Chen, G., Froim, S., Krinsky, N., Shklover, J., Shainsky‐Roitman, J., Lammers, T., & Schroeder, A.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- Tel Aviv University (IL)
- Universitätsklinikum Aachen (DE)
- Corresponding author
- Schroeder, Avi
- Venue
- Advanced Materials
- Publisher
- Wiley
- Published
- 2019-07-09
- Volume
- 32
- Issue
- 13
- Pages
- e1901989-e1901989
- ISSN
- 0935-9648 (ISSN-L)
- 1521-4095
- PMC
- PMC7124889
- OpenAlex
- W2957366757
- Cited by
- 496
- References
- 179
- Citations by year
- 2026: 69 · 2025: 113 · 2024: 111 · 2023: 70 · 2022: 54 · 2021: 49 · 2020: 29 · 2019: 1
- FWCI
- 2.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Advanced Materials (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RWTH Publications (RWTH Aachen) (submittedVersion)
- Funders
- European Research Council (STG‐2015‐680242)
- Russell Berrie Nanotechnology Institute, Technion-Israel Institute of Technology
- Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion-Israel Institute of Technology
- Ministry of Economy (52752)
- Ministry of Science and Technology, Israel (3‐11878)
- Israel Science Foundation (1778/13, 1421/17)
- Israel Cancer Association (2015‐0116)
- German-Israeli Foundation for Scientific Research and Development (I‐2328‐1139.10/2012)
- FP7 Science in Society (908049)
- Phospholipid Research Center
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Nanoplatforms for cancer theranostics
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Physical Sciences › Materials Science › General Materials Science › Nanotechnology research and applications
- Keywords
- artificial intelligence, nanotechnology, precision oncology, nanomedicine, intratumoral heterogeneity, interpatient heterogeneity, machine learning classification
- MeSH terms
- Animals, Artificial Intelligence, Humans, Neoplasms, Drug Delivery Systems, Computational Biology, Nanotechnology, Nanostructures, Nanomedicine, Precision Medicine
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