Integrating Artificial Intelligence and Nanotechnology for Precision Cancer Medicine
© 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
| Publié dans: | Advanced materials (Deerfield Beach, Fla.). - 1998. - 32(2020), 13 vom: 30. Apr., Seite e1901989 |
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| Auteur principal: | |
| Autres auteurs: | , , , , , , , |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2020
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| Accès à la collection: | Advanced materials (Deerfield Beach, Fla.) |
| Sujets: | Journal Article Review artificial intelligence big data cancer nanotechnology precision medicine |
| Résumé: | © 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. 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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| Description: | Date Completed 30.12.2020 Date Revised 13.11.2023 published: Print-Electronic Citation Status MEDLINE |
| ISSN: | 1521-4095 |
| DOI: | 10.1002/adma.201901989 |