دورية أكاديمية
The role of artificial intelligence and data science in nanoparticles development: a review.
| العنوان: | The role of artificial intelligence and data science in nanoparticles development: a review. |
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| المؤلفون: | Silveira RF; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil., Lima AL; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil., Gross IP; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil., Gelfuso GM; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil., Gratieri T; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil., Cunha-Filho M; Laboratory of Food, Drugs, & Cosmetics (LTMAC), University of Brasilia, 70910-900, Brasília, DF, Brazil. |
| المصدر: | Nanomedicine (London, England) [Nanomedicine (Lond)] 2024; Vol. 19 (14), pp. 1271-1283. Date of Electronic Publication: 2024 Jun 21. |
| نوع المنشور: | Journal Article; Review; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Future Medicine Ltd Country of Publication: England NLM ID: 101278111 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1748-6963 (Electronic) Linking ISSN: 17435889 NLM ISO Abbreviation: Nanomedicine (Lond) Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: London, UK : Future Medicine Ltd., c2006- |
| مواضيع طبية MeSH: | Nanoparticles*/chemistry , Artificial Intelligence* , Machine Learning* , Data Science*/methods, Humans ; Nanotechnology/methods ; Polymers/chemistry |
| مستخلص: | Artificial intelligence has revolutionized many sectors with unparalleled predictive capabilities supported by machine learning (ML). So far, this tool has not been able to provide the same level of development in pharmaceutical nanotechnology. This review discusses the current data science methodologies related to polymeric drug-loaded nanoparticle production from an innovative multidisciplinary perspective while considering the strictest data science practices. Several methodological and data interpretation flaws were identified by analyzing the few qualified ML studies. Most issues lie in following appropriate analysis steps, such as cross-validation, balancing data, or testing alternative models. Thus, better-planned studies following the recommended data science analysis steps along with adequate numbers of experiments would change the current landscape, allowing the exploration of the full potential of ML. |
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| معلومات مُعتمدة: | 00193-00000735/2021-10 Fundação de Apoio à Pesquisa do Distrito Federal |
| فهرسة مساهمة: | Keywords: artificial neural network; data mining; data science; machine learning; polymeric nanoparticle; quality by design Local Abstract: [plain-language-summary] [Box: see text]. |
| المشرفين على المادة: | 0 (Polymers) |
| تواريخ الأحداث: | Date Created: 20240621 Date Completed: 20240724 Latest Revision: 20240802 |
| رمز التحديث: | 20240803 |
| مُعرف محوري في PubMed: | PMC11285233 |
| DOI: | 10.1080/17435889.2024.2359355 |
| PMID: | 38905147 |
| قاعدة البيانات: | MEDLINE |
PDF full text from Publisher | تدمد: | 1748-6963 |
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| DOI: | 10.1080/17435889.2024.2359355 |