Artificial intelligence and machine learning assisted drug delivery for effective treatment of infectious diseases
Abstract
In the era of antimicrobial resistance, the prevalence of multidrug-resistant microorganisms that resist conventional antibiotic treatment has steadily increased. Thus, it is now unquestionable that infectious diseases are significant global burdens that urgently require innovative treatment strategies. Emerging studies have demonstrated that artificial intelligence (AI) can transform drug delivery to promote effective treatment of infectious diseases. In this review, we propose to evaluate the significance, essential principles, and popular tools of AI in drug delivery for infectious disease treatment. Specifically, we will focus on the achievements and key findings of current research, as well as the applications of AI on drug delivery throughout the whole antimicrobial treatment process, with an emphasis on drug development, treatment regimen optimization, drug delivery system and administration route design, and drug delivery outcome prediction. To that end, the challenges of AI in drug delivery for infectious disease treatments and their current solutions and future perspective will be presented and discussed.
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Ensemble algorithm, decision trees and random forest, instance based algorithms and artificial neural network are used to enhance drug delivery of infectious diseases.
“Ensemble algorithm, decision trees and random forest, instance based algorithms and artificial neural network are used to enhance drug delivery of infectious diseases.”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [13]
Machine learning models are used in drug delivery for infectious disease treatment.
“Machine learning models used in drug delivery for infectious disease treatment is shown in the Fig. 1 [13] .”
From Artificial intelligence, machine learning and deep learning in advanced robotics, a review (2023) · cites this paper as [13]
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Artificial intelligence, machine learning and deep learning in advanced robotics, a review
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- Authors
- He, S., Leanse, L. G., & Feng, Y.
- Affiliations
- Boston Children's Hospital (US)
- Harvard University (US)
- Corresponding author
- Feng, Yanfang
- Venue
- Advanced Drug Delivery Reviews
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 178
- Pages
- 113922
- ISSN
- 0169-409X (ISSN-L)
- OpenAlex
- W3198122771
- Cited by
- 141
- References
- 18
- Citations by year
- 2026: 22 · 2025: 42 · 2024: 44 · 2023: 20 · 2022: 12 · 2021: 1
- FWCI
- 1.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Advanced Drug Delivery Reviews (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Physical Sciences › Materials Science › Biomaterials › Nanoparticle-Based Drug Delivery
- Keywords
- artificial intelligence, machine learning, drug delivery, infectious diseases, antimicrobial resistance, multidrug-resistant bacteria, drug development, treatment regimen optimization, drug delivery systems
- MeSH terms
- Anti-Infective Agents, Artificial Intelligence, Communicable Diseases, Humans, Drug Delivery Systems
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