ItemArticle

Artificial Intelligence Driven Drug Delivery Systems: Recent Advances and Emerging Trends

Title
Artificial Intelligence Driven Drug Delivery Systems: Recent Advances and Emerging Trends
Creator
Sudha, Y.; Radhika, K.R.; Chethana, C.; Anoop, G.L.; Varma, Gadhiraju Tej; Bisalapur, Sahana
Description
Drug Delivery Systems (DDS) play a critical role in ensuring the therapeutic efficacy and safety of pharmaceutical agents. Conventional drug delivery approaches often suffer from limitations such as poor bioavailability, non-specific targeting, and systemic toxicity. Recent advancements in Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) have revolutionized the design and optimization of drug delivery platforms. AI-driven methods enable predictive modeling, intelligent nanocarrier design, and personalized therapeutic strategies by analyzing large biomedical datasets. These technologies facilitate optimized drug formulation, controlled release mechanisms, and targeted delivery, thereby improving treatment outcomes. AI algorithms such as Support Vector Machines (SVM), random forests, Convolutional Neural Networks (CNN), and reinforcement learning are increasingly applied in nanoparticle design, pharmacokinetic modeling, and clinical decision support systems. Additionally, emerging concepts such as self-driving laboratories, autonomous drug delivery systems, and AI-guided nanomedicine are reshaping pharmaceutical research. This review provides a comprehensive analysis of recent advances in AI-driven drug delivery systems, covering computational techniques, nanocarrier optimization, clinical applications, and emerging research trends. Comparative analysis tables summarize key algorithms, delivery platforms, and research developments reported in the literature. Finally, major challenges including data quality, regulatory issues, and interpretability of AI models are discussed along with future directions for the integration of AI in precision medicine and smart therapeutics. 2026, Dr. Yashwant Research Labs Pvt. Ltd. All rights reserved.
Source
International Journal of Drug Delivery Technology;Volume;16;Issue;9;pp.826-834
Date
01-01-2026
Publisher
Dr. Yashwant Research Labs Pvt. Ltd.
Subject
Artificial Intelligence; Drug Delivery Systems; Machine Learning; Nanomedicine; Precision Medicine; Smart Therapeutics
Coverage
Sudha Y., Department of Computer Science and Business Systems, Nitte Meenakshi Institute of Technology (NMIT), Nitte(Deemed to be University), Bengaluru, India; Radhika K.R., Department of CSE, BMSIT&M, Karnataka, Bengaluru, India; Chethana C., Department of CSE, BMSIT&M, Karnataka, Bengaluru, India; Anoop G.L., Department of CSE, Christ University, Karnataka, Bengaluru, India; Varma G.T., Department of IT, SRKR Engineering College, Andhra Pradesh, Bhimavaram, India; Bisalapur S., Department of CSE, Department of Computer Science and Engineering, S. G. Balekundri Institute of Technology, Affiliated to VTU, Belagavi, India
Rights
All Open Access; Bronze Open Access
Relation
ISSN: 9754415;
Format
online
Language
English
Type
Article

Citation

Sudha, Y.; Radhika, K.R.; Chethana, C.; Anoop, G.L.; Varma, Gadhiraju Tej; Bisalapur, Sahana, “Artificial Intelligence Driven Drug Delivery Systems: Recent Advances and Emerging Trends,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/23428.

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