Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
@article{204654,
author = {Shaikh Mahek and Dr. Aamer Quazi and Mr. Hussain Faizan H. and Shaikh Simran and Dhaware Nandini},
title = {Role of Artificial Intelligence in Novel Drug Delivery System},
journal = {International Journal of Innovative Research in Technology},
year = {2026},
volume = {13},
number = {1},
pages = {3569-3578},
issn = {2349-6002},
url = {https://ijirt.org/article?manuscript=204654},
abstract = {Artificial intelligence (AI) has emerged as a transformative force in pharmaceutical science, fundamentally altering the methods of drug discovery, formulation, and delivery to patients. The integration of AI with novel drug delivery systems (NDDS) signifies a groundbreaking advancement in contemporary medicine, presenting unparalleled prospects for addressing enduring obstacles in pharmacotherapy, including inadequate bioavailability, nonspecific toxicity, and patient noncompliance. This comprehensive review provides an in-depth examination of AI fundamentals, including machine learning, deep learning, and neural network architectures, followed by a systematic analysis of AI applications across the pharmaceutical industry. Special emphasis is placed on the transformative role of AI in the design, optimization, and clinical translation of novel drug delivery systems, including nanoparticle-based carriers, liposomes, polymeric micelles, hydrogels, transdermal systems, and stimuli-responsive platforms. This review also addresses the integration of AI with bioinformatics and systems biology for personalized medicine, discusses the regulatory landscape for AI-driven pharmaceutical products, and identifies key challenges and future directions. Evidence from over 200 published studies demonstrates that AI-powered approaches consistently reduce formulation development timelines by 40-60%, improve targeting efficiency, and enable real-time quality monitoring. We conclude that AI is not merely a computational tool but a paradigm-shifting technology that will define the future of drug delivery.},
keywords = {Artificial Intelligence, Machine Learning, Deep Learning, Novel Drug Delivery Systems, Drug Design, Pharmaceutical Technology},
month = {June},
}
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