Recent Advances in Drug Delivery Using AI and Machine Learning
A special issue of Pharmaceutics (ISSN 1999-4923). This special issue belongs to the section "Drug Delivery and Controlled Release".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 9
Special Issue Editors
Interests: injectables; polymeric nanotechnology; polymeric micelles; polymeric complexes; polymeric bioconjugates; PEGylation
Interests: inhalation delivery; formulation engineering; transdermal delivery; device engineering
Interests: drug encapsulation and delivery; organic synthesis; nano formulations
Special Issue Information
Dear Colleagues,
The evolving landscape of drug delivery has seen significant advancements with the emergence of nanoparticle-based systems, offering improved solubility, stability, and targeted therapeutic action. However, traditional development approaches often face challenges, such as inefficient drug loading, unpredictable release kinetics, and off-target effects. Integrating artificial intelligence (AI) and machine learning (ML) into nanoparticle-based drug delivery has the potential to overcome these limitations by enabling precise formulation design, optimizing nanoparticle properties, and personalizing drug release strategies.
AI/ML-driven methodologies facilitate data-driven decision-making, accelerate the discovery of novel nanoparticle formulations, and enhance real-time monitoring of drug delivery performance. These tools have been successfully applied to various nanoparticle platforms, including lipid-based nanoparticles, polymeric carriers, inorganic nanoparticles, and hybrid systems, offering new avenues for controlled and efficient drug delivery.
In this Special Issue, we invite researchers to submit original research articles, reviews, and short communications focusing on AI- and ML-integrated nanoparticle-based drug delivery systems. Contributions exploring predictive modeling of nanoparticle interactions, optimization of carrier design, AI-guided formulation strategies, and novel applications of computational tools in nanomedicine are particularly welcome.
Prof. Dr. Glen S. Kwon
Prof. Dr. Hugh D. C. Smyth
Dr. Chinmay Potnis
Dr. Rebeca T. Stiepel
Guest Editors
Manuscript Submission Information
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Keywords
- nanoparticle drug delivery
- artificial intelligence (AI)
- machine learning (ML)
- predictive modelling
- targeted drug delivery
- nanomedicine
- excipient optimization
- personalized drug formulations
- computational drug design
- AI-driven drug development
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