Comprehensive overview of AI methodologies in nano-drug delivery Optimization and Design

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Authors: Lei Zhang, Jun Li, Li Mu, Lanlan Guo, Jing Zhang, Ling Liu, Zhenglun Yu
Cited by: 1
References: 168

Abstract

This review comprehensively examines the application of artificial intelligence (AI) to revolutionize precision oncology across all phases of drug development, including target discovery and molecular design, nanomedicine delivery, and resistance mitigation. Deep learning, systems biology, and multi-omics analytics enabled by AI accelerate target discovery, lead optimization, and personalized therapy. This study focuses on a new area of AI-driven nanocarrier design, adaptive therapy design, and digital twin clinical decision support. AI bridges the knowledge gap between molecular information and real-world data to enable forecasting, transparent, patient-centered cancer treatment, and the foundation for a data platform to counsel future generations of cancer patients, therapies, and resistance control.

Fields of Study & Subjects

Computational Drug Discovery Methods Artificial Intelligence in Healthcare and Education Mathematical Biology Tumor Growth

Publication details

Journal / source
npj Precision Oncology
Publisher
Springer Science and Business Media LLC
Volume
10
Issue
1
Publication date
20 August 2026
Language
EN