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Machine Learning-Driven Rational Design in Nanomedicine: Advances in Computational Drug Delivery and in Silico Screening
Paperback
Series: Springerbriefs in Bioengineering
Technology & EngineeringBiology
ISBN13: 9783032040114
Publisher: Springer
Published: Jan 31 2026
Pages: 73
Weight: 0.30
Height: 0.18 Width: 6.14 Depth: 9.21
Language: English
This book explores how machine learning is transforming nanomedicine, with a focus on the rational design of lipid nanoparticles (LNPs) for mRNA-based therapies. Moving beyond traditional, labor-intensive workflows, it highlights AI-driven methods--such as supervised learning, data augmentation, and deep learning--for predictive modeling and in silico screening.
Key topics include chemoinformatics, molecular fingerprinting, and strategies to optimize LNP transfection efficiency and biocompatibility. Real-world applications, including mRNA vaccines and personalized nanomedicines, illustrate the convergence of computational biology and pharmaceutical engineering. It also addresses the ethical considerations and regulatory challenges surrounding AI-driven drug development. This book is intended for researchers, pharmaceutical scientists, computational biologists, and professionals in the biotechnology industry who seek to leverage AI-driven methodologies in nanomedicine development.
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