Lin Z, Chou WC, Cheng YH, He C, Monteiro-Riviere NA, Riviere JE. Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches. Int J Nanomedicine. 2022;17:1365–1379.
This study addresses the challenge of low nanoparticle (NP) delivery efficiency to tumors in cancer nanomedicine. Using data from the Nano-Tumor Database, machine learning and artificial intelligence methods, including a deep neural network, were applied to predict NP delivery efficiency based on physicochemical properties, tumor models, and cancer types. The deep neural network model outperformed other methods and identified cancer type, Zeta potential, and core material as key factors influencing delivery efficiency. The findings offer a quantitative model to optimize NP design for improved tumor delivery.
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