Applying artificial intelligence and computational modeling to nanomedicine

• Published in: Current opinion in biotechnology Vol. 85; p. 103043
• Main Authors: Hamilton, Sean, Kingston, Benjamin R
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.02.2024
• Subjects: Artificial Intelligence; Computer Simulation; Drug Delivery Systems; Nanomedicine - methods; Nanoparticles
• ISSN: 0958-1669; 1879-0429
• DOI: 10.1016/j.copbio.2023.103043

Achieving specific and targeted delivery of nanomedicines to diseased tissues is a major challenge. This is because the process of designing, formulating, testing, and selecting a nanoparticle delivery vehicle for a specific disease target is governed by complex multivariate interactions. Computational modeling and artificial intelligence are well-suited for analyzing and modeling large multivariate datasets in short periods of time. Computational approaches can be applied to help design nanomedicine formulations, interpret nanoparticle–biological interactions, and create models from high-throughput screening techniques to improve the selection of the ideal nanoparticle carrier. In the future, many steps in the nanomedicine development process will be done computationally, reducing the number of experiments and time needed to select the ideal nanomedicine formulation. •Computational modeling can be used to design many types of nanomedicines•Analysis of nanoparticle-biological interactions helps inform predictive models•High-throughput screening platforms generate rich data for computational analysis