Predictive Nanotoxicology
Bilal Khan, Yoram Cohen · 2022
Engineered nanomaterials have found use in a variety of industrial applications such as cosmetics, therapeutics, electronics, manufacturing, and healthcare. The compositions of nanomaterials vary according to the products and brands, thus the drive to categorize them into a suitable new class of materials. The application of Machine Learning (ML) algorithms in nanotoxicology has gained momentum over the past two decades due to two major reasons. ML has been proven useful for identifying nanomaterial properties and exposure conditions that affect cellular and organism toxicity, thereby providing information needed for risk analysis and for safe-by-design approaches for the development of new nanomaterials. Nanoinformatics platforms can serve to facilitate multidisciplinary collaboration among researchers in both institutions of higher learning and industry, thereby accelerating the development of computational tools and construction of rich databases to serve the broad nanotechnology community.