A panel of representative DNA, RNA, and DNA/RNA NANPs was designed with varying descriptors such as molecular weight, melting temperature, size, and stability. A training set composed of 80% of this batch was used for machine learning, where descriptors were matched against outcomes of experimentally found immunostimulations. A validation set was then used to confirm the predicted trends and validate the model. Created with Biorender.com