Combining cutting edge computational and experimental methods for targeting kras mutations in non-small cell lung cancer

Recent studies support the view that integration of AI algorithms with experimental methods is a key aspect in stream-lining the drug discovery process and identifying molecules with greater structural diversity, less off target effects than traditional screening methods. Furthermore, the authors believe that AI will eventually become standardized in drug discovery and existing pipelines specific to KRAS mutant inhibitor design will be expanded for additional KRAS mutations as well as other aggressive driver oncogenes across multiple cancers.