#63. The Era of NAMs

This podcast explores the transformative shift toward New Approach Methodologies (NAMs), which utilize human-relevant experimental and computational systems to modernize drug discovery and biomedical research. Major federal initiatives from the NIH and FDA are establishing a robust infrastructure for these technologies, moving them from peripheral alternatives to central organizing principles in regulatory science. The sources highlight how AI-driven integration of in vitro assays, such as organoids and tissue chips, with in silico modeling can significantly enhance the accuracy of safety and efficacy predictions. A featured case study on liver injury demonstrates that combining deep learning with human cell data provides more reliable results than traditional animal testing. Ultimately, the transition focuses on creating evidence-based ecosystems in which the choice of model is determined by its scientific fitness for a specific context of use. Growing policy alignment and FAIR data standards are currently paving the way for a faster, more ethical, and clinically predictive translational corridor. Produced by Dr. Jake Chen.