Biomedical engineers at Duke University developed an integrated AI-driven platform combining automated wet lab processes with artificial intelligence to rapidly design nanoparticles optimized for targeted drug delivery. This approach addresses significant formulation challenges by enabling high-throughput screening and optimization, aiming to enhance therapeutic efficacy and accelerate drug development timelines. The platform exemplifies the convergence of machine learning and laboratory automation to overcome complex pharmaceutical formulation hurdles.