Emerging Opportunities for Automated Intelligent Development and Optimization of Radiolabeling Reactions

Radiopharmaceuticals form the molecular basis of nuclear imaging and radionuclide therapy. As clinical demand continues to grow, systematic optimization of radiolabeling reactions is increasingly important for efficient and reliable radiopharmaceutical production. This perspective first summarizes key radiochemical performance metrics for radiolabeling optimization. Representative radiolabeling strategies involving nonmetal and metallic radionuclides are then discussed, together with their associated reaction variables and practical constraints. Building on this foundation, production-oriented commercial automated synthesis platforms are discussed to illustrate the device-level parameter optimization space, while rapid experimentation platforms are introduced as complementary tools for acquiring optimization data. Finally, inspired by recent advances in intelligent algorithms for chemical synthesis, this perspective discusses Bayesian optimization-centered strategies as decision-support tools for radiolabeling reaction optimization under expert guidance.