Methods and systems for cross-domain controlled stimulation of biological dynamics by AI iterative optimization physical patterns for migrating structured patterns (including crystals, semiconductors, and related processes) from physical or mineral systems to target biological systems to guide their measurable dynamic processes, such as growth, migration, proliferation, branching, and self-organization. The present application generates a defect and
anisotropy mapping or descriptor
delta (x) from a physical source and converts a derived stimulation pattern or stimulation
recipe under constrained conditions into an
executable stimulation protocol, which may include electrical stimulation or electro-
physical stimulation,
light stimulation, chemical stimulation,
thermal stimulation or mechanical stimulation, or may be in a multi-
modal form, meanwhile, the biological constraint and the
executable and safety constraint of the experimental device are met; applying the stimulation protocol to a target
biological system and obtaining
observation data through a sensor and / or visual means (photo, video, time-lapse photography) to extract quantitative features and calculate a result indicator that can be compared to a baseline; subsequent tests are selected under constraint conditions by an
artificial intelligence assisted decision engine to maximize information utility and achieve improvements while using stop rules to limit low-yield experimental activities and maintain comparability and
repeatability between different runs.