This chapter is devoted to the development of methods and principles for detecting the consequences of interactions between elements in integrated circuits, which will allow for proposing options for mitigating these consequences by making changes to the synchronization signal tree and information-carrying wires accordingly. Methods for detecting and mitigating interactions between elements have been proposed, which ensure time savings during detection and mitigate the consequences of interactions and overall timing parameters with minimal deterioration of their characteristic parameters and with minimal increase in area and power consumption. A method based on machine learning algorithms has been developed for predicting interactions between elements in integrated circuits. This method ensures approximately 36,6% time savings on signal integrity analysis with minimal data collection and circuit analysis, at the cost of around 10% loss in the predicted data. A method for modifying the corresponding wires, considering the architecture of the synchronization signal tree and the design features of the circuit, has been proposed. This method, through optimized combinations of shielding and blocking and relocating the wires of the synchronization signal tree, provides approximately 17,9% mitigation of interaction effects, 16,9% and 19,1% reduction in the overall setup and hold times of sequential elements, with a loss of about 5,66% in power consumption and 3,1% in area.