Valipour, A.; Bourque, A. R.; Housley, S. N.

Microvasculature networks mediate nutrient delivery, waste removal, and drug distribution, yet current microfluidic devices fail to capture biological complexity. Here, we introduce an integrative framework to automate generation of bio-informed microvasculature models unifying in silico and in vitro applications. Our approach leverages a new stochastic growth algorithm governed by fundamental angiogenic principles to generate closed-circuit, fabrication-ready architectures with physiological relevance. We introduce an inverse design strategy that provides a principled mechanism to assign vessel characteristics that satisfy physiological scaling laws. We then present electrical network dynamics, a new algorithm that characterizes network behaviors 100-10,000X faster than CFD, while preserving quantitative predictions. We demonstrate models are fully interchangeable between experimental domains through systematic investigation of vascular topology influence of flow, transport, and cellular behavior. Our platform closes a long-standing gap and provides a generalizable foundation for studying microvascular function in health and disease.