Therapeutic translation requires models of disease that have intervenable phenotypes relatable to clinical response. This has classically been rooted in cell and small animal models that have historically had poor predictive performance. There is thus a need for additional models with improved fidelity and the ability to capture the nuances of human disease and the genetic complexities that alter drug response. Tissue engineering has rapidly developed for this very reason, evolving from the confluence of separate advancing technologies in stem cell differentiation, biomaterial design and bioreactor development. Importantly, parallel understanding of both genetic and non-genetic underpinnings of human disease has formulated an array of benchmarks and phenotypes by which we can measure the fidelity of engineered human tissue. Though tissue engineering is rapidly progressing, it remains limited by scaffold and bioreactor designs that are based on predetermined parameters and the lack of real-time, nondestructive measurements of cell and tissue function. In this issue, we will focus on how investigators are tackling the limitations in both input and output of bioreactor design. Specifically, we will focus on (i) advances in biomaterials with adaptive control that can sense, and actuate cells for real time spatiotemporal control of engineered tissues and (ii) bioreactors with optical control, sensing, and feedback with precise spatiotemporal visualization, actuation, and confirmation of disease phenotypes.