The next generation of synthetic biology applications will increasingly involve engineered organisms that exist in intimate contact with humans, animals and the rest of the environment. Examples include cellular and viral approaches for maintaining and improving health in humans and animals. The need for reliable and specific function in these environments may require more complex system designs than previously. In these cases the uncertainties in the behavior of biological building blocks, their hosts and their environments present a challenge for design of predictable and safe systems. Here, we review systematic methods for the effective characterization of these uncertainties that are lowering the barriers to predictive design of reliable complex biological systems.
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