The promise of next-generation computer technologies, such as nano-electronics, implies a number of serious alterations to the design flow of digital circuits. One of the most serious issues is related to circuit layout, as conventional lithographic techniques do not scale to the molecular level. A second important issue concerns fault tolerance: molecular-scale devices will be subject to fault densities that are orders of magnitude greater than silicon-based circuits. In our work, we are investigating a different approach to the design of complex computing systems, inspired by the developmental process of multi-cellular organisms in nature. This approach has led us to define a hierarchical system based on several levels of complexity, ranging from the molecule (modeled by an element of a programmable logic device when the system is applied to silicon) to the organism, defined as an application specific multi-processor system. By setting aside some of the conventional circuit design priorities, namely size and (to a certain extent) performance, we are able to design fully scalable systems endowed with some properties not commonly found in digital circuits. Most notably, by exploiting a hierarchical self-repair approach, our systems are able to tolerate higher fault densities, whereas a self-replication mechanism allows our arrays of processing elements to self organize, greatly reducing the layout complexity of the system.