The von Neumann architecture was first expressed in 1945 and has largely dominated in many variants and refinements computer science for more than half a century. Alternative architectures always occupied a marginal place only, despite a growing need for new concepts and paradigms in computer science. Biologically-inspired engineering applies biological concepts to the design of novel computing machines and algorithms. This can lead to the creation of new machines, endowed with properties usually associated with the living world: adaptation, evolution, growth and development, fault-tolerance, self-replication or cloning, reproduction, etc. Most of these approaches are based on well established theories such as artificial neural networks, evolutionary algorithms, and cellular automata. The work presented in this thesis takes an alternative path and proposes concepts for novel and unconventional biologically-inspired machines. The approach is mainly motivated by the insight that tomorrow's computational substrates and environments might be very different from what we know today. Some of tomorrow's computers might be embedded in the paint that covers your desk or printed on a sheet of paper by means of a special ink. Most of such pervasive computing concepts have some common elements: (1) the computer's basic elements are very simple, identical, and available in a huge number, (2) the interactions between the elements are purely local, (3) the elements as well as the interconnections are unreliable, and (4) there is no global control mechanism available. This thesis is mainly based on the unification of the following three domains of research: (1) amorphous computing, (2) membrane systems, and (3) blending. An amorphous computer is a massive parallel machine made up of myriads of simple, unreliable, and identical elements, distributed randomly on a surface and interconnected locally by unreliable connections. Membrane systems are theoretical models inspired by biochemistry-based on regions bounded by membranes. The hierarchical membrane structures contain artificial chemistries, consisting in objects and reactions, which allow to do computations. Blending is a framework of cognitive science which tries to explain how we deal with mental concepts and how creative thinking emerges. First, an introduction of traditional bio-inspired machines and hardware is provided. This part also includes the presentation of a first implementation of a membrane system on reconfigurable hardware and a description of the cellular automata machine entitled BioWall, with its applications. Random boolean networks as well as several theoretical considerations and practical results are then used to introduce irregular computational structures. The C-Blending approach represents an novel computational blending method intended for membrane systems and artificial chemistries. In order to implement membrane systems on amorphous computers, the Circuit Amorphous Computer as well as special membrane systems, termed aP and aB membrane systems, are proposed. The ultimate concept proposed and studied consists in a unification of membrane systems, amorphous computers, and computational C-Blending. The unification of the three concepts results in several interesting properties. The cellular structures allow to create dynamical hierarchies and growing systems whereas the artificial chemistries represent an ideal mean to compute on the potentially imperfect and irregular hardware of an amorphous computer. Finally, the computational blending proposed describes an inventive method to create, organize, and adapt membrane systems. The characteristics and limits of the concepts proposed are analyzed and validated using various examples and toy applications. The thesis concludes with the definition of the Circuit Amorphous Computer and the Amorphon architecture, which might constitute the minimal element of tomorrow's computing machines.