In summary, the measurable objectives of the project were to:
- Establish the necessity of living systems (self reproducing evolvable structures) for effective nano-scale information processing. Here PACE has demonstrated that, at least for the large future area of nano-scale information processing that involves intelligent material synthesis, deployment and operation, a living technology approach is essential. Living systems efficiently and stably control their operation through local feedback processes at all scales and at the level of the smallest components. Homeostatic mechanisms have been demonstrated that operate at the level of artificial cells, and the requirements for evolvability worked out. The detailed aspects of living systems essential to this capability of information directed synthesis (and thence self-repair and self-reproduction) have been abstracted and have led to the concept of an artificial subcellular matrix, that has been clearly targeted in ongoing projects and applications.
- Establish a theoretical framework for computation in systems with genetically controlled catalytic reactions, self-assembly of complex molecular structures, and energy transduction, and within this framework describe measurable complexity, evolvability, and emergent hierarchy. Not one but several computational frameworks were established in PACE: ranging from Spintronic quantum computation, Morphological computation, Genetic self-assembly, Cell logic, through to Computational cell self-assembly. The issues of evolvability and complexity were studied in several of these frameworks, extending the general picture of embodiment to the microscopic physical domain: computation should make optimal use of physical processes that naturally address complex tasks, rather than recoding every process symbolically.
- Understand programmability via evolutionary learning in the space of chemical systems by characterizing the structure of the space and the structure of evolutionary paths through the space. A general graphical language was developed to describe the space of physico-chemical systems relevant to artificial cells. Work in the project revealed that the chemistry alone is not sufficient to characterize systems like artificial cells - in particular the interaction of chemical processes with physical self-organization is critical. Evolutionary learning was demonstrated for chemistry coupled phase systems, for models ranging from the simplest Ising fluid model to detailed mesoscale simulation of molecular amphiphile systems, despite the implicit problems of cooperation entailed. This work revealed that the structure of evolutionary paths through the space depends strongly on the physical spatial embedding, and it is not sufficient to characterize paths simply in terms of the chemical reactions involved. Programming via evolution of self-assembling systems was investigated with concrete physical models and for abstract problems.
- Establish an experimental platform (created with computer-controlled arrays of microflow reactors) for programming the functionality of artificial cells by means of evolutionary exploration of chemical-genetic metabolisms. The experimental platform that was created is that of the omega machine together with the evolution of experimental protocols. This platform, through its fine grained microscopic feedback structure, represents a major step forward beyond conventional lab-on-a-chip technology. Emphasis was placed on developing a universal programmable complementation machine capable of being programmed to direct chemical self-organization, processing and integration.
- Use this experimental platform to implement the first versions of evolutionary programmable chemistry. Work in PACE on evolutionary optimization with this experimental platform concentrated largely on the optimization of experimental protocols such as that for vesicle formation, but work was also performed on electronic protocols for spatial confinement and control. Novel algorithms were developed and proved successful in a range of hard problems up to the complexity of experimental protocols for protein translation. The model-based evolutionary optimization algorithms developed in PACE represent a new state of the art for design of experiments for iterated high throughput experiments, and are beginning to have application well beyond the field of artificial cells.
- Model interactions of artificial cells, and emergent computation that comes from such interaction. A full sweep of modeling approaches, ranging from quantum mechanical calculations of photochemical sites to continuum mechanics and chemical kinetics were explored and examples integrated in a virtual lab. While the full multiscale integration of these diverse approaches would entail a full solution of most of the major outstanding problems in physical science, major progress was made in identifying and extending mesoscale simulation tools that could represent the full range of phenomena important for artificial cell simulation. In particular, this framework supports the interplay between physical self-organization of collective phases such as the cell membrane, and chemical turnover of molecules via reactions, and hence can capture the major novel effects that go beyond prior modeling frameworks for evolutionary chemistry. At the level of interactions between artificial cells, a theoretical framework was developed for programmed self-assembly via specific recognition, and employed in the project in connection with experiments on directed vesicle self-assembly.
- Use the theoretical framework and the experimental results to create a comprehensive view of possible application domains. The range of possible applications of this breakthrough technology defied being captured comprehensively at this stage of development of the field. Whereas the impact on future ICT was explored intensively and systematically, the range of other applications proved difficult to circumscribe. Generally, the major future application fields identified concerned embedded microscale systems, in particular information-intensive nanoscale construction, process control, diagnostics, repair and discovery. Applications to the production of future soft computer circuitry represent only one extreme in the spectrum of possible intelligent IT devices of interest at the nanoscale.
- Create a research centre as a geographical locus for a scientific and professional visitor program for the new interdisciplinary research areas initiated by this project, conduct two major scientific and technical conferences to publicize these new research areas, and conduct workshops to train professionals in its commercial development. The European Centre for Living Technology ECLT was established successfully and placed on a firm independent foundation during the course of the project. The Centre has acquired independent funding and new partners in the course of the project. It has already hosted several scientific and technical conferences and has managed to place the new area of Living Technology on the scientific map. Numerous workshops and meetings at the Centre have established its reputation as an exciting venue for multi-disciplinary activity in complex systems, in future emerging IT, in systems chemistry, in evolutionary science and not least in the ethical discussion of these areas related to its core in Living Technology. The PACE project has drawn up an ethical guidelines document for artificial cell research that will prove invaluable as the field gathers international impetus.