Bio-ICT Synergies

by Fernando Martin-Sanchez

The prospect of having ICTs that would be more life-like and thus for instance more robust, self-regulating, adaptive, evolving, environment friendly and easy to live with, has long stimulated computer scientists to look for inspiration in the biological domain. Most bio-inspired ICT techniques and methods were designed on the basis of biological knowledge available at the '80s. In the meantime, biology has brought a wealth of new knowledge - for instance on development, action, perception, homeostasis and learning - that can now be exploited to fuel further advances in ICT systems. Conversely, efficient algorithms can be used to reflect back to biology, for instance to enable more efficient drug design, to move toward personalized medicine, or to distill a more synthetic view of the biological field. Beyond such cross-fertilization, however, maturing technologies and knowledge from both sides are paving the way for a deeper convergence between the biological and the ICT domain which will lead to systems with tightly integrated biological and technological components and to radical innovations, for instance in computer architectures, interfaces, prosthesis and implants.

The aim of this thematic group is to identify a long-term research agenda that would unlock the full potential of Bio-ICT synergies over the next few decades. How can we meaningfully combine biological and technological perspectives and exploit what is learned to advance both biology and technology, effectively linking the realms of information, material and life? The vision of technology becoming like a 'second nature' would have tremendous social, economic and industrial impact. Not only would it lead to new types of computational hard- and software; it would also improve, among others, manufacturing, medicine, the energy sector and the quality of the environment and of life in general. This will require radical interdisciplinarity, including the whole range of life sciences, but also the nano- and neuro-sciences. This being said, this group emphasises the ethical dimension of the vision, as well as the well known but unresolved difficulty of genuine multi-disciplinary research as key extra-scientific hurdles to be addressed.

Proposed Research Themes
Three main research themes were identified as pillars for exploiting the Bio-ICT synergies potential, namely 'New Computational Modelling Paradigms', 'Bio-Inspired Strategies of Growth, Adaptation and Evolution' and 'Bio-ICT Artefacts' (see Figure).

Connecting the natural, digital and artificial worlds: cell modelling, synthesis and hybrid systems.
Connecting the natural, digital and artificial worlds: cell modelling, synthesis and hybrid systems.

1. New Computational Modelling Paradigms
A major research challenge is the formalization and development of computational paradigms that are capable of capturing, relating and integrating the different levels of complexity in biological systems - from the molecule to the cell, tissue, organ, system, individual, population and ecosystem. Some of the technical challenges involved are: (a) connecting models at different levels of abstraction, (b)connecting discrete with continuous models, (c) dealing with inconsistent, competing models and (d) fitting models to data (data driven modelling). Other than contributing to systems biology, this research would lead to new computational architectures inspired by natural information processing structures eg in the brain or molecular processing within the cell, but applicable in different domains than the biological ones.

A thorough understanding of information processing in biological systems would lead to new computing systems based on 'wet-ware' or other life-like hardware, consisting of very large numbers of simple devices operating in a highly parallel fashion at comparatively low speed and with very low power dissipation.

2. Bio-Inspired Strategies of Growth, Adaptation and Evolution
In contrast to technological systems, biological systems have extraordinary capability to change over time. They grow, adapt, self-assemble, replicate, heal, self-organise, evolve. The second theme thus concerns studying how technological systems can grow, change, adapt, organise, heal and evolve to match, over long periods of time, evolving needs whilst being compatible with natural processes of change that surround them, for instance when dispersed in the environment, or when implanted. These different strategies of change are not independent but operate at different time scales and either at the individual or population level. We propose an interdisciplinary exploration of adaptation, learning, self-organisation, evolution and other emergent functionalities of living systems for the design of new computing models, algorithms and software programming paradigms. Moreover, there is enormous potential for applying this at the physical level, in particular at the nano- and micro scale, to develop new types of growing and evolving hardware (eg, memory or computing capacity grows when needed) and intelligent materials that could be applied in a variety of ambient interfaces.

3. Bio-ICT Artefacts
The third theme of research in modelling both the organizational and phenomenological features of living systems is to seamlessly integrate artificial entities into biological systems and processes (classical examples include artificial retinas or physiologically coupled artificial limbs). In this sense, main challenges include: (a) developing new information theories and modelling techniques to capture how biological systems realise basic capabilities of living systems at different granularities, (b) developing ways to validate such theories with respect to real biological systems, (c) interfacing between the living and the artificial world, including restoration or substitution of human capabilities (eg, using implants), (d) providing sensor/motor interface to the body, (e) extending the range of capacities beyond perception and action, including for instance memory, resistance to bacteria and viruses, or interfacing directly in metabolic processes ('cyber-drugs').

Participate in the online consultation of this report from 1 February to 31 March 2006 at

TG4 Coordinator:
Fernando Martin-Sanchez, Institute of Health Carlos III, Madrid Spain