Grand Challenges in Systems Physiology

Systems physiology is an integrated discipline. It combines experimental, computational, and theoretical studies to advance our understanding of the physiology of human and other living creatures. In other words, systems physiology is systems biology with a physiology (i.e., functionally)centered view. Understanding the principle behind the system is one of the fundamental challenges in systems physiology and systems biology. One can not make the use of sophisticated computational models or arrays of biological data to deepen our understanding of biological function without in-depth insights into the systems as a whole. For example, robustness and its trade-offs have been proposed as a fundamental principles (Kitano, 2004, 2007). This view, although still speculative, provides a framework for the conceptualization of data and observed phenomena. Identifi cation of a series of such principles and their relationships can enrich our understanding of biological systems. The beauty of a good theory is that it reshapes our view of the world, so that the same data and phenomena may be re-interpreted in the light of the introduced concepts. Such transformation of our conceptualization often leads to true advances in science. While such theoretical and explorative research are expected, it is also important to consolidate various efforts to achieve high impact objectives; these efforts are often referred as “Grand Challenges.” Defi ning grand challenges provide an effective approach that both illuminates unresolved issues and helps focus research effort on these problems and thereby advances the stateof-the-art in systems physiology. It is most effective when used for engineering-oriented projects where progress can be made by the effective coordination of research and development programs along with a series of technological innovations, rather than merely waiting for serendipitous explorations. While basic scientifi c explorations are still indispensable and much needed in this fi eld, it is also true that coordinated efforts on relatively well-defi ned missions can dramatically change the way we do science and apply it to medical practice. In this article, I attempt to defi ne a series of grand challenges that are interlinked and designed to accomplish the ultimate goal of creating an integrated understanding and platform for human healthcare services, biomedical research, and drug discovery. The grand challenge is to create highly accurate and broad coverage computational model of organisms that are backed up by well-controlled high precision experimental data. In practice, the true challenge is not only to build such a model, but also to establish a system of technologies that enable us to build these models costeffectively, because these models must match genetic and epigenetic diversity. With this technology, both virtual human and virtual mouse models shall be developed. In addition, models of specifi c cell lines shall be developed. This set of models shall be consistent with a set of cells and organisms used for drug discovery and biomedical research. The reality of the drug discovery pipeline is that it uses cell lines and animal models before moving into clinical trial. Thus, it is important that not only human models, but also mouse and cell line models are developed with an equal level of quality. Accomplishment of this grand challenge will enable us to use computational models and associated experimental verifi cation systems to understand disease mechanisms, and to predict drug effi cacy, side effects, and therapeutic strategy outcomes. At a workshop held in Tokyo in February 2008, a group of researchers agreed to initiate a project to create a “virtual human” in next 30 years (Jones, 2008). They also announced the Tokyo Declaration that reads in part as follows: “Recent advances in Systems Biology indicate that the time is now ripe to initiate a grand challenge project to create over the next 30 years a comprehensive, molecules-based, multi-scale, computational model of the human (‘the virtual human’), capable of simulating and predicting, with a reasonable degree of accuracy, the consequences of most of the perturbations that are relevant to healthcare.” Although creation of a virtual human (a comprehensive computational model of human being) has been the subject of much discussion in variety of conferences and workshops, the real implications and diffi culties with the model need to be readdressed. There is no doubt that simulation, if properly used, can be a powerful tool for scientifi c and engineering research. Modern aircrafts cannot be developed without help of computational fl uid dynamics (CFD). CFD is one of the most successful computational approaches used in the engineering design process. There are three major reasons why CFD is now widely accepted. First, the Navier-Storkes equation has been well established to provide a computational basis for fl uid dynamics with reasonable accuracy. While there are yet unresolved issues on how to compute tabular fl ows accurately, the Navier-Storkes equation provides an acceptable practical solution for most needs. Second, many CFD results are compared and calibrated against wind-tunnel experiments that are highly controlled and extensively monitored. Due to the existence of the wind-tunnel, CFD models can be improved for their accuracy and reliability of predictions. In wind tunnels, air fl ow speed, temperature, and other parameters can be adjusted within a very small error margin, for example within 0.01% error margin. Third, decades of effort have been spent on improving CFD and related fl uid dynamics research. Thus, the current status of CFD is a result of decades of effort. For computer simulation and analysis in biology to parallel the success of CFD, it must establish a fundamental computing paradigm comparable to the Navier-Storkes equation, to create a wind-tunnel equivalent for biological