There are a plethora of tools and innovative approaches to the development of cyberinfrastructure in order to support multiscale modeling activities. However, better and more robust approaches will always come out of close collaborations between computer scientists and biomedical researchers, as well as other field specialists. The interactions will educate all the groups to be fully aware of the requirements and challenges of the state of the art technology, and make routine use of the grid possible today. In addition, the development of new tools that support applications in different fields and through international collaborations greatly reduces the collective cost for global computational grids. The service oriented approach is gaining momentum and greatly facilitates the development of a knowledge based global economy.

There are often conflicting requirements between biomedical research and grid communities, with the former accustomed to a “one experiment at a time” approach, and the latter desiring systems that handle large number of jobs simultaneously. The reality is that current grid computing systems are still difficult to learn, only relatively stable, and limited by the technologies available in hardware, software, and programming languages, as noted in [³]. It is a challenge to both communities to design better software and use them effectively. With these caveats in mind, one may attempt to select from the available tools and build a robust platform to make routine use of the grid possible, through close collaborations with developers of all components involved where possible. By working with different applications and addressing the common needs and individual requirements, reusable components may be isolated without sacrificing the customized environments demanded by users. The structure of resources supported by the National Center for Research Resources, such as NBCR and NCMIR, requires collaborative projects to guide the development of the tools, as noted above.

The number of tools showed in Figure 5, along with those represented only as “…”, offer many possible combinations to build end to end problem solving environments, often with overlapping features. For every tool listed, there are solid alternatives under different use cases. As shown in the usage scenarios, the ultimate choice of tools depends on the specific problems to be solved and the target audience of the designed environment. As demonstrated by the number of tools that are using Opal based services, the service oriented approach provides the flexibility in customized front-end tools with transparent access to underlying distributed computation resources. The demands of multiscale modeling applications will drive the development of the computation and data cyberinfrastructure, which in turn enables simulation based biology and medicine. The ensuing challenges in the search for solutions of more difficult problems will further this iterative developmental cycle of technology and science, with continuous and immediate impact to the health and well being of the public.