On transferring the grid technology to the biomedical community

Area of Science:

• Biomedical Informatics
• Computer Science
• Technology Transfer

Background:

• Physicists pioneered Grid computing, enabling resource sharing.
• Classical technology transfer models, like Bozeman's, are insufficient for rapidly evolving technologies such as Grid and Cloud solutions.
• Life sciences face unique difficulties in adopting Grid technologies.

Purpose of the Study:

• To illustrate how Grid computing introduces novel challenges to technology transfer not addressed by existing models.
• To redefine success metrics for health Grids, emphasizing scientific human capital and created opportunities over market impact.
• To provide recommendations for improving Grid solution adoption in the biomedical community.

Main Methods:

• Analysis of technology transfer challenges using Bozeman's Effectiveness Model as a baseline.
• Illustration of Grid technology transfer realities through two case examples.
• Evaluation of success metrics for health Grids.

Main Results:

• Grid and Cloud computing technologies are in constant flux, complicating traditional technology transfer.
• Bozeman's model does not account for the dynamic nature of Grid technologies.
• Success in health Grids is better measured by scientific advancements and opportunities generated.

Conclusions:

• Existing technology transfer models require adaptation for rapidly evolving fields like Grid computing in life sciences.
• Focusing on scientific capital and opportunities offers a more accurate measure of health Grid success.
• Specific recommendations can facilitate the integration of Grid solutions into biomedical research, overcoming common adoption barriers.