Translation of novel therapies for type 1 diabetes and other autoimmune diseases to the clinic has been slow despite significant new initiatives from funding agencies. One reason for this is that different incentives drive industry, academia, and funding bodies. These communities therefore lack common goals and often communicate poorly, resulting in unintended obstacles that hamper progress in efficiently translating basic scientific discoveries into medical practice. Here, based on our own personal experiences, we discuss some of the drivers within each community that cause these problems, existing mechanisms to facilitate the translation of science into medical practice, and remaining issues that need to be solved.
Matthias von Herrath, Andrew Chan
Usage data is cumulative from July 2024 through July 2025.
Usage | JCI | PMC |
---|---|---|
Text version | 257 | 10 |
76 | 14 | |
Figure | 53 | 0 |
Citation downloads | 93 | 0 |
Totals | 479 | 24 |
Total Views | 503 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.