Fri, June 30th, Breakout Session
Moderator: Navin Varadarajan, Ph.D. (University of Houston)
The last few years have seen a dramatic increase in the number and complexity of single-cell technologies. A large number of these advances have been pioneered by individual laboratories. though in order for single-cell technologies to mature, they must become standardized tools that enable any biologist/clinician can access to test hypotheses. Mass cytometry is an example of one such tool that has made the successful transition. The scope of this discussion is to understand the challenges behind moving the technologies from the labs of the inventors and to make them commercially available tools/techniques.
Questions for the breakout session to consider include:
- Validation. One of the major challenges with single-cell technologies is cross-platform validation. While single-cell technologies provide the ability to deliver insight that would not be available based on population analyses, it is important to be able to identify technical errors, limitations and how to implement confidence metrics in single cell results.
- Standardization of statistics, bioinformatics and visualization. Another major challenge with single-cell data is to have robust methods that perform normalization, discretization etc. in a standardized manner. Good practices in defining thresholds, how they are determined and adhering to a minimal set of standards that will be published (e.g. see Minimal Information About T cell Assays, MIATA) comprise an essential framework. Similarly, there is a need to develop to visualization packages that better describe the complexity of multi-dimensional, time-resolved single-cell data. E.g. viSNE is good for single time points but what about time series?
- Technology transfer. How can the chasm between academic research valued for its novelty and biological insights and customer-centric platforms that are reliable and deliver repeatable be bridged better? What are the conditions necessary for matching market pull with technology push to minimize the challenges with technology transfer?
- Commercialization. There are many layers to commercialization including IP framework, hurdles to manufacturing, ease of implementation and market adoption. What programs can help PIs understand these challenges: NSF ICorps? Institutional help?