I looked at the site as well - lots of interesting bits of information. I snipped out the following which caught my eye:
There is, first, a numbers argument. If, historically, to discover a useful delivery medium might have required 100 experiments, each taking a day to complete, then a capability for performing 1000 experiments of comparable yield in one day, might be expected to yield 10 novel delivery media in just one day. Thus, high throughput experimentation is expected to have an impact simply from its ability to accelerate the Edisonian method by two to three orders of magnitude, improving the odds of chance discoveries. This raw experimentation capacity was key in the development of the delivery media that are being advanced as fqubed's first specific products.
Secondly, there is an information-enrichment argument. High throughput experimentation integrates computation with experiment; the choices of what experiments to do and how to perform them are assisted by simulation and computational design tools, by the data on experimental operations, such as processing procedures, and by the various property data accumulated in a data base that offers data accessibility to data mining and model development programs. Thus if the information yield per experiment can be maintained at an effective level, the extensive data sets are expected to yield better insights into the relationships between preparation, structure and properties.
Thirdly, and this is perhaps more of an opportunity in the soft materials domain than for other materials classes, there is the possibility to be prompted by the mechanics of the high throughput experimentation operations to sample new materials spaces, through performing processing in different ways than applied previously.
It got me to thinking about the pennsaid plus formulation, fungoff and how owning this company could assist NRI in keeping potential competitors at bay.
It also had me thinking about fast track applications at FDA. |
