While the industrial applications of fermentation continue to grow, underlying challenges to scaling up this fundamental process still remain. At the core of this lies a common challenge: a reliance on manual data collection and paper forms and notebooks, ad hoc process and parameter documentation, Excel spreadsheets with multiple versions that are difficult to track, inflexible ELNs and LIMs, and disparate data files from multiple instruments that are difficult to impossible to format and contextualize for statistical analysis. But there's hope: here's how a digital backbone can transform industrial fermentation.
Designable process flows can serve as the source code for experiments and a foundation for a GitHub for science. In this post, we illustrate what we mean by “GitHub for Science” and how this could transform the way we advance scientific idea to manufactured products.
The key to analyzing data faster and more accurately is in the way we record and organize our data. Loren Perelman shows us the best way to organize our data for analysis and just might change your perspective on what constitutes a beautiful data table!
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Novozymes delivers four break-through biofuels products to market in half the normal development time with transformative digital infrastructure.Get the case study