The great digital shift: Where synthetic biology, biomanufacturing, and biopharma combine

This article originally appeared on SynBioBeta.

There’s a great digital transformation at the heart of synthetic biology. Advances in lab automation, data processing, analytics, and more are converging to move ideas to market at unprecedented speed. Industries that cling to existing R&D approaches do so at their own peril.

Riffyn gives us another wonderful example of this with today’s announcement of how their scientific development environment (SDE) helped Novozymes—already an industry leader in biological solutions—cut development times in half in four biofuels products. In a case study, the two companies describe how the digital R&D infrastructure enhanced real-time collaboration on experimental design and data analytics, increased strain building and screening throughput by an order of magnitude, and halved product development time using half the personnel.

The partnership between Riffyn and Novozymes was kindled at SynBioBeta, and the fact that the Riffyn framework is driving innovation in the manufacturing of foundational bioproducts like fuel ethanol says a lot about how the digital shift is changing what products and markets are possible today and in the future.

Riffyn was started by Timothy Gardner, known to many as one of the early pioneers of synthetic biology. As Tim’s career took him from academia through to leading research & development at Amyris, along the way he came to understand that big data could be a big problem for companies, with researchers drowning in data but thirsty for usable knowledge. It is estimated that 80% of data scientists’ time is spent not analyzing data, but instead on cleaning it up. Also, much industry R&D data lacks standardization, leading to data fragmentation and lack of reproducibility—and therefore lack of a product. 

Tim founded Riffyn in 2014 with the goal of bringing a digital transformation to industry. The idea behind the Riffyn scientific development environment (SDE) is simple and powerful: structure your data and processes in a way that makes them maximally accessible for machine learning and collaboration. This digital shift in R&D harmonizes people, process, and data, and lets scientists focus on analyzing data, not managing it. 

Check out the RIffyn and Novozymes case study for details about this collaboration, and how biopharma, biomanufacturing, and other industries stand to be transformed by the great digital shift.