Case Study

Bioprocess analytics case study

“It used to take a scientist 40 hours to manage three weeks of experiment data. With Riffyn Nexus it can now be done in one or two hours.” — Riffyn customer


Learn how a global ag-biotech company has been able to:

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    Reduce the time needed to manage experimental data from 40 hours to only 1-2 hours

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    Break down communication barriers and eliminate confusion

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    Link and correlate data across fermentation and analytical chemistry teams

Fermenter illustration

It is estimated that scientists waste up to 80% of their time cleaning and readying data for analysis instead of analyzing data and making important discoveries. It is difficult to grasp what that means until you experience that pain for yourself and relief from it, as one Riffyn customer did. Here is their story — and how you can achieve similar results for your R&D processes.

The Challenge

A major biotech company spanning the agriculture, food, and pharmaceutical space needed to speed up their R&D processes. To meet their goal, they needed to contextualize and connect work being done over time by multiple groups within fermentation and analytical chemistry. A major roadblock to meeting their goal was fragmented data tools and systems leading to siloed data.

Most of their data were being captured and stored in spreadsheets, which typically belonged to different individuals who crafted each one uniquely. This made data difficult to impossible to share and contextualize in the broader experimental ecosystem. As a result, a lot of time was lost on miscommunication rather than on data analysis and interpretation.

The Outcome

To solve this problem, the Riffyn Science team used Riffyn Nexus to completely digitize our customer’s fermentation data capture, sample submission, and analytical data reporting. This provided all users across the groups with rigorous, standardized results. Using Riffyn Nexus, the fermentation team could instantly see the analytical data in the context of their process conditions, and the analytical team could understand where samples fit into the upstream fermentation process. This eliminated the need for them to do complex sample management and ultimately simplifying communication across the fermentation and analysis teams. It allowed all the team members to to see and investigate deviations and correlations in real-time.

Process data analytics 2

Complete fermentation process captured in Riffyn Nexus, including online and offline analytics. Cleaned, contextualized, aggregated data is analyzed in real-time with third-party analytics plugged-in directly to Riffyn Nexus.

Eliminating spreadsheets has also reduced human error and saved time previously spent on manual curation. It used to take one scientist 40 hours to manage three weeks of experiment data. Now, using Riffyn Nexus, data are automatically collated, contextualized, and readied for analysis. What used to take a standard work week now only takes one to two hours to complete. With the customer running 17 such experiments throughout the year, and a 20X reduction in data management time, our customer has realized hundreds of hours of time savings. The customer is now expanding Riffyn Nexus for downstream processes, including integration with the Riffyn API for lab automation, as well as expanding into other groups within the company.

Plots created with JMP® Software. Copyright 2019, SAS Institute Inc., Cary, NC, USA. All Rights Reserved. Reproduced with permission of SAS Institute Inc., Cary, NC.

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