Automating Bioprocess Data Analytics in JSL for Cultivated Meat (2025-US-30MP-2413)

Cultivated meat offers a sustainable, slaughter-free alternative to traditional animal agriculture by growing animal cells in bioreactors for human consumption. This emerging field draws from traditional biopharmaceutical manufacturing but requires lower input costs to achieve commodity-scale pricing. At UPSIDE Foods, we developed high-throughput experimental workflows to test and optimize formulations rapidly. However, large data sets created a new bottleneck, where manual data processing slowed iteration cycles and delayed process decisions.

To overcome this, we set up real-time access to key instrument data (e.g., ViCell XR/Blu, Nova Flex 2). We then developed tools using the JMP Scripting Language (JSL) to pull data into JMP and automate our data analysis workflows. This presentation demonstrates the script's functionality, such as built-in data visualizations (Graph Builder), automated trend analysis (Bivariate Fit), and operator-facing tools to guide process interventions (Tabulate). Our approach also unlocked automation for advanced calculations requiring numerical integration and conditional relationships. As a case study, I use cell-specific glucose consumption qGluc (pg/(cell*day)) to highlight a few critical aspects of our methodology and demonstrate scripting strategies for beginners:

• Developing standardized sample naming conventions
• Establishing real-time access to instrument data with Open Database Connectivity (ODBC)
  
• Automatically organizing and cleaning data using operations like JOIN and SORT
• Creating formula columns using key functions (e.g., IF, LAG, IS MISSING)

Integrating live data streams with automated analytics in JMP significantly accelerated bioprocess development and reduced decision latency at UPSIDE Foods.