Case Study
How BioHarvest Sciences Optimizes Manufacturing and Yield Prediction with BioRaptor
About
BioHarvest Sciences specializes in botanical synthesis, producing plant-based compounds in bioreactors. It is the first company in the world to grow plant cells in a liquid medium on a commercial scale. Their groundbreaking technology enables the selective growth of active compounds from plants without cultivating the entire organism. Their flagship product Vinia, a red grape extract, has generated $50M in sales with 100% YoY growth. Additionally, their CDMO services offer pharmaceutical companies, global beauty brands and food industry leaders, consistent quality control, industrial spare production, IP ownership of the proprietary molecules, all with greater reduced environmental impact.
Challenge
As BioHarvest scaled to 100 bioreactors and beyond, maintaining a stable manufacturing environment became increasingly complex. Key issues included:
Manual Data Collection
Operators spent hours daily recording parameters by hand, transcribing them into Excel spreadsheets.
Unwieldy Data Management
The growing volume of Excel data was difficult to query or analyze, limiting the ability to test hypotheses or identify deviations.
Operational Bottlenecks
Detecting and investigating yield deviations was a time-intensive process, often taking days due to fragmented and poorly integrated data.
Limited process visibility
Without a real-time quick overview, teams relied on retrospective weekly reviews, which often missed subtle trends or changes occurring in the bioreactors.
BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
Solution
After quick and painless implementation, BioHarvest now uses BioRaptor to manage all their bioprocess operations. It is a critical part of their operating system. Key benefits include:
Automated Data Collection
BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
Real-Time Metrics
Operators and scientists can see all critical metrics across all bioreactors, enabling proactive monitoring and swift decision-making.
Collaboration
Teams can easily share visualizations within experimental contexts, and discuss in real time why we are experiencing changes as they occur without the need for screenshots or copy and pasting data into excel.
Customization and Flexibility
BioRaptor’s adaptability allowed seamless integration with BioHarvest’s processes, reducing the learning curve and ensuring rapid adoption.
Advanced Analysis Tools
BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
- Automated mapping of growth curves.
- Rapid comparison of bioreactor performance
- Root cause analysis to investigate deviations in minutes, not days
- Design of Experiments for some of the smallest substreams
- Customized reports and queries
BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
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BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
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BioRaptor automates data collection across bioreactors, harmonizes and contextualizes to align all parameters with BioHarvest’s nomenclature.
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Results
Bioraptor has fundamentally changed how BioHarvest Sciences operate, reducing the time spent organizing data and enabling analysis as part of the daily workflow.
Management now uses BioRaptor dashboards in their weekly meetings, where they do an intensive review of the performance of everything that's on the manufacturing floor, plan their experiments, and can accurately predict and manage yield.
They are now able to focus our scientists on useful experiments, make the best informed decisions and ultimately plan the BioHarvest product roadmap with certainty.
The platform has truly changed the way we work, reducing the time spent organizing data and allowing analysis as part of the daily workflow. With all our data consolidated, we can quickly explore, understand, and improve our bioprocess accordingly. In addition, we have optimized our daily critical decision making process.
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IIan Sobel
CEO, BioHarvest Sciences
