Case Studies Engineering sweet proteins at scale to improve population health

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	Engineering sweet proteins at scale to improve population health

Engineering sweet proteins at scale to improve population health

Technology Category	Application Infrastructure & Middleware - Data Visualization Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries	Food & Beverage Healthcare & Hospitals
Applicable Functions	Product Research & Development Quality Assurance
Use Cases	Predictive Quality Analytics
Services	Data Science Services System Integration
Challenge	Joywell, a company on a mission to replace sugar with nutritious sweet proteins, faced several challenges in its quest. The company's data lacked context, making it difficult and time-consuming to make business decisions. The data was scattered across multiple people, notebooks, and machines, resulting in weeks of extra work and preventing teams from answering important business questions quickly. The teams struggled to aggregate large sets of data as data generated by different instruments would come out in different formats. This required scientists to perform a manual, tedious last step of standardizing 10-20 different file formats or risk leaving questions unanswered. To meet its ambitious goals, Joywell needed to ensure its processes are robust and repeatable not just within its lab but also at partner labs. Read More
About Customer	Joywell is a company based in Davis, CA, with a workforce of 11-50 employees. The company operates in the Industrial Biotech industry. Joywell is on a mission to bring joy and wellness to people by delivering sweet protein products that reproduce the sweetness of sugar without the adverse health repercussions. The company’s goal is to replace sugar with nutritious sweet proteins — helping to fight diabetes, heart disease, and other harmful effects of sugar. To accomplish this goal, Joywell needs to ensure their single batch fermentation processes can be translated to industrial production levels and sweet proteins can reach consumers at scale. Read More
Solution	Joywell implemented Benchling’s R&D Cloud, a platform designed to support the types of scientific experiments that Joywell conducts, such as strain engineering and fermentation. By storing standardized data from multiple experiments and various instruments in a single database, Benchling makes valuable data more accessible, saving time and facilitating collaboration. Strain engineering and fermentation teams no longer need to spend hours reformatting data, inputting large datasets into spreadsheets by hand or manipulating the data to gain insights. With Benchling, scientists get to see their data contextualized visually, right away to help them make decisions. The solution also improved collaboration and scalability, supporting commercialization and growth. Joywell can easily track critical success metrics during fermentation and downstream processing like titer, microbial productivity, purity, recovery yield. Read More Log in to view content
Contents

Technology Category

Application Infrastructure & Middleware - Data Visualization

Platform as a Service (PaaS) - Data Management Platforms

Applicable Industries

Food & Beverage

Healthcare & Hospitals

Applicable Functions

Product Research & Development

Quality Assurance

Use Cases

Predictive Quality Analytics

Services

Data Science Services

System Integration

Challenge

Joywell, a company on a mission to replace sugar with nutritious sweet proteins, faced several challenges in its quest. The company's data lacked context, making it difficult and time-consuming to make business decisions. The data was scattered across multiple people, notebooks, and machines, resulting in weeks of extra work and preventing teams from answering important business questions quickly. The teams struggled to aggregate large sets of data as data generated by different instruments would come out in different formats. This required scientists to perform a manual, tedious last step of standardizing 10-20 different file formats or risk leaving questions unanswered. To meet its ambitious goals, Joywell needed to ensure its processes are robust and repeatable not just within its lab but also at partner labs.

About Customer

Joywell is a company based in Davis, CA, with a workforce of 11-50 employees. The company operates in the Industrial Biotech industry. Joywell is on a mission to bring joy and wellness to people by delivering sweet protein products that reproduce the sweetness of sugar without the adverse health repercussions. The company’s goal is to replace sugar with nutritious sweet proteins — helping to fight diabetes, heart disease, and other harmful effects of sugar. To accomplish this goal, Joywell needs to ensure their single batch fermentation processes can be translated to industrial production levels and sweet proteins can reach consumers at scale.

Solution

Joywell implemented Benchling’s R&D Cloud, a platform designed to support the types of scientific experiments that Joywell conducts, such as strain engineering and fermentation. By storing standardized data from multiple experiments and various instruments in a single database, Benchling makes valuable data more accessible, saving time and facilitating collaboration. Strain engineering and fermentation teams no longer need to spend hours reformatting data, inputting large datasets into spreadsheets by hand or manipulating the data to gain insights. With Benchling, scientists get to see their data contextualized visually, right away to help them make decisions. The solution also improved collaboration and scalability, supporting commercialization and growth. Joywell can easily track critical success metrics during fermentation and downstream processing like titer, microbial productivity, purity, recovery yield.

Impact #1	Scientists save hours per week on data capture and entry, improving productivity.
Impact #2	Automatic dashboards and reports save scientists time, eliminating manual, tedious steps.
Impact #3	Executives get real-time insight into performance to help guide business strategy, enabling faster decision making.

Impact #1

Scientists save hours per week on data capture and entry, improving productivity.

Impact #2

Automatic dashboards and reports save scientists time, eliminating manual, tedious steps.

Impact #3

Executives get real-time insight into performance to help guide business strategy, enabling faster decision making.

Benefit #1	Scientists save hours per week on data capture and entry.
Benefit #2	The company has already completed three tech transfers.

Benefit #1

Scientists save hours per week on data capture and entry.

Benefit #2

The company has already completed three tech transfers.

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Overview

Engineering sweet proteins at scale to improve population health

Operational Impact

Quantitative Benefit