The speed and precision of today’s genome editing technologies have led to myriad advancements in molecular biology. However, these advancements have created a double-edged sword, and biologics manufacturers like Novozymes must face both sides. With yeast strain selection for industrial applications becoming increasingly complex, the organization realized it needed a new approach powered by statistics. After years of pandemic restrictions, Novozymes saw an opportunity to strengthen their internal data programming community and their collaboration with experts at JMP.


Two of Novozymes' North American sites are in Franklinton, NC and in the Research Triangle Park, an internationally known biotech hub. Hosting the Hackathon at the nearby JMP Headquarters in Cary emerged as a strong option. Working with personnel at JMP, Novozymes leaders arranged to host Zymers at the Global Education Center at JMP HQ. Here, employees worked in self-selected groups on nine analytics projects, some using JMP in novel ways to streamline their workflows. One of these groups spent their time on the JMP campus looking at novel approaches to yeast selection.


After the conclusion of the Hackathon, Novozymes hosted a debriefing session to describe how each group employed JMP to achieve their analytic goals. Such innovations included improvements to the yeast selection procedure, in which a method once requiring 752 tubes across 4 experiments was pared down to just 300 tubes in 1 experiment. This type of collaboration showcased at the Hackathon demonstrated Novozymes’ deepening relationship with JMP and the democratization of data literacy in the organization.

The relationship between a software company and its customers is often clinically sterile: the client identifies the software as valuable, elects to purchase some number of licenses, and then deploys the program to optimize a given task. By all accounts, this type of relationship is beneficial to both parties. The software company succeeds in selling its product, and the buyer enjoys a streamlined workflow. However, if the labels of supplier and customer are removed, a deeper relationship emerges. JMP and Novozymes are striking such a bond, becoming partners rather than producers and purchasers. In the process, a synergy has brewed, propelling Novozymes’ ideals of creativity and collaboration.

Novozymes, a global manufacturer of industrial enzymes and microorganisms, has defined the forefront of biotechnology since its founding as a spin-off from Novo Nordisk in 2000. Since then, Novozymes has amassed substantial acclaim, including receiving the 2021 and 2022 EPA Safer Choice Partner of the Year Award in recognition of its accomplishments in human health and environmental safety. Producing everything from carbonic anhydrase for more cost-effective carbon capture to pectinase for cleaner fabric biopreparation, the organization strives to redefine industrial science using biology. With this ambition, it’s no surprise that Novozymes emphasizes collaboration.

The Novozymes Hackathon was launched with the goal of bringing together individuals from wide-ranging scientific departments to address and overcome strategic challenges at the institution. The Hackathon initiative quickly drew the support of leadership. Staff Data Scientist Heidi Privett notes that “the Hackathon is a really great forum to bounce ideas off one another.” Taking place virtually during the coronavirus pandemic of 2020, the company sought a return to in-person hacking this year. Lead data science engineer Michael Akerman reached out to the Novozymes’ JMP account team shortly thereafter, and the Hackathon was welcomed to JMP’s Global Education Center at SAS Headquarters in Cary, North Carolina.

Data literacy for all

At Novozymes, Akerman explains, “there’s a huge amount of support from upper management for digitalization, data science and JMP to make sure that we do our science effectively.”

With a background in both pure chemistry and chemical engineering, Akerman understands the challenges with taking a fundamental chemical innovation—for instance, the synthesis of a new enzyme—and upscaling it to an industrial level. The principal obstacle to this growth, he notes, is the integration of statistical thinking into all teams involved. If the proliferation of statistical thinking is achieved companywide, scaling from bench to industry is much smoother.

Conventionally, bench scientists at organizations with the market reach of Novozymes outsource data analysis to a centralized team of consulting data scientists. This handoff is undesirable, Akerman notes, because data is transferred beyond its original domain. By bolstering data literacy across R&D, data can be both produced and analyzed by the same team, thereby reducing bias and stimulating innovation.

The 2023 Hackathon presented a valuable opportunity for Novozymes to emphasize data and experimental literacy in cross-functional groups. Small, interdisciplinary teams applied JMP to investigate a diverse array of obstacles.

“It was the best of both worlds,” Privett says. “Zymers were able to travel to expand their networks and work on some cool stuff at the same time;” a dual imperative that effectively delivers value to the business by broadening collaboration and energizing employees with a forum for creative problem solving.

"The Hackathon is a chance to turn ideas into opportunities"

Michael Akerman

Data Scientist, Novozymes

The project selection procedure and Hackathon structure engendered genuine employee interest in the subject matter. Projects were self-organized, and the ideas listed with descriptions in a database accessible to all employees. Hackathon participants then self-selected into projects that piqued their interest. One such project focused on the use of statistically designed experiments to streamline a microorganism selection procedure critical to Novozymes’ industrial partners.

Broadening the scope of statistically designed experiments

The selection of top-performing yeast strains to deliver to ethanol producers is a cornerstone of Novozymes’ business and was the subject of a recent Hackathon project. Manufacturers begin with corn and derive ethanol according to the schematic below. The ethanol is then mixed with fuel, yielding the 10% ethanol gasoline familiar to consumers.

Since yeast is what provides the final marketable product, the fermentation step is of paramount importance. While hydrolysis of starch provides the necessary glucose intermediate, the desired marketable product is ethanol. Without effective yeast fermenting the glucose into ethanol, the process fails. Thus, fermentation laboratories require the best quality yeast. In practice, this expectation means the yeast must yield maximal ethanol production with minimal unwanted byproducts—a standard leading Novozymes to a distinctly twenty-first-century headache. Globally, genetic tools have improved, but Novozymes-specific processes for evaluating yeast performance and high throughput screening have also developed, making their selection procedure for top yeast strains increasingly complex.

“Novozymes has become so good at developing high ethanol-producing yeast strains that it is now difficult to select top candidates,” scientist Brianna Thompson adds, noting that it’s a great problem to have; these selection headwinds result from years of genetic research and innovation. However, to market the best quality product, one yeast strain must be selected as the most efficient, opening the door to statistical testing.

The large number of parameters that can change how a yeast strain will perform creates a logical opportunity for the company to use design of experiments (DOE) capabilities in JMP. To break down the impact of each individual factor, Thompson further adds that Novozymes “can look at the variability of its ethanol producers, using DOE to gain insight into which factors influence each yeast.” This Hackathon initiative represents a novel application of DOE within the company.

Instead of limiting DOE use for late-stage analysis of how factors influence preselected strains, the group could now perform the actual selection with DOE, too.

The power of DOE is its streamlining prowess. The customary approach in R&D is to test one variable at a time, but DOE uses statistics to design experiments that assess multiple variables concurrently. This efficiency often affords substantial time and resource advantages to the user.

At this year’s Hackathon, Thompson and her colleagues sought to design the framework for this kind of selection procedure. With sixty strains to evaluate and twelve variables contributing to yeast viability, narrowing the field was challenging. But wielding DOE, the team was able to substantially smoothen the selection process.

A method once requiring 752 tubes across 4 experiments was pared down to just 300 tubes in 1 experiment, while simultaneously testing more variables.

Thompson notes that complicated and powerful information about the data, such as factor interactions and graph curvature, are visualized in JMP with ease. Such an application embodies just how powerful DOE is in simplifying experiments, allowing for continually streamlined processing in a world of innovation.

Fostering a deeper relationship with JMP

In May 2023, Zymers from across the world converged upon the Global Education Center, ready to demonstrate Novozymes’ commitment to collaborative analytical development. With shared visions for emboldening scientists through statistical enablement, the partnership between JMP and Novozymes is only natural.

Thompson’s result was just one of many value-adding solutions to come out of the 14 projects addressed during the Hackathon—yet another indicator that the two companies’ partnership goes well beyond that of a traditional supplier and buyer.

“JMP is a tool that Novozymes uses quite extensively,” says biostatistician Jonathan Kennedy, adding that it makes sense that the Hackathon would be supported by the JMP organization. Not only were Novozymes team members brought together for the Hackathon, but there were “resources available on site to advise those using JMP.” As a result, “group members were able to reach out to a wider breadth of colleagues working in different areas of the company with different types of data,” adds Senior Data Science Engineer Ryan Schroen. The result is an organization with second-to-none data production capabilities. And as Thompson notes, “JMP tools are really good at helping Novozymes understand what the data means so that we can make the right decisions.”

Novozymes excels in scientific innovation and data creation, and JMP specializes in telling stories with data to inform decision-making. The 2023 Hackathon forms just one facet of the relationship between the two value-driven companies; a bond far surpassing the surface of software.

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