A supplier of manufacturing operations management (MOM) software says it is unifying data across a broader range of systems and adding more analytics, and is seeing a greater number of mature use cases among its customers.
According to Scott Drap, sales director at Quartic.ai, as a growing startup, the company has also seen an increase in front-line customers scaling the Quartic software to work across multiple manufacturing facilities.
“What’s new or different in the last few years is that we’re more mature in combining data from IT systems across the enterprise—it’s not just coming from the plant floor,” he says.
Quartic.ai, which will be presenting at the 17th Annual Bioprocessing Summit in Boston, says it’s easier to evangelize about its technology.
“We’re more mature as a company, and that means we have mature use cases of all the benefits that our customers have seen,” says Drap.
Case study
In their talk at the upcoming Bioprocessing Summit, Manuel Tejeda, director of customer success, and Vinodh Rodrigues, vice president of customer success, both at Quartic.ai, will present a case study of a customer who struggled with the amount and consistency of their monoclonal antibody (mAb) yield.
“Their chromatography column had a specific lifetime for each packing, but their yield measurements were coming in two weeks or more after each batch was completed, so they couldn’t reliably leverage this recommended lifespan,” Tejeda explains.
“With the Quartic.ai platform, using real-time batch monitoring, they were able to build models to determine the remaining useful life or quality of that packing column, and predict what the impact would be on yield.”
The result, Tejeda says, is that, on several occasions, the manufacturing technology users were able to communicate to the operations team that the packing quality was degrading early. “They were able to replace the packing to ensure the remaining batches in the campaign weren’t affected,” Tejeda explains.
The customer was also able to monitor conductivity in the mixing of the buffer solution to deal with inconsistent conductivity, a common issue in chromatography columns. “They were able to create models and deal with some other issues too in real-time,” Tejeda says.
The result, Drap explains, is that the customer was able to reduce discarded batches and increase yields, saving both time and money.
According to Rodrigues, this case study links to broader industry trends. “Our customers aren’t just dealing with operational technology (OT) data anymore, but over the past couple of years, we’re also seeing laboratory information management systems (LIMS), and they want to bring in data from enterprise resource planning (ERP) systems.”
Many of them have do-it-yourself solutions, Rodrigues explains, but without data integration, clients such as the one mentioned in the case study can experience turnaround times of 7–10 days. “And that’s the change we’re trying to implement—the intelligence to leverage all these new pipelines of data coming in.”
The company says it is working to help its existing clients scale up solutions implemented at one site across multiple plants.
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