Quartic.ai, Sparta Systems partner on ‘smart’ manufacturing tech

14-Jul-2020 - Last updated on 14-Jul-2020 at 14:25 GMT

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The two companies are collaborating on AI-enabled risk detection, intended to increase pharma product quality and process efficiency.

Quartic.ai is joining forces with Sparta Systems to develop artificial intelligence (AI) based solutions to detect risks early in the pharmaceutical manufacturing process. The goal is to come up with solutions that can help reduce product quality impact, and enable near-real-time product release.

Getting a handle on quality output during the manufacturing of pharmaceutical products is crucial to drug companies and their production partners. However, because quality cannot be fully controlled, the process relies on detection of and reaction to risk and problems to safeguard product quality.

Dana Jones, CEO of Sparta Systems, said the joint effort ultimately will provide users with “meaningful” insights and intelligence.

“The ability to not only capture but distribute the information to all levels and across all operating units empowers our customers to make faster and better decisions while assuring the quality of medical products and safety of patients and users,” she said.

Working with Quartic.ai’s AI and IoT Platform, Sparta’s TrackWise and TrackWise Digital will collect production equipment data during development, in order to create and ‘train’ algorithms that detect product and process anomalies. Once the product is completely developed and given the go-ahead for commercial distributions, users reportedly will be able to deploy these algorithms to pinpoint performance anomalies before time and materials are wasted on noncomforming product.

In the event performance ‘drift’ is detected, the two platforms working together will create a a record, pair it and provide operators with development insights, and deliver instructions on correcting issues. The process is designed to avoid issues and under-informed production decisions.

Rajiv Anand, Quartic.ai CEO, said the collaboration will harness the integrated sensors of processing and manufacturing equipment, and use AI and machine-learning tools to prevent deviations.

“The ultimate goal is to be certain that all critical parameters are met, that we capture process and human knowledge, and that we are certain product coming off the line is not just ok, but perfect - the absolute highest quality,” Anand explained.