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28 Pharmaceutical Technology ® Trends in Manufacturing eBook May 2023 PharmTech.com WRIGHTSTUDIO - STOCK.ADOBE.COM P harmaceutical manufacturing equipment companies and technology providers are ex- ploring how artificial intelligence (AI) can benefit process control systems. Two Italian companies—pharmaceutical machinery manufac- turer Luperini and technology start-up Eigengran— partnered to launch AI-enabled equipment for oral solid dosage drugs that they have called Cognitive Pharma Machinery. Luperini signed a licensing agreement to use Eigen- gran's cognitive control technology in December 2022, following 18 months of testing and development. The initial work focused on high-shear wet-granulation (HSWG). In one-pot HSWG equipment, such as that made by Luperini, the entire granulation process, in- cluding the drying step, is performed within one unit. This set-up was well-suited for the initial project of developing a cognitive control system using process analytical technology (PAT) sensors to monitor the progression of the granulation process over time. "Ou r tech nolog y is a key element i n t he appl i- cation of PAT guidelines for oral drug production and will be a key step towards achieving Pharma 4.0 practice in the pharmaceutical manufacturing process," said Marco Luperini, chief technology of- ficer of Luperini, in an announcement of the tech- nology (1). Luperini's new test center in Chiesina Uz- zanese, Italy houses pilot machines for evaluation to simulate conditions that may be encountered in real-world scenarios. Building predictive control models Eigengran says that controlling the granulation pro- cess to achieve a target granule size is complex be- cause it depends on the properties of the solids, liquid binder, and the interface between them as well as the forces applied to the particles (2). These dynamic sys- tems, however, have patterns that can be exploited by new capabilities in AI algorithms and sensors, says Carolina Gastone, Eigengran's CEO. AI Algorithms Find Use in Pharma Equipment Jennifer Markarian is manufacturing reporter for Pharmaceutical Technology ® . Machine learning provides real-time data for process control of high-shear wet granulation.