Report Title: Towards an Advanced Manufacturing System: Continuous Manufacturing, Process Engineering, and Artificial Intelligence for Fine Chemicals

Presenter: Dr. Huang Xinlei

Venue: Conference Room 601, Building A, Shantou Laboratory

Report Time: Monday, March 30,2026,10:00

Report Summary: As China's chemical and fine chemical industries enter a critical phase of transitioning from being a "large chemical nation" to a "strong chemical nation," the strategic national development priorities of "high quality, green development, safety, and intelligence" have been explicitly established. In Europe and North America, Advanced Manufacturing Technology (AMT) is profoundly reshaping the pharmaceutical and fine chemical industries; its successful implementation relies on robust process engineering strategies to overcome core challenges in scale-up and technology transfer. Among these strategies, continuous manufacturing has emerged as a pivotal breakthrough point, offering significant advantages over conventional batch processes in terms of product quality, safety, and sustainability; meanwhile, the deep integration of artificial intelligence (AI) is further accelerating this industrial transformation. Various AI-driven approaches—including data-driven optimization, hybrid models, predictive control, and generative AI systems tailored for industrial knowledge management—are continuously enhancing process understanding, decision-making rigor, and overall production efficiency. This report focuses on the latest advancements in international continuous manufacturing platforms, outlines practical process optimization strategies across all production stages—from laboratory and kilogram-scale to pilot and commercial production—and briefly discusses process scale-up methodologies, determination of key engineering parameters, essential considerations for process design, and emerging technological trends in continuous manufacturing. Furthermore, drawing on experience in process safety assessment, process risk identification, and engineering-scale up, this report analyzes critical engineering challenges associated with continuous processes, including heat and mass transfer, residence time control, and reaction safety. Supported by real-world industry cases, the report demonstrates how AI can be integrated with fundamental chemical engineering principles to facilitate process optimization, scale-up decision-making, and safety assessments, thereby fostering a production ecosystem characterized by greater resilience and flexibility. By integrating three key domains—continuous manufacturing, process engineering, and artificial intelligence—this report provides a forward-looking perspective to demonstrate how AMT can facilitate the realization of an advanced manufacturing paradigm that is safer, more robust, cost-optimized, highly efficient, rapid, and environmentally friendly.

Speaker Biography：

Huang Xinlei holds a Ph.D. in Chemical Engineering. He earned his bachelor's degree from Central China Normal University, where he obtained dual degrees in Chemistry and English. He then pursued his Ph.D. at Syracuse University in the United States, focusing his research on biomass conversion and reaction engineering. After completing his Ph.D., he conducted postdoctoral research at the University of Delaware, collaborating with DuPont/Chemours to optimize hazardous processes. Following his postdoctoral tenure, he joined CONTINUUS Pharmaceuticals—a continuous manufacturing startup incubated by Novartis and MIT—where he engages in research and development of advanced manufacturing technologies and continuous processes. Prior to returning to China, he served as a Senior Process Engineer at the U.S. production site of Pharmaron, where he was fully responsible for the end-to-end process management of active pharmaceutical ingredients (APIs), encompassing process development, scale-up, technology transfer, as well as continuous/flow process design, process safety assessment, and model-assisted optimization. His expertise spans continuous manufacturing, reaction engineering, process engineering, and process safety. Upon his return to China, he joined the Research Institute of China National Chemical Engineering Group, where he is actively exploring the application of advanced manufacturing equipment, artificial intelligence, and machine learning in process development and production manufacturing. His objectives are to enhance the efficiency and quality of process development, and to drive the manufacturing of APIs and chemical products toward greener, more efficient, and more sustainable pathways.

School of Chemistry and Chemical Engineering (School of Carbon Neutrality and Future Technologies)

March 29,2026