AI-Supported Process Development & Flow Chemistry

Accelerating Innovation in Chemical Manufacturing

AI-supported process development will drive the advancement of more efficient chemical processes. Improved processes result in reduced work-up and waste. AI will contribute by enabling partially autonomous experimentation and suggesting optimal starting points. Technology selection will also be AI-assisted. Enhanced processes provide a cost advantage. Additionally, new chemical transformations will be unlocked through flow chemistry, enabling strategies that are impossible in batch processing, with a significant impact on waste reduction.

Speed will become the dominant business driver, surpassing quality and cost as the primary factor. This shift will open new strategic approaches. In the future, pharmaceutical companies may no longer own technologies or production plants. Instead, they might rent technologies and equipment to enter the market as quickly as possible, ensuring they are the first to meet a specific demand. Modularity and flexible automation – enabled by concepts like the Module Type Package (MTP) – will be critical for accelerating production. MTP facilitates the seamless integration of different process modules, much like USB technology for computers. In this evolving landscape, the best solution will not necessarily be the one that prevails; rather, the fastest solution to meet demand will take precedence. AI will significantly reduce development times, accelerating time to market.

Furthermore, telescoping, which connects synthesis steps without intermediate work-up, can dramatically reduce manufacturing times. This approach can sometimes be financially justified by lowering working capital requirements.

Comprehensive data measurement and process data storage will be the foundation for future advancements. Historically, many processes have been developed and then left unchanged. However, process industries will increasingly recognize that process knowledge is a core competency, strengthened by a data-driven approach. The more process data is available, the more effectively AI can support operations and recommend improvements. As a result, data management and analysis will become critical to competitiveness. Continuous learning and process optimization will be key drivers of long-term success.

Dr. Dirk Kirschneck, Strategic Director at Microinnova, will join Dr. Daniel Heinrich (Axplora) and Martin Bindl (Evonik) for a dynamic panel discussion moderated by Roger LaForce (Dorra Europe) at Chemspec Europe. The roundtable, titled “AI and ESG: Shaping the Future of Sustainable Global Supply Chains” and hosted by TKS, will explore how emerging technologies and environmental, social, and governance principles are transforming the supply chain landscape. Dr. Kirschneck looks forward to contributing his insights and expertise to this forward-thinking conversation.