Perhaps we are currently witnessing Amara’s Law play out in real time when it comes to artificial intelligence: “We tend to overestimate the short-term impact of a new technology and underestimate its long-term consequences.” AI has long since ceased to be merely the subject of scientific research. It has entered practical application and is beginning to fundamentally transform research, methods, and ways of working in nearly all scientific disciplines.
For the Center for Pharmaceutical Process Engineering (PVZ) at the Technical University of Braunschweig, this raises a central question: How can we combine artificial intelligence and digital methods with an understanding of scientific processes in a way that creates tangible added value for the development and manufacture of pharmaceuticals? Scientists at the PVZ are exploring this question and translating these new technological possibilities into concrete applications for pharmaceutical research and production.
One example is the work of Prof. Dr.-Ing. Carsten Schilde and his team. As an article in the AI special issue of the Braunschweig-based magazine Stadtglanz shows, the PVZ combines artificial intelligence, process simulations, and data-driven models with established scientific process knowledge. Such hybrid approaches can help to better understand complex manufacturing processes, identify critical product properties, and detect potential quality deviations at an early stage. The range of applications extends from algorithmically supported experimental design and self-driving labs (SDLs) to agent-driven systems that continuously map and monitor real-world development and manufacturing processes.
The goal is not to replace scientific expertise with AI. Rather, the combination of AI, data, and in-depth process understanding is intended to help generate new knowledge and make more informed decisions.
The PVZ aims to actively shape this development. In the coming years, the PVZ will therefore systematically expand collaborations with industry, non-university research institutions, clinical partners, and international universities. In this way, AI will become more than just a technological trend; it will serve as a tool for more efficient, robust, and responsible drug development and manufacturing.