Pharmaceutical research is constantly looking into unmet medical needs and addressing them with new, more active and specific molecules that bring greater value to patients. To do this; the molecular structures of active pharmaceutical ingredients (API) are becoming much more complex while development timelines drastically shorten within a very dynamic landscape with stronger regulatory requirements and focus on cost. This requires a transformation of chemical process R&D both in the chemical development labs and the plants and opens an opportunity for AI to reshape the way chemical processes are developed, transferred from labs to plants and how these plants are operated.
Within the J&J chemical pilot plants; a self-optimizing; autonomous process digital twin was developed to predict the scale up of a chemical process step from lab to plant, optimize this step during live production and autonomously – without any human in the loop – run this chemical process in the most optimal way. This industry-first case study is the equivalence of the self-driving car and opens the door to rethink the chemical process development & production paradigm within pharmaceutical industry.
