Hybrid modeling has proven to be a cost-effective and time-saving approach for process modeling, driving advancements in model-based process development across the biopharmaceutical industry. By combining mechanistic and data-driven modeling techniques, hybrid models offer a robust framework for improving process efficiency and scalability. In this work, we demonstrate how hybrid models can accelerate the development of key bioprocesses, including upstream processes for cell and gene therapies, and the in vitro transcription (IVT) process. These case studies illustrate the versatility of hybrid modeling in optimizing complex processes, reducing development timelines, and enhancing overall process performance.
