Biopharmaceutical Process Development

Biopharmaceutical process development aims to optimize the manufacturing of biological drugs like monoclonal antibodies, focusing on efficiency, yield, and product quality. Current research emphasizes the application of machine learning, particularly deep reinforcement learning and Bayesian optimization, to improve process control, reduce production time and costs, and enhance robustness against process variability, for example, by optimizing cell culture expansion strategies. These advancements promise significant improvements in the speed and cost-effectiveness of biopharmaceutical production, ultimately leading to more accessible and affordable therapies.