Global Optimization and Active Learning

Operating biopharmaceutical manufacturing processes at optimal conditions is critical to maximize productivity and product quality, while minimizing manufacturing cost and environmental impact. Therefore, employing efficient and effective optimization strategies is essential. These span from simple ones like one-factor-at-a-time, which assess the influence of process variables in isolation, to more advanced ones such as Design of Experiments (DoE) or Gaussian Process-based (GP) optimization, which also account for variable interactions.