The pharmaceutical industry is increasingly utilizing mechanistic and hybrid computational modeling and simulation in process development and engineering to accelerate timelines, assess and mitigate risks, and support scale-up/tech transfer. The corresponding proportion of scientific evidence supporting regulatory applications derived from modeling and simulation studies is expected to continue to grow in the future. More recently, the advent of Industry 4.0 has spread to the pharmaceutical industry, leading to a rise in digitalization efforts to modernize pharmaceutical manufacturing operations. Along with the increasing availability of digital technologies, this trend has inspired applications of physical science-based digital twins in pharmaceutical operations for real-time process optimization, operator training, soft sensing, and advanced monitoring. Given these developments, an increasingly important question is how to justify the quality of the underlying models. In this talk, highlights of recent applications of these technologies across the pharmaceutical and biopharmaceutical process lifecycle will be presented. We will then discuss the key credibility factors, prerequisites, and associated evidence that can be provided to justify model quality.
This presentation will present highlights of recent applications of mechanistic and hybrid computational modeling and simulation in pharmaceutical and biopharmaceutical process development, engineering, and manufacture, before considering the importance of model quality and how can it be justified.