Bioprocessing in the Digital Age: The Role of Process Models. Issue 1 (23rd September 2019) - Narayanan, Harini; Luna, Martin F.; von Stosch, Moritz; Cruz Bournazou, Mariano Nicolas; Polotti, Gianmarco; Morbidelli, Massimo; Butté, Alessandro; Sokolov, Michael
Abstract: In this age of technology, the vision of manufacturing industries built of smart factories is not a farfetched future. As a prerequisite for Industry 4.0, industrial sectors are moving towards digitalization and automation. Despite its tremendous growth reaching a sales value of worth 188 billion in 2017, the biopharmaceutical sector distinctly lags in this transition. Currently, the challenges are innovative market disruptions such as personalized medicine as well as increasing commercial pressure for faster and cheaper product manufacturing. Improvements in digitalization and data analytics have been identified as key strategic activities for the next years to face these challenges. Alongside, there is an emphasis by the regulatory authorities on the use of advanced technologies, proclaimed through initiatives such as Quality by Design (QbD) and Process Analytical Technology (PAT). In the manufacturing sector, the biopharmaceutical domain features some of the most complex and least understood processes. Thereby, process models that can transform process data into more valuable information, guide decision‐making, and support the creation of digital and automated technologies are key enablers. This review summarizes the current state of model‐based methods in different bioprocess related applications and presents the corresponding future vision for the biopharmaceutical industry to achieve the goals of Industry 4.0 while meeting the regulatory requirements. Abstract : The era of digitalization has paved way to the fourth industrial revolution in various sectors including the Pharma 4.0 initiative of the bioprocess industries. The review sheds light on process models being one of the key enablers for this digital transformation. It presents a perspective on the current modeling techniques, their future improvement, and the opportunities it brings to digitalization while simultaneously fulfilling the regulatory norms.