Various living mechanisms have been used in bulk polymerization to produce via free radical polymerization both controlled polymers, i.e., with low polydispersity, and block copolymers. The common drawback of all these processes is the very low polymerization rate which derives from the decreased concentration of propagating radicals. This problem can be overcome in principle by operating in emulsion polymerization, so as to take advantage of radical segregation to decrease terminations without significantly reducing the polymerization rate with respect to the corresponding nonliving processes. In this work, it has been shown that this result can be achieved only using the RAFT (or degenerative transfer) living mechanism and operating in miniemulsion polymerization. Several experiments are presented where, using different monomers, living conditions are achieved without significant loss in productivity. The obtained results are supported by modeling arguments, which also rationalize previous experimental results reported in the literature using different living mechanisms.

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.

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