This review surveys recent applications of design‐of‐experiments (DoE) methodology in the development of biotechnological processes. Methods such as factorial design, response surface methodology, and (DoE) provide powerful and efficient ways to optimize cultivations and other unit operations and procedures using a reduced number of experiments. The multitude of interdependent parameters involved within a unit operation or between units in a bioprocess sequence may be substantially refined and improved by the use of such methods. Other bioprocess‐related applications include strain screening evaluation and cultivation media balancing. In view of the emerging regulatory demands on pharmaceutical manufacturing processes, exemplified by the process analytical technology (PAT) initiative of the United States Food and Drug Administration, the use of experimental design approaches to improve process development for safer and more reproducible production is becoming increasingly important. Here, these options are highlighted and discussed with a few selected examples from antibiotic fermentation, expanded bed optimization, virus vector transfection of insect cell cultivation, feed profile adaptation, embryonic stem cell expansion protocols, and mammalian cell harvesting.

The following report with recommendations is the result of an expert panel meeting on soft sensor applications in bioprocess engineering that was organized by the Measurement, Monitoring, Modelling and Control (M3C) Working Group of the European Federation of Biotechnology ‐ Section of Biochemical Engineering Science (ESBES). The aim of the panel was to provide an update on the present status of the subject and to identify critical needs and issues for the furthering of the successful development of soft sensor methods in bioprocess engineering research and for industrial applications, in particular with focus on biopharmaceutical applications. It concludes with a set of recommendations, which highlight current prospects for the extended use of soft sensors and those areas requiring development.

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Liver cell culture models are attractive in both tissue engineering and for development of assays for drug toxicology research. To retain liver specific cell functions, the use of adequate cell types and culture conditions, such as a 3D orientation of the cells and a proper supply of nutrients and oxygen, are critical. In this article, we show how extracellular matrix mimetic hydrogels can support hepatocyte viability and functionality in a perfused liver-on-a-chip device. A modular hydrogel system based on hyaluronan and poly(ethylene glycol) (HA-PEG), modified with cyclooctyne moieties for bioorthogonal strain-promoted alkyne-azide 1, 3-dipolar cycloaddition (SPAAC), was developed, characterized, and compared for cell compatibility to hydrogels based on agarose and alginate. Hepatoma cells (HepG2) formed spheroids with viable cells in all hydrogels with the highest expression of albumin and urea in alginate hydrogels. By including an excess of cyclooctyne in the HA backbone, azide-modified cell adhesion motifs (linear and cyclic RGD peptides) could be introduced in order to enhance viability and functionality of human induced pluripotent stem cell derived hepatocytes (hiPS-HEPs). In the HA-PEG hydrogels modified with cyclic RGD peptides hiPS-HEPs migrated and grew in 3D and showed an increased viability and higher albumin production compared to when cultured in the other hydrogels. This flexible SPAAC crosslinked hydrogel system enabled fabrication of perfused 3D cell culture of hiPS-HEPs and is a promising material for further development and optimization of liver-on-a-chip devices.

This review provides an overview and a critical discussion of novel possibilities of applying soft sensors for on-line monitoring and control of industrial bioprocesses. Focus is on bio-product formation in the upstream process but also the integration with other parts of the process is addressed. The term soft sensor is used for the combination of analytical hardware data (from sensors, analytical devices, instruments and actuators) with mathematical models that create new real-time information about the process. In particular, the review assesses these possibilities from an industrial perspective, including sensor performance, information value and production economy. The capabilities of existing analytical on-line techniques are scrutinized in view of their usefulness in soft sensor setups and in relation to typical needs in bioprocessing in general. The review concludes with specific recommendations for further development of soft sensors for the monitoring and control of upstream bioprocessing.