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Small‐scale protein purification presents opportunities for accelerated process development of biotherapeutic molecules. Miniaturization of purification conditions reduces time and allows for parallel processing of samples, thus offering increased statistical significance and greater breadth of variables. The ability of the miniaturized platform to be predictive of larger scale purification schemes is of critical importance. The PerkinElmer JANUS BioTx Pro and Pro‐Plus workstations were developed as intuitive, flexible, and automated devices capable of performing parallel small‐scale analytical protein purification. Preprogrammed methods automate a variety of commercially available ion exchange and affinity chromatography solutions, including miniaturized chromatography columns, resin‐packed pipette tips, and resin‐filled microtiter vacuum filtration plates. Here, we present a comparison of microscale chromatography versus standard fast protein LC (FPLC) methods for process optimization. In this study, we evaluated the capabilities of the JANUS BioTx Pro‐Plus robotic platform for miniaturized chromatographic purification of proteins with the GE ӒKTA Express system. We were able to demonstrate predictive analysis similar to that of larger scale purification platforms, while offering advantages in speed and number of samples processed. This approach is predictive of scale‐up conditions, resulting in shorter biotherapeutic development cycles and less consumed material than traditional FPLC methods, thus reducing time‐to‐market from discovery to manufacturing.

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Graph rewriting has been used extensively to model the behaviour of concurrent systems and to provide a formal semantics for them. In this paper, we investigate processes for Local Action Systems (LAS); LAS generalize several types of graph rewriting based on node replacement and embedding. An important difference between processes for Local Action Systems and the process notions that have been introduced for other systems, for example, Petri nets, is the presence of a component describing the embedding mechanism. The aim of the paper is to develop a methodology for dealing with this embedding mechanism: we introduce a suitable representation (a dynamic structure) for it, and then investigate the algebraic properties of this representation. This leads to a simple characterization of the configurations of a process and to a number of equational laws for dynamic structures. We illustrate the use of these laws by providing an equational proof of one of the basic results for LAS processes, namely that the construction yielding the result graph of a process behaves well with respect to the sequential composition of processes.