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Host cell proteins (HCP) that co‐purify with biologics produced in Chinese hamster ovary cells have been shown to impact product quality through proteolytic degradation of recombinant proteins, leading to potential product losses. Several problematic HCPs can remain in the final product even after extensive purification. Each recombinant cell line has a unique HCP profile that can be determined by numerous upstream and downstream factors, including clonal variation and the protein sequence of the expressed therapeutic molecule. Here, we worked with recombinant cell lines with high levels of copurifying HCPs, and showed that in those cell lines even modest downregulation (≤50%) of the difficult to remove HCP Cathepsin D, through stable short hairpin RNA interference or monoallelic deletion of the target gene using CRISPR‐Cas9, is sufficient to greatly reduce levels of co‐purifying HCP as measured by high throughput targeted LC‐MS. This reduction led to improved product quality by reducing fragmentation of the drug product in forced degradation studies to negligible levels. We also show the potential of cell engineering to target other undesired HCPs and relieve the burden on downstream purification.

Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first “Highland Games” competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development‐related properties of six antibodies from their amino acid sequences alone. Predictions included purification‐influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all‐prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in‐house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.

In recent years, mRNA-based therapeutics have been a fast-growing new class of biologics that can, in principle, encode any protein(s) directly in patients to treat various diseases. mRNA vaccines have been proven to work efficiently, have high potency, and can be rapidly developed and deployed, which is critical for a quick responses in the case of a pandemic. Such agile development is enabled by rapid synthesis of RNA in vitro using recombinant enzymes rather than relying on lengthy and complex cell culture processes. mRNA exhibits physical and chemical properties differing from protein-based therapeutics. It is highly negatively charged and the hydroxyl group makes mRNA less stable and more susceptible to hydrolysis and nucleophilic cleavage. This novel work shares comprehensive studies carried out to compare the performance of various mRNA purification strategies by considering its scalability and critical quality attributes. In addition, the paper provides insights on how to establish a scalable mRNA purification process that consists of ultrafiltration/ diafiltration and chromatography steps with good recoveries. Alternative Oligo(dT) based columns were further explored aiming to improve total process recovery. With Oligo(dT) as a capture step, overall recoveries of 70% can be achieved for mRNAs studied here that encode anti-influenza immunoglobulin G monoclonal antibodies.