The genetic sequence of the Chinese hamster ovary (CHO) cell line first was published just over a decade ago. As with the Human Genome Project, genomic knowledge of that and other biopharmaceutical production cell lines — both animal and microbial — has expanded greatly alongside dramatic increases in computing power. Meanwhile new and improved genetic engineering techniques have offered the potential for targeted rather than random integration of transgenes into production cells. And regulators began to emphasize monoclonality more, demanding evidence that cell banks are derived from single engineered cells. All the while, cell-line development groups faced increasing pressure to shorten timelines associated with their workflows. Authors in this month’s featured report highlight strategies that are taking biopharmaceutical production to new levels.

Introduction: Cell-Line Development Discussion at Biotech Week Boston
by Brian Gazaille and Cheryl Scott
As presentations at recent BPI conferences have revealed, “big data,” next-generation sequencing (NGS), automation, and powerful analytical technologies are helping biopharmaceutical companies achieve parallel goals of shortening timelines while meeting regulatory expectations. And despite the widespread popularity of certain instruments, the talks at Biotech Week Boston (BWB) and the BPI Conference US West (BPI West) demonstrated that there is no one way to do so. Combining some of the approaches mentioned herein just might take biopharmaceutical production to new levels that not long ago would have been deemed impossible. Here we highlight discussions at BWB. (Look for more in our BPI West postevent report later this year.) Highlighted topics include transgene integration, clonality, and accelerating cell-line development.

Cell Lines Are the Foundation: A Methodical Approach to Derisking Outsourced
Development and Improving Manufacturability of Novel Biologics
by Jason Condon
Selection of a cell line and development of an early manufacturing process are critical steps in biologics development. So it is a worthwhile endeavor to make a plan for doing so and begin with a contract manufacturing partner that can provide the expression titers and yields necessary for a biomanufacturing process that can be used across all phases of clinical development and even into early commercial supply. Programs are derisked by preventing the need for late-stage process development overhauls or changes in cell line and/or manufacturing process technology. Here, Cue Biopharma’s director of drug-substance technical operations presents a decision-making strategy that puts cell-line development first to set up early process development and prepare for manufacturability and scalability assessments with financial/timeline considerations in mind.

Targeting RNA: How Epitranscriptomics Can Improve Productivity
by Cheryl Scott, with Niall Barron
Cell-line development traditionally has focused on genetic engineering of chromosomal DNA in cellular nuclei. Few researchers have considered the potential for manipulating how genes are transcribed as an avenue for increasing productivity — until recently. Niall Barron is a professor of biochemical engineering at Ireland’s National Institute for Bioprocessing Research and Training (NIBRT) and at University College Dublin. He presented at two BPI conferences in 2022 on the potential for using epigenetics in biopharmaceutical production cell-line development. Here BPI’s senior technical editor discusses what his laboratory is learning about mRNA methylation in production cell lines and therapeutic cells — and how the science could be applied technologically.

Quantitative Synthetic Biology for Biologics Production
by Haewon Chung, Dinghai Zheng, Brianna Jayanthi, Alina Ferdman, Georgian Tutuianu, Jeremy J. Gam, Kevin D. Smith, Niko McCarty, Raja Srinivas, and Alec A.K. Nielsen
Multiple areas of cell-line development have improved over the years, but advances in expression vector design have lagged behind other technologies. Most expression vectors still rely on a “one-size-fits-all” approach that can provide suboptimal expression. Here, Asimov authors introduce the CHO Edge system, which builds on the current state of the art by integrating expanded genetic tools with data-driven models, including a proprietary hyperactive transposase for genomic integration, a library of more than 2,500 characterized genetic elements, and computer-aided design software for vector design and simulation. The integrated system routinely achieves titers of 5–10 g/L across modalities in a four-month timeline, and it can be licensed or engaged as development service.