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Feb 1, 2011 (Vol. 31, No. 3)

Tips on How to Make Good Cells Better

Cell-Line Optimization Takes Many Forms, and Each Approach Has Its Adherents

  • Conserving Resources

    Like most large companies with multiple pipeline and marketed biologicals, Genentech employs platform CHO cells to produce most of its materials for toxicology and early clinical trials. Optimization occurs only for projects that have passed developmental milestones. “Since we do not know the long-term success of any individual project, we minimize our investment in the early phases and avoid optimization unless either production levels are insufficient or undesirable product quality attributes are detected,” says John Joly, Ph.D., a scientist at the company. Cells targeted for additional development are typically about to enter Phase III studies. Cells and processes emerging from these efforts are carried through for commercial supply.

    “A highly productive cell culture process depends greatly on the cell line, media, and process,” Dr. Joly notes. “This means starting with a host cell line that is highly conducive to generating high-yielding cell lines, screening to distinguish good from poor producers, designing experiments that will accurately reflect success at larger scale. Predictive scale-down models of our bioreactors early in the screening process has led to many successful cell culture processes at Genentech.”

    Dr. Joly’s group relies on gene transfection and amplification techniques to produce high-yielding cell lines, clone-screening to select the best-performing lines, and media development to understand the impact of nutrients on yield improvement and product quality.

    “We include design of experiment (DOE) for much of our work, whether it’s done at high, moderate, or low throughput. Given the rich history of producing biopharmaceuticals from CHO cells at Genentech, we are able to build upon what we learned during past projects.”

    While Genentech hedges its bets during early development, the possibility that these cells may one day be called upon for full-scale production is always within view. Its scientists closely examine early-stage productivity, compare it with anticipated future demands, and determine if changes will be needed for either the cell line or process. “We then make rational choices about how much effort in cell line and process development are warranted.”

  • Ultimate Downstream Biomarkers

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    Metabolon interprets cellular metabolism changes to enhance process optimization from clone selection to manufacturing.

    Numerous points of investigation, or intervention, are possible during cell-line development. DNA, RNA, and proteins are traditional places where developers look. Increasingly they also consider the metabolome—the t300–400 significant small molecule metabolites representing the downstream products of cellular activity.

    Metabolon provides fee-for-service around its core technology, which uses conventional analysis tools (HPLC and mass spectrometry) to profile all small molecules in a sample. Metabolomics has been a hot research area in biology and medicine; now it is proving its mettle as a service to support biomanufacturing as well.

    Metabolon conducted its first such study three years ago. In 2010 bioprocess-related work accounted for one-fourth of the firm’s 320 projects, says Mike Milburn, Ph.D., CSO.

    “Our bioprocessing-related work focuses on helping companies pick which cell lines to investigate further,” Dr. Milburn says. Selecting the right cells, or rejecting the wrong ones, has a profound influence on manufacturing, bioprocessing, and product quality. Metabolomics, according to Dr. Milburn, provides greater insight into the “black box” of production cells, and affords bioprocessors an alternative to the “pure numbers game of high-throughput screening of culture conditions and many, many clones.”

    A typical metabolomic project profiles all relevant metabolites and their concentrations, both inside cells and in the culture medium, over the course of a cell culture run. Intracellular analysis provides a “fingerprint” of cellular activity, and might lead to hypotheses about pathway activation or inactivation, either of which may be beneficial or detrimental to the process or affect product quality. These ideas are then confirmed (or not) by fingerprinting the medium for the extracellular counterparts of the same metabolites, as well as others. “We look for compounds in the medium that are limiting, which if added back might improve the process,” says Dr. Milburn.

    Alternatively, one could identify a product outside the cell that suggests that key nutrients are being shunted to a suboptimal metabolic pathway. For example, one recent study showed that cells were producing too much sorbitol, a metabolite indicating that glucose is undergoing suboptimal metabolism. Sorbitol is expressed at high levels, for example, in cells undergoing apoptosis. “This was a clear indication that these cells were not as metabolically healthy in this medium as they should have been. In this situation, the study indicated clones that the sponsor should probably have avoided.”

    Using metabolic biomarkers of cell suitability has other advantages as well. During early development cells are usually grown in rich media, where they appear to thrive and produce. “But that doesn’t mean the cell is healthy, or will be as robust in production media. The right biomarker can help processors triage out unhealthy cells very early on.”

    Unlike genomic or proteomic cell line analysis, metabolomics is rapid and easily testable. Developers can add or remove ingredients, or change conditions, and test the changes over the course of several days. “It’s much more difficult, after making a genetic change, to know if it will directly affect the process or product.”

    This is one reason why media and feed companies are so interested in metabolomics. As processing evolves toward more chemically defined media, the study of small molecules becomes indispensible for replacing vital nutrients and eliminating those that do not contribute to productivity.

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