Developing cell culture processes at industrial scale is expensive. High-density or advanced culture systems can overcome these high costs but deliver inconsistent results, forming a bottleneck in the path to commercially manufacturing high-density cultures. New image analysis methods break that bottleneck.
For perspective, chemical polymerization plants have zero to one percent variability, but monoclonal antibody production has a 10% yield variability, Mark C. Allenby, PhD, senior lecturer in biomedical engineering, University of Queensland, says in a new study.
Most image analyses are still performed manually but, Allenby tells GEN, “Advances in 3D microscopy, image analysis, and bioreactor platforms, as well as recent developments in image analysis software, have allowed noninvasive, automatic analyses of cell and cell viability measurements, and complex algorithms are being developed to predict cell phenotype or health from brightfield morphology.”
For example, notes Allenby, “Imaging analyses can provide automated, quantitative subcellular (microscopy) to multicellular tissue (medical imaging) metrics that are noninvasive and that directly measure cell behavior without the need to sample medium or take indirect population-based supernatant measurements.”
Consequently, these methods enable greater control over fragile cell types or complex culture platforms. They can be applied to high-density/3D cultures as well as to low-density/liquid suspension bioreactors.
The need for improved analytics is driven by the need to produce ever larger quantities of expensive mammalian cellular products at lower prices, such as monoclonal antibodies, extracellular matrix proteins, adenoviral vectors, and emerging cell and tissue products.
The demand for greater manufacturing efficiencies is pushing companies to transition from liquid suspension to high-density culture systems such as hollow fiber bioreactors. These systems “allow more cells to be grown in smaller volumes of medium and reduce the major cost burden to industrial cell culture. But their greater complexity has made their adoption challenging across the past three decades,” according to Allenby. “It becomes difficult to control cell behavior or health and to maintain high cell or product quality and purity at the end of the process.”
To gain insights that enable high-density and 3D cell cultures to be optimized, Allenby recommends applying quantitative imaging analysis into the bioprocess modeling to capture the 3D complexity—such as spatial deviances—that supernatant analyses cannot capture.
As yet, “Integrating spatiotemporal image metrics into new high-density bioprocess models remains a challenge,” Allenby says, “but it is needed to develop better designed, scaled, optimized, and controlled high-density platforms.”
Simply put, robust imaging analyses will better enable advanced, high-efficiency bioreactors to translate to industrial scale for cell and gene therapies, mAbs, cellularized medical grafts, and other novel bioproducts.
