Glycosylation is one of the most common post-translational modifications in mammalian-expressed biologics, and is considered to be a critical quality attribute of therapeutic glycoproteins. Due to its biological relevance, physiochemical assessment on the glycosylation profile is always important to the success of a drug development initiative. This article describes the combination of experimental design and machine learning techniques applied to characterize and optimize a conventional, non-derivatized glycoprofiling method on glycans derived from a human immunoglobulin using high-performance anion exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Two independent experimental designs, a 16-run definitive screening design (DSD) and a 28-run central composite design (CCD), were incorporated with a machine learning technique known as “self-validating ensemble modeling (SVEM)” and used to build predictive models for four chromatographic responses. We show that the predictive models created using SVEM on the DSD data reliably predicted the behavior of the chosen responses when applied to CCD validation data. This demonstrates that the DSD is an efficient alternative to the larger, traditional CCD in which the combination of experimental design and machine learning can effectively characterize and optimize analytical methods.
Tag: <span>design of experiment</span>
A rapid increase in the number of gene therapy trials and products has led to a comparable increase in the need for industrial production of viral gene therapy vectors such as lentiviral, adeno-associated, and adenoviral vectors. Current production systems are limited with respect to scalability and robustness. With our CAP® and CAP-T™ cell lines, we have developed a novel system for high-density suspension culture, efficient and reproducible transfection, and highly efficient production of viral vectors. By upstream process optimization, we have obtained a robust and high-density fed-batch culture system which can be scaled in any current bioreactor format. A design-of-experiments approach has been employed to optimize transient production of lentiviral vectors with significantly higher titers than can be obtained with adherent HEK293T cells…
Mass transfer is one of the most crucial parameters during scale-up in cell culture, and may cause variations in specific yields. At the cellular level, all the cells require proper supplementation of essential nutrient sources: nitrogen, oxygen, and carbon. The ability of cells to grow, maintain viability, and provide high specific productivity depends on the proper distribution of these nutrients. The latter depends on proper mass transfer to supply oxygen, carbon, and nitrogen through agitation and aeration, along with other micronutrients…