Traditionally, the Six Sigma framework has underpinned quality improvement and assurance in biopharmaceutical manufacturing process management. This paper proposes a neural network (NN) approach to vaccine yield classification and compares it to an existing multiple linear regression approach. As part of the Six Sigma process, this paper shows how a data mining framework can be used to extract further value and insight from the data gathered during the manufacturing process, and how insights into yield classification can be used in the quality improvement process.
BioProcessing Journal Posts
Plants must be capable of responding to climatic fluctuations, diurnal rhythms, available supplies of water and nutrients, and insect attacks and infestations. To ensure such responses, plants need a network of regulating substances called phytohormones. These substances enable plants to respond to both biotic and abiotic stresses by initiating a cascade of orchestrated actions, and to trigger development-specific processes. In this article, we will discuss a highly sensitive analytical method for quantitative determination of phytohormones. The main representatives of the plant hormones are jasmonic acid (JA), cytokines, auxins, abscisic acid, salicylic acid, gibberellins, and strigolactones.
Plaque assays have traditionally been a reliable way to determine the titer of a lytic virus. However, this method has several shortcomings in that it is time-consuming, labor intensive, and suffers from limited sensitivity. In this article, we describe a novel flow cytometry-based titration assay to quantify green fluorescent protein-labeled herpes simplex virus type 1 (HSV-1-GFP). Using this assay, we were able to directly quantify ten-fold dilutions of the virus in which every GFP-positive cell could be counted. In a head-to-head comparison with a traditional plaque assay, the flow cytometry assay showed a greater linear range and was accomplished in less than half the time of the plaque assay.
Antibody-dependent cellular phagocytosis (ADCP), which relies on macrophages to attack and devour tumor cells following antibody binding, is a potentially useful mechanism of action (MOA) for antibody drug developers and vaccine makers to consider in determining product efficacy. Unfortunately, it is often ignored in favor of more accessible MOAs driving biological function such as antibody-dependent cellular cytotoxicity (ADCC) because the assays are tedious to prepare, perform, and reproduce.
