Application of machine learning methods to pathogen safety evaluation in biological manufacturing processes.

The production of recombinant therapeutic proteins from animal or human cell lines entails the risk of endogenous viral contamination from cell substrates and adventitious agents from raw materials and environment. One of the approaches to control such potential viral contamination is to ensure the manufacturing process can adequately clear the potential viral contaminants. Viral clearance for production of human monoclonal antibodies is achieved by dedicated unit operations, such as low pH inactivation, viral filtration, and chromatographic separation.

Femtomolar Fab binding affinities to a protein target by alternative CDR residue co-optimization strategies without phage or cell surface display.

In therapeutic or diagnostic antibody discovery, affinity maturation is frequently required to optimize binding properties. In some cases, achieving very high affinity is challenging using the display-based optimization technologies. Here we present an approach that begins with the creation and clonal, quantitative analysis of soluble Fab libraries with complete diversification in adjacent residue pairs encompassing every complementarity-determining region position.

A micro-scale process for high-throughput expression of cDNAs in the yeast Saccharomyces cerevisiae.

Methods have been developed aimed at applying at high-throughput technology for expression of cloned cDNAs in yeast. Yeast is a eukaryotic host, which produces soluble recombinant proteins and is capable of introducing post-translational modifications of protein. It is, thus, an appropriate expression system both for the routine expression of various cDNAs or protein domains and for the expression of proteins, which are not correctly expressed in Escherichia coli.