Webinar Description:

Recombinant protein expression is influenced by a variety of variables associated with the choice of codons used for synthetic production. A case study is presented comparing various codon design strategies, including predictive machine-learning algorithms based on Design-of-Experiment data sets. The impact of these designs on the production of Virus Like Particles ln Nicotania Benthamiana is presented.

Learning Objectives:

Recombinant protein expression, codon optimization.

Speakers:

Pierre-Olivier Lavoie
Director of Platform Discoveries
Medicago

Pierre-Olivier Lavoie is the Director of Platform Discoveries at Medicago (Canada) where he works on expression technologies in plants. He has contributed to put in place Medicago’s VLPExpress high throughput discovery platform used for the development of plant-made Influenza, Rotavirus and Norovirus vaccines and various proprietary expression elements.

Mark Welch, Ph. D.
Vice President of Research & Development
ATUM

Dr. Mark Welch has been with ATUM since 2006. At ATUM, Dr. Welch developed the GeneGPS machine-learning technology for experiment-driven gene expression optimization. He currently oversees gene, protein, vector and strain engineering contracts for customers as well as new technology development. Prior to work at ATUM, Dr. Welch held positions at Applied Biosystems and at Maxygen, Inc. Dr. Welch received his Ph.D. at the University of Colorado at Boulder.

Cost: No Cost!