A deep learning tool and service for next-generation
antibody humanization

Antibody humanization is a critical step in the development of a therapeutic antibody drug candidate. Traditional humanization methods and publicly available online tools, such as BioPhi, have quality and throughput limitations. Genovac’s humanization solution, powered by ENPICOM, uses next-generation generative deep learning-based algorithms to humanize antibodies with very high success rates and enables identification of one-to-many humanized candidate antibodies with significant savings in cost and time.

20th Annual PEGS Boston Conference and Expo.
Genovac and ENPICOM speakers at PEGS 2024.

Pete Leland, Genovac

Prior to joining Genovac, Pete was a principal scientist for downstream process development at Catalent, Madison, Wis. Before that he was a proposal manager at Patheon, a division of Thermos Fisher Scientific, in Princeton, N.J., and the senior manager of technical operations in the Madison, Wis., Protein Division of Fargo-based Aldevron. Pete holds a Bachelor of Arts in chemistry from St. Olaf College, Northfield, Minn., and a doctorate in biochemistry from the University of Wisconsin-Madison.

Nicola Bonzanni, ENPICOM

As the Chief Product Officer at ENPICOM, Dr. Bonzanni leverages his expertise in science and technology to bridge the gap between life sciences, software engineering, and data visualization. He oversees a team of bioinformaticians, computational immunologists, scientific project managers, and product managers to deliver cutting-edge computational software solutions for life scientists.