Division/Committee: [BIOT] Division of Biochemical Technology

The development and commercialization of biotherapeutics depends on successful upstream process development to identify the ideal protein candidates and its final cell line for commercial production, as well as cell culture media, bioreactor process conditions, and process control/monitoring. Enhancements in laboratory automation, DNA synthesis, and synthetic biology have led to rapid advances in the throughput and approaches taken in upstream process development. The application of technologies such as cell-free expression, microfluidics, and automated bioreactors has enabled the rapid design and testing of increasingly large numbers of protein candidates and production conditions in reasonable timelines. Advances in machine learning and other computational methods are being implemented on the multidimensional data sets generated during high-throughput upstream process development to drive process decision-making and generate cross-program learnings. This session will focus on developing and applying experimental and computational tools, workflows, and processes that increase our ability to perform therapeutic candidate development in a high-throughput, automated fashion. This session will explore advances in functional artificial intelligence-based algorithms for accurate sampling of property landscape, analytical characterization, and the rational design of biological materials and functions. Finally, this session will foster discussion on the use of community standards and initiatives to improve these processes as new ways to distribute and share data across the community.

Thomas Mansell Ph.D.

Assistant Professor, Iowa State University

Appearances