Daniel Griffin

Dan Griffin is a Chemical Engineer at Amgen in the Pivotal and Commercial Process Development Group for Synthetic Drug Substance. Prior to joining Amgen in 2016, Dan earned a PhD in Chemical Engineering from Georgia Tech, where he conducted research on salt crystallization from nuclear waste and became interested in combining online process monitoring and automation tools with learning algorithms to understand and control complex processes. Continuing that pursuit, Dan has led a number of initiatives within Synthetics Process Development group at Amgen that are aimed at combining automation with learning-from-data strategies to enable accelerated process development—the topic of today’s talk stemmed from work on those initiatives.