Summary
Dustin Sands is a Senior Process Modeler and biochemical engineer with 8 years of experience building digital twins, simulation frameworks, and ML-driven automation for bioprocessing across 2L–1000L bioreactors and GMP environments. He has led cross-functional projects at Ark Biotech and Takeda to optimize cultured meat and cell therapy processes, delivering measurable yield and operational improvements through in-silico CMC tools and predictive control. Equally comfortable coding in Python and C as he is developing assays (photospectrometry, Raman), he bridges wet-lab insight and software engineering to turn experimental data into deployable models. His work spans technoeconomic analysis, process selection (fed-batch vs perfusion), and state-based probabilistic methods — with side interests in encryption and blockchain concepts applied to secure data workflows. Based in Cambridge, MA, he maintains an active portfolio of upstream cell culture simulators and ML research that underscore a practical, research-forward approach to bioprocess digitalization.
8 years of coding experience
4 years of employment as a software developer
University College London