Michael Sokolov
Papers
3
Total Citations
48
H-Index
2
About
Michael Sokolov is a leading figure in the digital transformation of bioprocess development, specializing in high-throughput automation, online monitoring, and machine learning for biomanufacturing. His work centers on accelerating the transition from strain screening to robust production processes, particularly for therapeutic proteins like monoclonal antibodies. Sokolov’s major contributions include pioneering the use of mini-bioreactor platforms for multivariate prediction, as demonstrated in his highly cited 2018 work on endopolygalacturonase production with *Saccharomyces cerevisiae* (28 citations). He further advanced the field by integrating online multivariate analysis with robotic cultivation systems (2020, 18 citations), enabling real-time, data-rich decision-making during microbial screening. Most notably, his 2024 paper on self-driving development of perfusion processes (2 citations) represents a cutting-edge leap toward autonomous bioprocessing, where AI agents orchestrate experiments to optimize yields with minimal human intervention. With a growing citation impact, Sokolov’s work is instrumental in reducing the time and cost of biopharmaceutical innovation, making him a key contributor to the next generation of smart, automated biomanufacturing.
Research Focus
Key Achievements
Top Papers
- 1
- 2Monitoring Parallel Robotic Cultivations with Online Multivariate Analysis18 citations · 2020
- 3