Massimo Morbidelli received his Laurea in Chemical Engineering at the Politecnico di Milano and PhD at the University of Notre Dame. He is currently Professor Emeritus at the Politecnico di Milano (Italy) and Professor Emeritus at the ETH Zurich (Switzerland).
His main research interest is in the area of biopharmaceutics and specifically on the integrated continuous manufacturing of therapeutic proteins, and its automation and digitalization.
Massimo Morbidelli is co-author of more than 750 papers, 23 international patents and six books, including the recent ones on Continuous Biopharmaceutical Processes (2018), Cambridge University Press, coauthored with D. Pfister and L. Nicoud and Perfusion Cell Culture Processes for Biopharmaceuticals (2020), Cambridge University Press, coauthored with M. Wolf and J.-M. Bielser. He is the first chemical engineer elected to the Italian Academy of Science (Accademia dei Lincei), is a member of the Italian Academy of Engineering and Technology, serves as the Executive Editor of the ACS journal of Industrial & Engineering Chemistry Research, and is the recipient of:
- R.H. Wilhelm Award in Chemical Reaction Engineering by the American Institute of Chemical Engineers, 2005
- Gerhard Damk�hler-Medaille of DECHEMA.and VDI-GVC, 2014
- Excellence in Process Development Research Award by the American Institute of Chemical Engineers, 2017
- Separations Science and Technology Award by the American Chemical Society, 2018
- ICB Award, Contributions to Integrated Continuous Biomanufacturing, 2019
- Laurea Honoris Causa, Slovak University of Technology, Bratislava, 2019
- European Research Council, Advanced Grant, Continuous Digitalized Processes for Producing Biopharmaceuticals, 2023
In his career he advised more than 100 PhD students. He is a cofounder of ChromaCon Ltd., a spin-off company from his research group, which brings new chromatographic processes (MCSGP-technology) for the purification of proteins and peptides to the market (now acquired by YMC, Japan) and of DataHow Ltd. for the application of data science and machine learning in Biotechnology and specifically in the Biopharma Industry.