Abstract Machine Learning is quickly becoming an impending game changer for
transforming big data thrust from the bioprocessing industry into actionable output. However …

The term hybrid modeling refers to the combination of parametric models (typically derived
from knowledge about the system) and nonparametric models (typically deduced from data) …

The growing biopharmaceutical industry has reached a level of maturity that allows for the
monitoring of numerous key variables for both process characterization and outcome …

The biopharmaceutical market has experienced a tremendous growth in the last years.
However, this growth should be balanced considering the difficulty in bioproduct …

Biopharmaceutical production has recently begun transitioning toward the construction of
highly advanced, digitalised production facilities, as per Industry Revolution 4.0 or smart …

The production of monoclonal antibody (mAb) therapeutics, a rapidly growing multi-billion-
dollar enterprise in the biopharmaceutical industry, faces major challenges in achieving …

The biopharmaceutical industries are continuously faced with the pressure to reduce the
development costs and accelerate development time scales. The traditional approach of …

Today's biomanufacturing processes are still operated based on experience, and thus can
hardly cope with increasing bioprocess complexity. Recently, there is a growing interest in …

Hybrid modeling, with an appropriate blend of the mechanistic and data‐driven framework,
is increasingly being adopted in bioprocess modeling, model‐based experimental design …

Owing to the advancement in the technologies, the vision of smart manufacturing is not
implausible. Development of sophisticated measuring tools, modelling approaches …