Big data analytics is the journey to turn data into insights for more informed business and
operational decisions. As the chemical engineering community is collecting more data …

As competition in the biopharmaceutical market gets keener due to the market entry of
biosimilars, process analytical technologies (PATs) play an important role for process …

Process monitoring systems are necessary for ensuring the long-term reliability of the
operation of industrial systems. This article provides some perspectives on progress in the …

This article provides a perspective on control and operations for biopharmaceutical
manufacturing. Challenges and opportunities are described for (1) microscale technologies …

While data analytics tools are changing how manufacturers make critical decisions and
designs, the selection of the best method requires a substantial level of expertise. In …

Real‐time release testing (RTRT) is defined as “the ability to evaluate and ensure the quality
of in‐process and/or final drug product based on process data, which typically includes a …

With recent advances in digitisation and big data analytics, more pharmaceutical firms are
adopting digital tools to achieve modernisation. The biological phenomena within …

Representative cultivation models are needed for designing efficient monoclonal antibody
(mAb) production processes. Simple Monod-type kinetic models could fail to capture …

While machine learning (ML) has made significant contributions to the biopharmaceutical
field, its applications are still in the early stages in terms of providing direct support for quality …

For many modern biopharmaceutical processes, manufacturers develop data-driven models
using data analytics/machine learning (DA/ML) methods. The challenge is how to select the …