Data science tools and applications on the way to Pharma 4.0

Valentin Steinwandter; Daniel Borchert; Christoph Herwig

doi:10.1016/j.drudis.2019.06.005

Data science tools and applications on the way to Pharma 4.0

Drug Discov Today. 2019 Sep;24(9):1795-1805. doi: 10.1016/j.drudis.2019.06.005. Epub 2019 Jun 14.

Authors

Valentin Steinwandter¹, Daniel Borchert¹, Christoph Herwig²

Affiliations

¹ Exputec GmbH, Mariahilferstr. 147/2/2D, Vienna, Austria.
² Institute of Chemical Environmental and Bioscience Engineering, Research Area Biochemical Engineering, Vienna University of Technology, Gumpendorferstr. 1a, Vienna, Austria; CD Laboratory on Mechanistic and Physiological Methods for Improved Bioprocesses, Vienna University of Technology, Gumpendorferstr. 1a, Vienna, Austria. Electronic address: christoph.herwig@tuwien.ac.at.

PMID: 31207205
DOI: 10.1016/j.drudis.2019.06.005

Abstract

Multiple obstacles are driving the digital transformation of the biopharmaceutical industry. Novel digital techniques, often marketed as 'Pharma 4.0', are thought to solve some long-existing obstacles in the biopharma life cycle. Pharma 4.0 concepts, such as cyberphysical systems and dark factories, require data science tools as technological core components. Here, we review current data science applications at various stages of the bioprocess life cycle, including their scopes and data sources. We are convinced that the scope and usefulness of these tools are currently limited by technical and nontechnical problems experienced during their development and deployment. We suggest that the establishment of DevOps mind- and toolsets could improve this situation and would be essential cornerstones in the further development of Pharma 4.0 systems.

Publication types

Review

MeSH terms

Data Science / trends*
Drug Development
Drug Industry / trends*
Humans
Information Storage and Retrieval
Information Technology / trends
Manufacturing Industry / trends