Process systems engineering–the generation next?

EN Pistikopoulos, A Barbosa-Povoa, JH Lee… - Computers & Chemical …, 2021 - Elsevier
Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

Machine learning for biologics: opportunities for protein engineering, developability, and formulation

H Narayanan, F Dingfelder, A Butté, N Lorenzen… - Trends in …, 2021 - cell.com
Successful biologics must satisfy multiple properties including activity and particular
physicochemical features that are globally defined as developability. These multiple …

[HTML][HTML] Moving towards an era of hybrid modelling: advantages and challenges of coupling mechanistic and data-driven models for upstream pharmaceutical …

A Tsopanoglou, IJ del Val - Current Opinion in Chemical Engineering, 2021 - Elsevier
Highlights•Mathematical models as tools to establish quantitative links between bioprocess
CPPs and KPIs.•Review of the advantages and limitations of mechanistic and statistical …

Emerging challenges and opportunities in pharmaceutical manufacturing and distribution

M Sarkis, A Bernardi, N Shah, MM Papathanasiou - Processes, 2021 - mdpi.com
The rise of personalised and highly complex drug product profiles necessitates significant
advancements in pharmaceutical manufacturing and distribution. Efforts to develop more …

Hybrid modeling—a key enabler towards realizing digital twins in biopharma?

M Sokolov, M von Stosch, H Narayanan, F Feidl… - Current Opinion in …, 2021 - Elsevier
Digital twins (DTs) represent a vividly emerging technology in the manufacturing industry
strongly motivated by the goals of industry 4.0. It strives for smart factories with completely …

Digital twins in manufacturing: systematic literature review for physical–digital layer categorization and future research directions

M Atalay, U Murat, B Oksuz, AM Parlaktuna… - … Journal of Computer …, 2022 - Taylor & Francis
Modern technologies and recently developed digital solutions make their way into all
aspects of lives of individuals and businesses, and manufacturing industry is no exception …

[HTML][HTML] Applications of machine learning in antibody discovery, process development, manufacturing and formulation: Current trends, challenges, and opportunities

TT Khuat, R Bassett, E Otte, A Grevis-James… - Computers & Chemical …, 2024 - Elsevier
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 …

Integrated design of biopharmaceutical manufacturing processes: Operation modes and process configurations for monoclonal antibody production

S Badr, K Okamura, N Takahashi, V Ubbenjans… - Computers & Chemical …, 2021 - Elsevier
Monoclonal antibodies are leading the growing biopharmaceutical markets. To sustain the
increasing demand, manufacturing processes should be optimized to increase efficiency …

Purification of modified therapeutic proteins available on the market: An analysis of chromatography-based strategies

C Sánchez-Trasviña, M Flores-Gatica… - … in Bioengineering and …, 2021 - frontiersin.org
Proteins, which have inherent biorecognition properties, have long been used as
therapeutic agents for the treatment of a wide variety of clinical indications. Protein …

[HTML][HTML] Industrial internet of things: What does it mean for the bioprocess industries?

L Borgosz, D Dikicioglu - Biochemical Engineering Journal, 2024 - Elsevier
Abstract Industrial Internet of Things (IIoT) is a system of interconnected devices that, via the
use of various technologies, such as soft sensors, cloud computing, data analytics, machine …