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Cited by 176

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Process Analytical Technologies – Advances in bioprocess integration and future perspectives

Open access
Gerzon, Gabriella, Sheng, Yi, Kirkitadze, Marina·2022·Journal of Pharmaceutical and Biomedical Analysis

Abstract

Process Analytical Technology (PAT) instruments include analyzers capable of measuring physical and chemical process parameters and key attributes with the goal of optimizing process controls. PAT in the form of a probe or sensor is designed to integrate within the pharmaceutical manufacturing line and is coupled with computing equipment to perform chemometric modeling for result interpretation and multilayer statistical control of processes. PAT solutions are intended for understanding bioprocesses with a goal to control quality at all stages of product manufacturing and achieve quality by design (QbD). The goal of PAT implementation is to promote real-time release of products to decrease the cycle time and cost of production. This review focuses on the applications of PAT solutions at different stages of the manufacturing process for vaccine production, the advantages, challenges at present state, and the vision of the future development of biopharmaceutical industries.

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Metadata

Authors
Gerzon, G., Sheng, Y., & Kirkitadze, M.
Venue
Journal of Pharmaceutical and Biomedical Analysis
Publisher
Elsevier BV
Published
2022-01
Volume
207
Pages
114379
ISSN
0731-7085 (ISSN-L)
OpenAlex
W3203851743
Cited by
176
References
11
FWCI
9.38
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Process Analytical Technologies – Advances in bioprocess integration and future perspectives. https://app.cochat.ai/papers/10.1016/j.jpba.2021.114379
The paper
Gerzon, G., Sheng, Y., & Kirkitadze, M. (2022). Process Analytical Technologies – Advances in bioprocess integration and future perspectives. Journal of Pharmaceutical and Biomedical Analysis. https://doi.org/10.1016/j.jpba.2021.114379

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.