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Assessment of Recent Process Analytical Technology (PAT) Trends: A Multiauthor Review

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Simon, Levente L., Pataki, Hajnalka, Marosi, György, Meemken, Fabian, Hungerbühler, Konrad, Baiker, Alfons, Tummala, Srinivas, Glennon, Brian, Kuentz, Martin, Steele, Gerry, Kramer, Herman J. M., Rydzak, James W., Chen, Zengping, Morris, Julian, Kjell, Francois, Singh, Ravendra, Gani, Rafiqul, Gernaey, Krist V., Louhi-Kultanen, Marjatta, O’Reilly, John, Sandler, Niklas, Antikainen, Osmo, Yliruusi, Jouko, Frohberg, Patrick, Ulrich, Joachim, Braatz, Richard D., Leyssens, Tom, von Stosch, Moritz, Oliveira, Rui, Tan, Reginald B. H., Wu, Huiquan, Khan, Mansoor, O’Grady, Des, Pandey, Anjan, Westra, Remko, Delle-Case, Emmanuel, Pape, Detlef, Angelosante, Daniele, Maret, Yannick, Steiger, Olivier, Lenner, Miklós, Abbou-Oucherif, Kaoutar, Nagy, Zoltan K., Litster, James D., Kamaraju, Vamsi Krishna, Chiu, Min-Sen·2015·Organic Process Research & Development
DOI 10.1021/op500261y
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Abstract

This multiauthor review article aims to bring readers up to date with some of the current trends in the field of process analytical technology (PAT) by summarizing each aspect of the subject (sensor development, PAT based process monitoring and control methods) and presenting applications both in industrial laboratories and in manufacture e.g. at GSK, AstraZeneca and Roche. Furthermore, the paper discusses the PAT paradigm from the regulatory science perspective. Given the multidisciplinary nature of PAT, such an endeavour would be almost impossible for a single author, so the concept of a multiauthor review was born. Each section of the multiauthor review has been written by a single expert or group of experts with the aim to report on its own research results. This paper also serves as a comprehensive source of information on PAT topics for the novice reader.

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Metadata

Authors
Simon, L. L., Pataki, H., Marosi, G., Meemken, F., Hungerbühler, K., Baiker, A., Tummala, S., Glennon, B., Kuentz, M., Steele, G., Kramer, H. J. M., Rydzak, J. W., Chen, Z., Morris, J., Kjell, F., Singh, R., Gani, R., Gernaey, K. V., Louhi-Kultanen, M., O’Reilly, J., Sandler, N., Antikainen, O., Yliruusi, J., Frohberg, P., Ulrich, J., Braatz, R. D., Leyssens, T., von Stosch, M., Oliveira, R., Tan, R. B. H., Wu, H., Khan, M., O’Grady, D., Pandey, A., Westra, R., Delle-Case, E., Pape, D., Angelosante, D., Maret, Y., Steiger, O., Lenner, M., Abbou-Oucherif, K., Nagy, Z. K., Litster, J. D., Kamaraju, V. K., & Chiu, M.-S.
Venue
Organic Process Research & Development
Publisher
American Chemical Society (ACS)
Published
2015-01-08
Volume
19
Issue
1
Pages
3-62
ISSN
  • 1083-6160 (ISSN-L)
  • 1520-586X
DOI
10.1021/op500261y
OpenAlex
W2038865813
Cited by
439
References
6
FWCI
30.53
Type
journal article
Language
en
Open access
green
Funders
  • Engineering and Physical Sciences Research Council (GR/R19366/01, GR/R43853/01)
  • European Research Council (280106-CrySys)
  • Ministry of Education of the People's Republic of China (NCET-12-0106)
  • Suomen Akatemia (260141)
  • National Natural Science Foundation of China (21075034, 21275046)
  • DTI

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.