Evidence map›Paper›PMID 39055968›Full record

ArticleOrganic process research & development2024

Automated Continuous Crystallization Platform with Real-Time Particle Size Analysis via Laser Diffraction.

Sayan Pal, Arun Pankajakshan, Maximilian O Besenhard, Nicholas Snead, Juan Almeida, Shorooq Abukhamees, Duncan Craig, Federico Galvanin, Asterios Gavriilidis, Luca Mazzei

Abstract read
In one paragraph

Article in Organic process research & development, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Image Analysis Methodologies.Advances in biochemical engineering/biotechnology · 2026
    Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Sayan PalDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
Arun PankajakshanDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
Maximilian O BesenhardDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.ORCID https://orcid.org/0000-0002-5079-617X
Nicholas SneadDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.
Juan AlmeidaPerceptive Engineering, Applied Materials, Vanguard House, Keckwick Lane, Sci Tech Daresbury, Cheshire WA4 4AB, U.K.
Shorooq AbukhameesDepartment of Pharmaceutics and Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, The Hashemite University, Zarqa 13115, Jordan.
Duncan CraigFaculty of Science, University of Bath, Claverton Down, Bath BA2 7AY, U.K.
Federico GalvaninDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.ORCID https://orcid.org/0000-0002-3296-1581
Asterios GavriilidisDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.ORCID https://orcid.org/0000-0003-3508-5043
Luca MazzeiDepartment of Chemical Engineering, University College London, Torrington Place, London WC1E 7JE, U.K.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fourth industrial revolution is gaining momentum in the pharmaceutical industry. However, particulate processes and suspension handling remain big challenges for automation and the implementation of real-time particle size analysis. Moreover, the development of antisolvent crystallization processes is often limited by the associated time-intensive experimental screenings. This work demonstrates a fully automated modular crystallization platform that overcomes these bottlenecks. The system combines automated crystallization, sample preparation, and immediate crystal size analysis via online laser diffraction (LD) and provides a technology for rapidly screening crystallization process parameters and crystallizer design spaces with minimal experimental effort. During the LD measurements, to avoid multiple scattering events, crystal suspension samples are diluted automatically. Multiple software tools, i.e., LabVIEW, Python, and PharmaMV, and logic algorithms are integrated in the platform to facilitate automated control of all the sensors and equipment, enabling fully automated operation. A customized graphical user interface is provided to operate the crystallization platform automatically and to visualize the measured crystal size and the crystal size distribution of the suspension. Antisolvent crystallization of ibuprofen, with ethanol as solvent and water with Soluplus (an additive) as antisolvent, is used as a case study. The platform is demonstrated for antisolvent crystallization of small ibuprofen crystals in a confined impinging jet crystallizer, performing automated preplanned user-defined experiments with online LD analysis.

Identifiers

PMID39055968
PMCPMC11267596

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.