Evidence map›Paper›PMID 41801362›Full record

ReviewAdvances in biochemical engineering/biotechnology2026

Technical Scale in Biomolecular Crystallization.

Wenqing Tian, Wenqian Chen, Huaiyu Yang

Abstract readReview
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In one paragraph

Review in Advances in biochemical engineering/biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Wenqing TianAstrazeneca, Macclesfield, UK.
Wenqian ChenDepartment of Pharmacy and Pharmaceutical Sciences, National University of Singapore, Singapore, Singapore.
Huaiyu YangLoughborough University, Loughborough, UK. h.yang3@lboro.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the scalability of biomolecular crystallization processes has garnered significant attention due to its advantages in enhancing product quality and reducing manufacturing costs compared to the traditional purification methods. Unlike the crystallization process of small molecules, biomolecular crystallization lacks a comprehensive theory or guidelines, often relying on modified crystallization theories and empirical approaches. It is challenging to guide protein molecules assembling into ordered crystal lattice due to the huge molecular size and complexity of the structure, and protein crystals are more delicate and fragile than conventional small organic molecular crystals. Furthermore, proteins often exhibit limited stability within specific environmental conditions, such as varying pH and temperature ranges. Consequently, many standard methods employed for small-molecule crystallization are not applicable to biomolecular crystallization. Most of the bimolecular crystallization research are focused on tiny scale, while more research on biomolecular crystallization at various larger technical scales has emerged over time. The scaling up mechenism from the tiny scale to the large scale is critical to widely apply the biomolecular crystallization. This chapter begins by summarizing the different methods used in biomolecular crystallization. Then, biomolecular crystallization is reviewed from nL to μL scale (e.g., hanging drop or sitting drop) to mL scale, such as in small batch or microfluidic crystallizer till hundred mL or L scale, such as standard stirred crystallizer. Finally, it explores different crystallization scales with corresponding process monitoring and analytical methods for the crystallization kinetics.

Indexed as

ProteinsCrystallizationProteinsBiomolecular crystallizationKineticMicro–meso–macro methodsProcess analytical toolsProteinScaling up

Identifiers

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Registered trials

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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.