Evidence map›Paper›PMID 39751653›Full record

ArticleBioprocess and biosystems engineering2025

Computational fluid particle dynamics modeling of tangential flow filtration in perfusion cell culture.

Hamideh Hayati, Caitlin Kurtz, Yu Feng, Sarwat Khattak

Abstract read
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Article in Bioprocess and biosystems engineering, 2025. 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. Article
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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

4 authors.

Hamideh HayatiSchool of Chemical Engineering, Oklahoma State University, Stillwater, OK, 74078, USA.
Caitlin KurtzCell Culture Development, Biogen, 5000 Davis Drive, Research Triangle Park, NC, 27709, USA. caitlin.kurtz@biogen.com.
Yu FengSchool of Chemical Engineering, Oklahoma State University, Stillwater, OK, 74078, USA.
Sarwat KhattakCell Culture Development, Biogen, 5000 Davis Drive, Research Triangle Park, NC, 27709, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Membrane fouling is a common and complex challenge with cell culture perfusion process in biopharmaceutical manufacturing that can have detrimental effects on the process performance. In this study, we evaluated a method to calculate the hollow fiber membrane resistance at different time points for water and supernatant. In addition, the number of subvisible particles of < 200 nm. diameter suspended in the supernatant were quantified using a nano-flow cytometry method. A computational fluid dynamics (CFD) model was developed to evaluate the impact of feed flow rate and particle count on the transmembrane pressure (TMP). Then a steady-state discrete phase model was applied to incorporate particles into the model and simulate the particles deposition over the membrane wall. The results showed an increase in the number of particles and the membrane resistance along the time course of the perfusion process. The CFD model illustrated that more particle deposition was observed at lower feed stream flow rates. The fraction of deposited particle was reduced by > 50% when the feed flow rate was increased from 35 ml/min to 300 ml/min. Our findings suggest that the total number of subvisible particles has a significant impact on TMP and membrane resistance and, thus, could play a major role in the mechanism of membrane fouling. CFD modeling can be a useful tool to predict the behavior of a process in a specific membrane. CFD simulations could also be used to optimize process parameters to improve membrane cleanability, reduce particle deposition, and reduce the risk of membrane fouling.

Indexed as

Cell Culture TechniquesComputer SimulationFiltrationHydrodynamicsMembranes, ArtificialMembranes, ArtificialCell cultureComputational fluid particle dynamics (CFPD)Extracellular vesiclesHollow fiber filterPerfusionTangential flow filtration (TFF)

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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.