Evidence map›Paper›PMID 38927782›Full record

ReviewBioengineering (Basel, Switzerland)2024

Integration Approaches to Model Bioreactor Hydrodynamics and Cellular Kinetics for Advancing Bioprocess Optimisation.

Vishal Kumar Singh, Ioscani Jiménez Del Val, Jarka Glassey, Fatemeh Kavousi

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. The 10th Anniversary ofBioengineering (Basel, Switzerland) · 2025
    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

4 authors.

Vishal Kumar SinghProcess and Chemical Engineering, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland.ORCID 0009-0004-2106-3219
Ioscani Jiménez Del ValSchool of Chemical & Bioprocess Engineering, University College Dublin, D04 V1W8 Dublin, Ireland.
Jarka GlasseyProcess and Chemical Engineering, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland.
Fatemeh KavousiProcess and Chemical Engineering, School of Engineering and Architecture, University College Cork, T12 K8AF Cork, Ireland.ORCID 0000-0002-4166-4589

Funding

Eli Lilly (Ireland) University College Cork Eli Lilly Research Scholarship
6 · The paper itself

Abstract

Large-scale bioprocesses are increasing globally to cater to the larger market demands for biological products. As fermenter volumes increase, the efficiency of mixing decreases, and environmental gradients become more pronounced compared to smaller scales. Consequently, the cells experience gradients in process parameters, which in turn affects the efficiency and profitability of the process. Computational fluid dynamics (CFD) simulations are being widely embraced for their ability to simulate bioprocess performance, facilitate bioprocess upscaling, downsizing, and process optimisation. Recently, CFD approaches have been integrated with dynamic Cell reaction kinetic (CRK) modelling to generate valuable information about the cellular response to fluctuating hydrodynamic parameters inside large production processes. Such coupled approaches have the potential to facilitate informed decision-making in intelligent biomanufacturing, aligning with the principles of "Industry 4.0" concerning digitalisation and automation. In this review, we discuss the benefits of utilising integrated CFD-CRK models and the different approaches to integrating CFD-based bioreactor hydrodynamic models with cellular kinetic models. We also highlight the suitability of different coupling approaches for bioprocess modelling in the purview of associated computational loads.

Indexed as

bioprocess modellingcell reaction kineticscomputational fluid dynamicsdigitalisationprocess optimisation

Identifiers

PMID38927782
PMCPMC11200465

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.