Evidence map›Paper›PMID 37342509›Full record

ArticleFrontiers in bioengineering and biotechnology2023

Next-generation cell line selection methodology leveraging data lakes, natural language generation and advanced data analytics.

Stephen Goldrick, Haneen Alosert, Clare Lovelady, Nicholas J Bond, Tarik Senussi, Diane Hatton, John Klein, Matthew Cheeks, Richard Turner, James Savery and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 25% of its field
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

5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. 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

11 authors at 2 institutions in 1 country.

Stephen GoldrickDepartment of Biochemical Engineering, University College London, London, United Kingdom.
Haneen AlosertDepartment of Biochemical Engineering, University College London, London, United Kingdom.
Clare LoveladyCell Culture and Fermentation Science, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Nicholas J BondAnalytical Sciences, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Tarik SenussiCell Culture and Fermentation Science, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Diane HattonCell Culture and Fermentation Science, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
John KleinData Science and Modelling, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Matthew CheeksCell Culture and Fermentation Science, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Richard TurnerPurification Process Sciences, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
James SaveryData Science and Modelling, Biopharmaceuticals Development, R&D, AstraZeneca, Cambridge, United Kingdom.
Suzanne S FaridDepartment of Biochemical Engineering, University College London, London, United Kingdom.
AstraZeneca (United Kingdom) · GBUniversity College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as

Indexed as

cell line developmentdata analyticsIndustry 4.0machine learningnatural language generation

Identifiers

PMID37342509
PMCPMC10277482
OpenAlexW4379469793

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.