Evidence map›Paper›PMID 31599989›Full record

ArticleSociology of health & illness2019

The datafication of reproduction: time-lapse embryo imaging and the commercialisation of IVF.

Lucy van de Wiel

Abstract read
In one paragraph

Article in Sociology of health & illness, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
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  3. Article
  4. Article
  5. Article
  6. Digital health: A sociomaterial approach.Sociology of health & illness · 2023
    Article
  7. Article
  8. Article
  9. Article
  10. 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

1 author.

Lucy van de WielDepartment of Sociology, University of Cambridge, Cambridge, UK.ORCID 0000-0002-2413-7795

Funding

Wellcome TrustWellcome Trust 209829/Z/17/Z
6 · The paper itself

Abstract

The 21st century has witnessed the emergence of in silico reproduction alongside the familiar in vitro reproduction (e.g. IVF), as increasingly large and automatically-generated data sets have come to play an instrumental role in assisted reproduction. The article addresses this datafication of reproduction by analysing time-lapse embryo imaging, a key data-driven technology for embryo selection in IVF cycles. It discusses the new forms of knowledge and value creation enabled by data-driven embryo selection and positions this technology as a harbinger of a wider datafication of (reproductive) health. By analysing the new ways of seeing embryos with 'in silico vision,' the 'data generativity' of developing embryos and the patenting of embryo selection algorithms, I argue that this datafied method of embryo selection may not just result in more or less 'IVF success,' but also affects the conceptualisation and commercialisation of the assisted reproductive process. In doing so, I highlight how the datafication of reproduction both reflects and reinforces a consolidating trend in the fertility sector-characterised by mergers resulting in larger fertility chains, online platforms organising fertility care and expanded portfolios of companies aiming to cover each step of the IVF cycle.

Indexed as

AlgorithmsEmbryonic DevelopmentFertilization in VitroHumansMedicalizationMicroscopyPatents as TopicTime-Lapse ImagingdataficationIVFreproductive healthreproductive rightsreproductive technologytime-lapse embryo imaging

Identifiers

PMID31599989
PMCPMC6856688

What OpenQuestion holds

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LicenceCC BY
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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.