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.
Highlights
Recent years have seen an intensification of the datafication of reproduction, as increasingly large and automatically-generated data sets have come to play an instrumental role in the technological reproduction of human life
As the so-called “data revolution” is transforming health care at large (Kitchin, 2014), it is pertinent to focus on assisted reproduction in particular because it is a relatively unregulated sector in which bioinnovations—including data-centric ones—are introduced rapidly. Such innovations are relevant beyond their clinicalefficacy given the culturally-specific and politically-charged nature of reproductive processes and their reconceptualisation and reconfiguration in the face of new reproductive technologies (Franklin, 2013)
As fertility clinics invest in time-lapse imaging, more intended parents will be confronted with the question of whether to include this add-on in their In Vitro Fertilisation (IVF) cycles—often at an increased cost
Summary
At the heart of the valuation of data-driven embryo selection is the emergence of new software and algorithmic products, which produce new forms of datafied biocapital. The upholding of a model of universality and interchangeable standardisation is both a key driver and an effect of the datafication of embryo selection It is part of a marketing strategy to extend automated embryo selection to more clinics, while being in and of itself a condition of emergence for the networked reproductive bioeconomies of data sharing and data ownership emerging with data-driven IVF. The datafication of embryo selection entails at once the clinical introduction of integrated apparatuses for reproductive data generation, the creation of connected networks of data sharing, and the production of biocapital out of biodata by means of algorithmisation—all of which combine in a system that is marketed directly to patients and fertility clinics. The large-scale redistributions of embryo data between fertility companies that produce and use time-lapse embryo imaging create new forms of value, and reorder institutional relationships as lines between research and clinical practices are blurred. What is at stake in these developments is that data asymmetries between clinical, pharmaceutical and biotechnological organisations reflect and reconfigure the power dynamics in the fertility sector, which I will discuss
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