Digital/computational phenotyping: What are the differences in the science and the ethics?

Federica Lucivero,Nina Hallowell

doi:10.1177/20539517211062885

Federica Lucivero, Nina Hallowell

Open Access

https://doi.org/10.1177/20539517211062885

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Journal: Big Data & Society	Publication Date: Jul 1, 2021
Citations: 3	License type: CC BY 4.0

Affiliation: Wellcome Centre for Ethics and Humanities

Abstract

The concept of 'digital phenotyping' was originally developed by researchers in the mental health field, but it has travelled to other disciplines and areas. This commentary draws upon our experiences of working in two scientific projects that are based at the University of Oxford's Big Data Institute - The RADAR-AD project and The Minerva Initiative - which are developing algorithmic phenotyping technologies. We describe and analyse the concepts of digital biomarkers and computational phenotyping that underlie these projects, explain how they are linked to other research in digital phenotyping and compare and contrast some of their epistemological and ethical implications. In particular, we argue that the phenotyping paradigm in both projects is grounded on an assumption of 'objectivity' that is articulated in different ways depending on the role that is given to the computational/digital tools. Using the concept of 'affordance', we show how specific functionalities relate to potential uses and social implications of these technologies and argue that it is important to distinguish among them as the concept of digital phenotyping is increasingly being used with a variety of meanings.

Highlights

Digital phenotyping is based on the assumptions that digital technologies can be used to identify phenotypic (observable physical or behavioural traits) features and this will facilitate better understanding of disease states
Digital phenotyping is based on the assumptions that digital technologies can be used to identify phenotypic features and this will facilitate better understanding of disease states
Beyond its application in mental health research the idea of using digital technologies – including computing, machine learning techniques, smartphone applications, and wearable, environmental and mobile phone sensors – to collect and analyse environmental, behavioural and physiological data, explore phenotypic traits, and contribute to disease diagnosis, has driven much research and public health agendas (Huckvale et al, 2019; Waring and Majumder, 2020). This commentary draws upon our experiences of working in two scientific projects that are based at the University of Oxford’s Big Data Institute – https://www. radar-ad.org/ (Muurling et al, 2021) and The Minerva Initiative (Nellaker et al, 2019), which are developing

Summary

Introduction

Digital phenotyping is based on the assumptions that digital technologies can be used to identify phenotypic (observable physical or behavioural traits) features and this will facilitate better understanding of disease states. Building on the concept of digital biomarkers and their relevance for AD research, the RADAR-AD project aims to use remote monitoring technologies to accurately and continuously track and monitor clinical changes to address the lack of a robust way to identify symptoms and track disease progression.

Results

Conclusion