Abstract
Large investments over many decades in genomics in diverse fields such as precision medicine, plant biology, and recently, in space life science research and astronaut omics were not accompanied by a commensurate focus on high-throughput and granular characterization of phenotypes, thus resulting in a “phenomics lag” in systems science. There are also limits to what can be achieved through increases in sample sizes in genotype–phenotype association studies without commensurate advances in phenomics. These challenges beg a question. What might next-generation phenomics look like, given that the Internet of Things and artificial intelligence offer prospects and challenges for high-throughput digital phenotyping as a key component of next-generation phenomics? While attempting to answer this question, I also reflect on governance of digital technology and next-generation phenomics. I argue that it is timely to broaden the technical discourses through a lens of political theory. In this context, this analysis briefly engages with the recent book “The Earthly Community: Reflections on the Last Utopia,” written by the historian and political theorist Achille Mbembe. The question posed by the book, “Will we be able to invent different modes of measuring that might open up the possibility of a different aesthetics, a different politics of inhabiting the Earth, of repairing and sharing the planet?” is directly relevant to healing of human diseases in ways that are cognizant of the interdependency of human and nonhuman animal health, and critical and historically informed governance of digital technologies that promise to benefit next-generation phenomics.
Perspective
Genomics is an established technology and scholarship with a storied history spanning the 20th and 21st centuries. The contribution of heredity to drug response phenotypes was first proposed and theorized in the field of pharmacogenetics in the 1950s and 1960s (Kalow, 1962; Motulsky, 1957). The availability of high-throughput omics technologies allowed the study of genome-by-drug interactions at scale, thus transforming pharmacogenetics to pharmacogenomics in the late 1990s, and giving rise to allied fields of precision medicine such as pharmacoproteomics and pharmacometabolomics as well. The rise of ecogenetics (Brewer, 1971) and afterward ecogenomics over the last half century expanded the scope of research on host–environment interactions from drugs and nutrition in the broadest sense possible. This meant a greater emphasis in systems science on environmental pollution, biodiversity loss, climate emergency and urban design, digital transformation, disinformation, and biopolitics, and the ways in which they collectively impact on host biology in the case of humans, nonhuman animals, or planetary ecosystems (Horton et al. 2014; Springer and Özdemir, 2022; Yetişkin and Özdemir, 2022).
The interest in unpacking the underlying mechanisms of disease and responses to drugs and other ecological exposures led to genomics and multiomics applications in diverse fields such as planetary health, clinical trials of drugs and vaccines, precision/personalized medicine, precision nutrition, plant biology, biofuels, veterinary medicine, and most recently, space life science research. Rutter and colleagues suggested that “As humanity becomes increasingly spacefaring, high-resolution omics on orbit could permit an advent of precision spaceflight healthcare.” (Rutter et al. 2024). Short-term spaceflight has been the subject of systems science to understand its impacts on human biology at scale, for example, through longitudinal multiomics analysis of host microbiome and immune responses during and after spaceflight (Tierney et al. 2024).
Large investments over many decades in genomics and multiomics technologies were not accompanied, however, by a commensurate focus on high-throughput characterization of phenotypes, thus resulting in a “phenomics lag” in systems science (Özdemir, 2020). Phenomics refers to “systematic measurement and analysis of qualitative and quantitative traits, including clinical, biochemical, and imaging methods, for the refinement and characterization of a phenotype.” (Lanktree et al., 2010). Lags or bottlenecks in phenomics to move genomics to real-life applications exist in medicine and public health and also in plant biology (Cobb et al. 2013), and, as discussed by Vishwa Ranjan Upadhyay and colleagues in the August 2024 issue of OMICS, in livestock phenomics as well.
To be sure, the phenomics lag is also an opportunity for critical reflection to achieve more robust and reproducible multiomics research in the course of unpacking the biological and ecological components of complex phenotypic traits. Indeed, scholars have argued that “some of the most scientifically disrupting and industry-relevant challenges relate to ‘phenomics’ instead of ‘genomics’” (Pérez-Enciso and Steibel, 2021).
An innovation “bottleneck” is a metaphor frequently deployed to forecast, map, and intervene on multiple possible futures awaiting emerging or established technologies. A bottleneck conjures up images of challenge and hope; it signifies a cumbersome passage, a narrow strait to sail through, as well as open vistas awaiting once the bottleneck is cleared. As with all models, metaphors are almost always an incomplete description of the field practices. Nonetheless, metaphors that are critically informed can offer ways to theorize and address the existing gaps in science, technology, and society.
If the current phenomics lag is one of the rate-limiting steps for genomics and multiomics innovations, this begs a question. What might next-generation phenomics look like, given that the Internet of Things (IoT) and digital technologies such as artificial intelligence offer prospects and challenges for digital phenotyping as a key component of next-generation phenomics?
There are limits to what can be achieved through increases in sample sizes in genotype–phenotype association studies without accompanying advances in phenomics (Özdemir, 2020). To this end, measurement of phenotypes in the controlled settings of physicians’ offices and clinical trials does not always accurately reflect patients’ relevant experiences and what matters to them in the course of a disease and its treatment. The real-life context of diseases and treatments matters greatly if we are to unravel the multiomics and mechanistic basis of complex real-life phenotypic architectures in ways that stand the tests of time and context.
Longitudinal phenomics and real-time data capture, with next-generation phenomics, can unpack what, when, and how patients experience temporally and spatially, and build linkages between the content and context of their experiences of disease and treatment. To the extent that “context is gold” to explain why some treatments work, whereas others fail, and why some patients become worse and others return to a healthy state, there is a need for a better understanding of the real-life settings. Continuous phenotypic measures in real-time can also help to overcome the recall bias in clinical trials when the participants are retrospectively asked about their responses to disease and treatment. Additionally, next-generation phenomics can usefully address disease phenotypes as well as drug, nutrition, vaccine, and other health intervention outcome phenotypes with an eye to precision/personalized medicine.
The Internet of Pharmaceutical Things (IoPT) is a specialized application of the IoT to drug-related phenotypes and continuous phenotypic data capture. The IoPT integrates process innovation with innovation in capturing the real-life experiences and priorities of patients (Özdemir, 2020). With sensors embedded in, e.g., a smart textile or wristwatch, patients’ responses to treatments can be documented at scale with the IoPT and in ways resolved in time and space, and importantly, within the social and real-life context of their daily settings, be it at work, on the street, at home, on a space station, or on vacation. The potential applications of the IoPT are not limited to the phenotyping of drug-related real-world outcomes, however.
The IoPT can help automation in pharmaceutical manufacturing units and optimize the supply chain for medicines among the smart factories, hospitals, and digital pharmacies. Patient education and drug information services, too, stand to benefit from the IoPT, as embedded sensors and digital connectivity could serve as a two-way platform for phenotypic data capture and to deliver the most recent pharmacology information to patients and caregivers. (Özdemir, 2020).
Next-generation phenomics can help to unravel novel phenotypes and their novel contexts that are hitherto overlooked and yet matter greatly for patients and robust omics innovations. Unlike the genome of a patient that can be characterized, phenomics is open-ended and not a closed entity (Pérez-Enciso and Steibel, 2021). A corollary for next-generation phenomics is that there is an infinite range of phenotypes and their spatial, temporal, and social contexts that can be measured.
Next-generation phenomics, and continuous digital phenotyping in particular, come with a host of societal dimensions that ought to be borne in mind. The same technologies that offer digital and remote measurement of phenotypic big data can also be used for surveillance, disinformation, and closing up public spaces that are crucial for democracy in science, medicine, and society (Springer and Özdemir, 2022; Yetiskin 2022). Hence, digital is inherently political. For critically informed governance, it would be timely to broaden the technical discourses on next-generation phenomics through a lens of political theory. In this context, it is essential to go beyond the traditional science policymaking that asks “which social issues emerge from a new technology?” to include, additionally, questions that unpack politics and power asymmetries such as “who is/are framing science and technology policy, and why?”.
In his recent book “The Earthly Community: Reflections on the Last Utopia,” the historian and political theorist Achille Mbembe asks a number of questions that are well-poised to inform how best to govern the digital transformation of life in an era of climate emergency. The book astutely asks “what remains of the human subject in an age when the instrumentality of reason is carried out by and through information machines and technologies of calculation” and “who will define the threshold or set the boundary that distinguishes between the calculable and the incalculable, between that which is deemed worthy and that which is deemed worthless, and therefore dispensable.” (Mbembe, 2022).
The questions that Mbembe poses are important and relevant to critical governance of next-generation phenomics in times of extreme digital transformation (Özdemir, 2018) and to reflect on whether and how we might collectively “open up the possibility of a different aesthetics, a different politics of inhabiting the Earth, of repairing and sharing the planet?” (Mbembe, 2022).
Thinking about healing the planet through a new and critically and historically grounded aesthetics and politics bodes well with healing of human diseases in ways that are cognizant of the interdependency of human and nonhuman animal health, and socially just and robust governance of digital technologies that promise to benefit next-generation phenomics.
Footnotes
Disclaimer
Views expressed are the personal opinion of the author only and do not necessarily reflect the views of the affiliated institutions.
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The author declares no conflicting financial interests.
Funding Information
No funding was received for this editorial analysis.
