Skip to main content
SpringerLink
Log in

Personalised and Precision Medicine: What Kind of Society Does It Take?

  • Chapter
The Palgrave Handbook of Biology and Society

Abstract

A decade ago, personalised medicine was largely synonymous with the matching of drug therapies to the genomes of individual patients. Since then, it has become a more inclusive term referring to the consideration of individual characteristics—molecular and otherwise—to improve medical research and practice. In this chapter I explore what goals and values underpin current iterations of personalised medicine. An important such goal is comprehensive individual digital data capture: having as much information as possible about the bodies, lives, and environments of individuals is increasingly seen as necessary to reach the goal of personalisation. This, in turn, requires the cooperation of patients who contribute information, time, and self-monitoring efforts, typically with little influence on how their bodies and lives are represented and ‘datafied’.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 239.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Mansfield and Guthman (2014) discern a very similar development in their analysis of epigenetic research: The idea of biological plasticity, which underpins epigenetics, is anti-determinist. Because environmental stimuli influence how a person’s DNA is expressed, there cannot be one ‘normal’. Difference is thus inscribed into the very concept of epigenetics. But, as Mansfield and Guthman show, this difference is not morally and politically neutral: Some ‘variations’ are treated as signs of damage and thus treated as a ‘disruption’ of desirable processes while others are not. That some population groups are much more likely to be exposed to ‘damaging’ stimuli than others is an issue that epigenetic epidemiology pays increasing attention to (Hanson et al. 2011).

  2. 2.

    Very tellingly, Google launched a digital health data platform called ‘baseline’ in 2014 (Levy 2014).

References

  • Abernethy, Amy, Edward Abrahams, Anna Barker, Ken Buetow, Randy Burkholder, William S. Dalton, et al. 2014. Turning the Tide Against Cancer through Sustained Medical Innovation: The Pathway to Progress. Clinical Cancer Research 20 (5): 1081–1086.

    Article  Google Scholar 

  • Agus, David B. 2016. The Lucky Years: How to Thrive in the Brave New World of Health. New York: Simon & Schuster.

    Google Scholar 

  • Ausiello, Dennis. 2013. From Symptomatic to Pre-symptomatic, Continuous Care. YouTube, 26 March. Accessed 29 March 2016. https://www.youtube.com/watch?v=X9wZKCLtujE

  • Bazelier, Marloes T., Frank de Vries, Joan Bentzen, Peter Vestergaard, Hubert G.M. Leufkens, Tjeerd-Pieter Van Staa, and Nils Koch-Henriksen. 2012. Incidence of Fractures in Patients with Multiple Sclerosis: The Danish National Health Registers. Multiple Sclerosis Journal 18 (5): 622–627.

    Article  Google Scholar 

  • Britnell, Mark. 2015. In Search of the Perfect Health System. London: Palgrave.

    Book  Google Scholar 

  • Casper, Monica J., and Lisa-Jean Moore. 2009. Missing Bodies: The Politics of Visibility. New York: New York University Press.

    Google Scholar 

  • Cetina, Krin K. 2005. The Rise of a Culture of Life. EMBO Reports 6 (S1): S76–S80.

    Article  Google Scholar 

  • Clarke, Adele E., Janet K. Shim, Laura Mamo, Jennifer R. Fosket, and Jennifer R. Fishman, eds. 2010. Biomedicalization: Technoscience and Transformations of Health and Illness in the U.S. Durham, NC: Duke University Press.

    Google Scholar 

  • Cressey, Daniel. 2008. Adverse Drug Reactions a Big Killer. Nature news online, 17 March. Accessed 26 August 2017. http://www.nature.com/news/2008/080317/full/news.2008.676.html#cor1

  • Dean, Jodi. 2016. Big Data: Accumulation and Enclosure. Theory & Event 19 (3).

    Google Scholar 

  • Desmond-Hellmann, Susan. 2012. Toward precision medicine: A new social contract? Science Translational Medicine 4 (127): 127ed3.

    Google Scholar 

  • European Science Foundation (ESF). 2012. Personalised Medicine for the European Citizen—Towards More Precise Medicine for the Diagnosis, Treatment and Prevention of Disease. Strasbourg: ESF.

    Google Scholar 

  • Green, Sara, and Henrik Vogt. 2016. Personalizing Medicine: Disease Prevention in Silico and in Socio. Journal of Philosophical Studies, 30: 105–145.

    Google Scholar 

  • Hanson, Mark A., Felicia M. Low, and Peter D. Gluckman. 2011. Epigenetic Epidemiology: The Rebirth of Soft Inheritance. Annals of Nutrition and Metabolism 58 (2): 8–15.

    Article  Google Scholar 

  • Harford, Tim. 2014. Big Data: Are We Making a Big Mistake? Financial Times Weekend Magazine 29 (30 March): 28–31.

    Google Scholar 

  • Hartzband, Pamela, and Jerome Groopman. 2016. Medical Taylorism. New England Journal of Medicine 374 (2): 106–108.

    Article  Google Scholar 

  • Hedgecoe, Adam. 2004. The Politics of Personalised Medicine: Pharmacogenetics in the Clinic. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Hein, Buster. 2015. How Apple Watch could Predict Heart Attacks in the Future. CultofMac, 8 May. Accessed 26 August 2017. http://www.cultofmac.com/322011/how-apple-watch-could-one-day-predict-heart-attacks/

  • Hood, Leroy. 2008. Systems Biology and Systems Medicine: From Reactive to Predictive, Personalized, Preventive and Participatory (P4) Medicine. Engineering in Medicine and Biology Society. EMBS 30th Annual International Conference of the IEEE. cliv-cliv.

    Google Scholar 

  • Jensen, Peter B., Lars J. Jensen, and Soren Brunak. 2012. Mining Electronic Health Records: Towards Better Research Applications and Clinical Care. Nature Reviews Genetics 13: 395–405.

    Article  Google Scholar 

  • Jewson, Nicholas D. 1976. The Disappearance of the Sick-Man from Medical Cosmology, 1770–1870. Sociology 10 (2): 225–244.

    Article  Google Scholar 

  • Khoury, Muin J., Tram K. Lam, John P. Ioannidis, Patricia Hartge, Margaret R. Spitz, Julie E. Buring, Stephen J. Chanock, et al. 2013. Transforming Epidemiology for 21st Century Medicine and Public Health. Cancer Epidemiology, Biomarkers and Prevention 22 (4): 508–516.

    Article  Google Scholar 

  • Lakoff, George, and Mark Johnson. 1998. Metaphors We Live By. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Lareau, David. 2012. The Data Tsunami. Healthcare IT News, May 3. Accessed May 10, 2016. http://www.healthcareitnews.com/blog/data-tsunami

  • Lazarou, Jason, Bruce H. Pomeranz, and Paul N. Corey. 1998. Incidence of Adverse Drug Reactions in Hospitalized Patients: A Meta-analysis of Prospective Studies. JAMA 279 (15): 1200–1205.

    Article  Google Scholar 

  • Levy, Karyne. 2014. Google is Going to Collect Information to Try and Figure out the Perfectly Healthy Human. Business Insider, 14 July. Accessed 26 August 2017. http://www.businessinsider.com/google-baseline-study-2014-7?_ga=1.245189573.1746773008.1460119087&IR=T

  • Longhurst, Christopher A., Robert A. Harrington, and Nigam H. Shah. 2014. A “Green Button” for Using Aggregate Patient Data at the Point of Care. Health Affairs 33 (7): 1229–1235.

    Article  Google Scholar 

  • Lupton, Deborah. 2013. Watery Metaphors: Swimming or Drowning in the Data Ocean. The Sociological Life blog, 29 October. Accessed 27 August 2017. http://simplysociology.wordpress.com/2013/10/29/swimming-or-drowning-in-the-data-ocean-thoughts-on-the-metaphors-of-big-data/

  • Lynch, Michael, Simon A. Cole, Ruth McNally, and Kathleen Jordan. 2010. Truth Machine: The Contentious History of DNA Fingerprinting. Chicago: University of Chicago Press.

    Google Scholar 

  • Mansfield, Becky, and Julie Guthman. 2014. Epigenetic Life: Biological Plasticity, Abnormality, and New Configurations of Race and Reproduction. Cultural Geographies 22 (3): 3–20.

    Google Scholar 

  • Mayer-Schönberger, Viktor, and Kenneth Cukier. 2013. Big Data. London: John Murray Publishers.

    Google Scholar 

  • Meloni, Maurizio. 2016. Political Biology: Science and Social Values in Human Heredity from Eugenics to Epigenetics. Basingstoke: Springer.

    Book  Google Scholar 

  • Meloni, Maurizio, and Giuseppe Testa. 2014. Scrutinizing the Epigenetics Revolution. BioSocieties 9 (4): 431–456.

    Article  Google Scholar 

  • de Mul, Jos. 1999. The Informatization of the Worldview. Information, Communication and Society 2 (1): 69–94.

    Article  Google Scholar 

  • Nettleton, Sarah. 2004. The Emergence of E-Scaped Medicine? Sociology 38 (4): 661–679.

    Article  Google Scholar 

  • [US] National Academy of Sciences (NAS). 2011. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and A New Taxonomy of Disease. Washington, DC: NAS.

    Google Scholar 

  • Neff, Gina. 2013. Why Big Data Won’t Cure Us. Big Data 1 (3): 117–123.

    Article  Google Scholar 

  • Noble, Denis. 2008. The Music of Life: Biology Beyond Genes. Oxford, UK: Oxford University Press.

    Google Scholar 

  • Onakpoya, Igho J., Carl J. Heneghan, and Jeffrey K. Aronson. 2016. Worldwide Withdrawal of Medicinal Products Because of Adverse Drug Reactions: A Systematic Review and Analysis. Critical Reviews in Toxicology. doi:10.3109/10408444.2016.1149452

  • Özdemir, Vural, Kamal F. Badr, Edward S. Dove, Laszlo Endrenyi, Christy Jo Geraci, Peter J. Hotez, Djims Milius, et al. 2013. Crowd-Funded Micro-grants for Genomics and Big Data: An Actionable Idea Connecting Small (Artisan) Science, Infrastructure Science, and Citizen Philanthropy. OMICS A Journal of Integrative Biology 17 (4): 161–172.

    Article  Google Scholar 

  • Pálsson, Gísli. 2007. How Deep is the Skin? The Geneticization of Race and Medicine. BioSocieties 2: 257–272.

    Article  Google Scholar 

  • Pariser, Eli. 2012. The Filter Bubble: What the Internet is Hiding From You. London: Penguin.

    Book  Google Scholar 

  • PerMed Consortium. 2015. Shaping Europe’s Vision for Personalised Medicine: Strategic Research and Innovation Agenda. Cologne. Accessed 13 December 2015 http://www.permed2020.eu/_media/PerMed_SRIA.pdf

  • Prainsack, Barbara. 2007. Research Populations: Biobanks in Israel. New Genetics and Society 26 (1): 85–103.

    Article  Google Scholar 

  • ———. 2015a. Is Personalised Medicine Different? (Reinscription: The Sequel). A Response to Troy Duster. British Journal of Sociology 66 (1): 28–35.

    Article  Google Scholar 

  • ———. 2015b. Three “H”s for Health—The Darker Side of Big Data. Forum Bioethica 8 (2): 4–5.

    Google Scholar 

  • ———. forthcoming. Personalization from Below: Participatory Medicine in the 21st Century? New York City: New York University Press.

    Google Scholar 

  • Prainsack, Barbara, Silke Schicktanz, and Gabriele Werner-Felmayer, eds. 2014. Genetics as Social Practice, 147–164. Farnham: Ashgate.

    Google Scholar 

  • Robinson, Peter N. 2012. Deep Phenotyping for Precision Medicine. Human Mutation 33 (5): 777–780.

    Article  Google Scholar 

  • Rose, Nikolas. 1999. Powers of Freedom: Reframing Political Thought. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • ———. 2007. The Politics of Life Itself: Biomedicine, Power, and Subjectivity in the Twenty-First Century. Princeton: Princeton University Press.

    Book  Google Scholar 

  • Roski, Joachim, George W. Bo-Linn, and Timothy A. Andrews. 2014. Creating Value in Health Care Through Big Data: Opportunities and Policy Implications. Health Affairs 33 (7): 1115–1122.

    Article  Google Scholar 

  • Schatz, Bruce R. 2015. National Surveys of Population Health: Big Data Analytics for Mobile Health Monitors. Big Data 3 (4): 219–229.

    Article  Google Scholar 

  • Skinner, David. 2006. Racialized Futures: Biologism and the Changing Politics of Identity. Social Studies of Science 36 (3): 459–488.

    Article  Google Scholar 

  • Taylor, Astra. 2014. The People’s Platform: Taking Back Power and Culture in the Digital Age. New York: Picador.

    Google Scholar 

  • Timmermans, Stefan, and Mara Buchbinder. 2010. Patients-in-waiting Living between Sickness and Health in the Genomics Era. Journal of Health and Social Behavior 51 (4): 408–423.

    Article  Google Scholar 

  • Topol, Eric. 2012. The Creative Destruction of Medicine: How the Digital Revolution Will Create Better Health Care. New York: Basic Books.

    Google Scholar 

  • ———. 2015. The Patient will See You Now: The Future of Medicine is in Your Hands. New York: Basic Books.

    Google Scholar 

  • Tutton, Richard. 2014. Genomics and the Reimagining of Personalized Medicine. Farnham: Ashgate.

    Google Scholar 

  • United Nations (U.N.) International Convenant on Economic, Social and Cultural Rights. 1966. Accessed 27 August 2017. http://www.ohchr.org/EN/ProfessionalInterest/Pages/CESCR.aspx

  • Vogt, Henrik, Elling Ulvestad, Thor Eirik Eriksen Cand Polit, and Linn Getz. 2014. Getting Personal: Can Systems Medicine Integrate Scientific and Humanistic Conceptions of the Patient? Journal of Evaluation in Clinical Practice 20: 942–952.

    Article  Google Scholar 

  • Vogt, Henrik, Bjørn Hofmann, and Linn Getz. 2016. The New Holism: P4 Systems Medicine and the Medicalization of Health and Life Itself. Medicine, Health Care and Philosophy 19: 307–323.

    Article  Google Scholar 

  • Waldby, Catherine. 2000. The Visible Human Project: Information Bodies and Posthuman Medicine. London: Routledge.

    Book  Google Scholar 

  • Weber, Griffin M., Kenneth D. Mandl, and Isaac S. Kohane. 2014. Finding the Missing Link for Big Biomedical Data. The Journal of the American Medical Association 331 (24): 2479–2480.

    Google Scholar 

  • Webster, Andrew. 2002. Innovative Health Technologies and the Social: Redefining Health, Medicine and the Body. Current Sociology 50 (3): 443–457.

    Article  Google Scholar 

  • Weston, Andrea D., and Leroy Hood. 2004. Systems Biology, Proteomics, and the Future of Health Care: Toward Predictive, Preventative, and Personalized Medicine. Journal of Proteome Research 3: 179–196.

    Article  Google Scholar 

  • Zwolsman, Sandra E., Nynke van Dijk, and Margreet Wieringa de Waard. 2013. Observations of Evidence-based Medicine in General Practice. Perspectives on Medical Education 2: 196–208.

    Article  Google Scholar 

Download references

Acknowledgments

I am grateful to John Cromby, Des Fitzgerald, Maurizio Meloni and Henrik Vogt for very helpful comments on an earlier version of this chapter. The usual disclaimer applies.

Author information

Authors and Affiliations

  1. King’s College London, London, UK

    Barbara Prainsack

Authors
  1. Barbara Prainsack
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Sociological Studies, University of Sheffield, Sheffield, UK

    Maurizio Meloni

  2. School of Management, University of Leicester, Leicester, UK

    John Cromby

  3. Cardiff University, Cardiff, UK

    Des Fitzgerald

  4. Department of Anthropology, Laval University, Québec, Canada

    Stephanie Lloyd

Copyright information

© 2018 The Author(s)

About this chapter

Cite this chapter

Prainsack, B. (2018). Personalised and Precision Medicine: What Kind of Society Does It Take?. In: Meloni, M., Cromby, J., Fitzgerald, D., Lloyd, S. (eds) The Palgrave Handbook of Biology and Society. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-52879-7_29

Download citation

  • DOI: https://doi.org/10.1057/978-1-137-52879-7_29

  • Publisher Name: Palgrave Macmillan, London

  • Print ISBN: 978-1-137-52878-0

  • Online ISBN: 978-1-137-52879-7

  • eBook Packages: Social SciencesSocial Sciences (R0)

Publish with us

Policies and ethics

Search

Navigation