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Theoretical Medicine and Bioethics

, Volume 40, Issue 2, pp 103–121 | Cite as

Evidence for personalised medicine: mechanisms, correlation, and new kinds of black box

  • Mary Jean WalkerEmail author
  • Justin Bourke
  • Katrina Hutchison
Article
  • 280 Downloads

Abstract

Personalised medicine (PM) has been discussed as a medical paradigm shift that will improve health while reducing inefficiency and waste. At the same time, it raises new practical, regulatory, and ethical challenges. In this paper, we examine PM strategies epistemologically in order to develop capacities to address these challenges, focusing on a recently proposed strategy for developing patient-specific models from induced pluripotent stem cells (iPSCs) so as to make individualised treatment predictions. We compare this strategy to two main PM strategies—stratified medicine and computational models. Drawing on epistemological work in the philosophy of medicine, we explain why these two methods, while powerful, are neither truly personalised nor, epistemologically speaking, novel strategies. Both are forms of correlational black box. We then argue that the iPSC models would count as a new kind of black box. They would not rely entirely on mechanistic knowledge, and they would utilise correlational evidence in a different way from other strategies—a way that would enable personalised predictions. In arguing that the iPSC models would present a novel method of gaining evidence for clinical practice, we provide an epistemic analysis that can help to inform the practical, regulatory, and ethical challenges of developing an iPSC system.

Keywords

Personalised medicine Correlational evidence Mechanistic evidence Black box Induced pluripotent stem cell 

Notes

Acknowledgements

This research was supported by Australian Research Council (Grant ID CE140100012). The authors would like to thank colleagues in the Ethics, Policy and Public Engagement theme at the Centre of Excellence for Electromaterials Science (ACES) for their comments on drafts.

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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Monash UniversityClaytonAustralia
  2. 2.University of MelbourneParkvilleAustralia
  3. 3.Macquarie UniversityNorth RydeAustralia
  4. 4.Australian Research Council Centre of Excellence for Electromaterials ScienceWollongongAustralia

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