Genetic Testing & Personalised Medicine PDF

Genetic testing & Personalised Medicine : Ethical, social, and regulatory challenges Professor Barbara Prainsack Department of Global Health & Social Medicine Overview: I. Genetics & society: 1. Who talks about it? 2. What is being said? 3. Hot topics II. Personalised/Precision...

Genetic testing & Personalised Medicine : Ethical, social, and regulatory challenges Professor Barbara Prainsack Department of Global Health & Social Medicine Overview: I. Genetics & society: 1. Who talks about it? 2. What is being said? 3. Hot topics II. Personalised/Precision Medicine (PM) 1. History 2. Transition from genetics/genomics to PM 3. Challenges III. Conclusions Genetics and society Genetics & society: 1. Who talks about it? 2. What is being said? 3. Hot topics Who talks about it? A. Medical ethics - initially mostly philosophers and physicians - Codifications: Nuremberg Code 1949, Declaration of Helsinki 1964, etc. B. Bioethics - Human Genome Project: 3-5% of funding dedicated to ELSI (Ethical, Legal, and Social Implications) Who talks about it? C. Social Sciences - Exploration of political, social, and individual conditions and practices that shape which new fields of science and technology are adopted by societies - Initially great reservations against normative stances What is being said? Main themes: (1) Identity (2) Justice (3) Participation (1) Identity 1990s: ‘Geneticisation’ of society (A. Lippman 1991) 2000s: ‘Englightened geneticisation’ (A. Hedgecoe 2001) ‘Biosociality’ (P. Rabinow 1996) Davos, 1912 1924 “it is not hard to imagine groups formed around the chromosome 17, locus 16,256, site 654,376 allele variant with a guanine substitution” [Rabinow, Paul 1996 “Artificiality and enlightenment: from sociobiology to biosociality.” Essays on the anthropology of reason (Princeton: Princeton University Press).] Davos, 2008 World Economic Summit (1) Identity Empirical studies have shown: (1) People often integrate genetic information into existing identities and narratives (2) The growing proliferation of genetic predisposition testing (incl. online testing) for complex diseases does not seem to have an effect on people’s behaviour (3) We have no good data on the effect of identities and long-term strategies (1) Identity 2010s: A. Focus on negative effects: Patients-in-Waiting (Timmermans & Buchbinder 2010) pre-patients B. Focus on positive aspects: P4-medicine: participatory, personalised, preventive, predictive (Hood) C. Positive and negative aspects: somatic individuality (Novas &Rose 2001) situated dis/empowerment (Prainsack & Toom 2010) (2) Justice - Deborah Stone: The ‘chocolate cake‘ problem of justice - Just resource allocation is one of the core concerns of bioethics, but also health policy, research policy, and social policy (2) Justice Some key topics and insights: - Risk: People in lower socio economic groups have higher health risks (aka ‘health gap’, Michael Marmot); - Discrimination: Fear of genetic discrimination; underserved groups (e.g. some minorities) - Individualisation of duties and responsibilities: Concern about costly predictive tests with little or no clinical utility; debate on ‘lifestyle solidarity’ - Is the end of genetic exceptionalism near? [M Powers & R. Faden (2006). Social Justice: The Moral Foundations of Public Health and Health Policy. New York: Oxford University Press.] [A. Buyx & B. Prainsack (2012). Lifestyle-related diseases and individual responsibility through the prism of solidarity. Clinical Ethics 7/2: 79-85] (3) Participation - Hans Jonas (1903-1993): Doctors are alone with their patients and with God - Since WWII the scope of legitimate expertise and authority of physicians has been shrinking - Increasing emphasis on patient participation since the mid 20th century: Patient and public involvement (PPI), shared decision making, ‘citizen science’ etc. (3) Participation 2010s: Growing possibilities to generate and analyse health-related data outside of the clinic (beyond-the-clinic, BTC): data generation (e.g. online genetic testing) data analysis (e.g. “Cure Together”) Patients participate in: Datengeneration Analyse Interpretation Translation Personalised Medicine & Precision Medicine (PM) Personalised Medicine: - Initially, focus on matching drug treatments to groups with certain genetic markers - Later on, more inclusive of wider, non-genetic/genomic data Critique of Personalised Medicine Alternative concepts: (1) Stratified Medicine: Mostly used in connection with pathophysiology and treatment http://www.ncbi.nlm.nih.gov/pubmed/18999921 (2) Precision Medicine: FDA, since 2009. Link to data-rich medicine, and medicine beyond the clinic http://www.nap.edu/catalog.php?record_id=13284 (3) Individualisation Forward Look on ‘Personalised Medicine of the European Citizen’, individualisation European Science Foundation (ESF), 2011- 2012 Personalised http://www.esf.org/uploads/media/ Personalised_Medicine.pdf Medicine Stratified medicine Blockbuster medicine To avoid overemphasis on genomics, define PM as considering individual characteristics at every stage, prevention, diagnosis, treatment, monitoring - this corresponds strongly with the concept of Precision Medicine which originated in the US [© National Academy of Sciences, 2011] Where do the data for PM come from? (1) Use of data from medical science and research (2) Quantification of information that is in the clinical domain (3) Integration of new data originating outside of the scientific and clinical domain. Sources: commercial actors; NAS 2011 smartphone apps; patient support websites (e.g. curetogether.com) Expansion of social, legal, ethical challenges to wider datasets [Weber et al. 2014] Main ethical/social challenges: Genetic testing / PM: Autonomy (right to know, right not to know) Rights and interests of family members Data protection Avoiding discrimination Effect on identities Conclusion: PM: Ethical, social, regulatory challenges 1. Implications of data-rich PM: More emphasis on collaboration; new distribution of power, expertise, agency 2. data moving from public to health domain (and vice versa); data analysis has become a market 3. Vision of PM relies on patients contributing data – willingly or unwillingly PM: Ethical, social, regulatory challenges 4. Does the emphasis on molecular and digital data “crowd out” other types of evidence? 5. How can we include things that are meaningful to patients into personalised medicine? 6. Who should be the gate keeper of personal health repositories? 7. Who controls algorithms? PM: Ethical, social, regulatory challenges 8. ‘Filter bubble effect’ 9. Social exclusion  Thank you for your attention! If you have questions or comments, contact me at: [email protected]