1 Pharmacogenomics and American Indian Populations: Drug Development in the Context of Health Disparities Morris W. Foster, Ph.D. Department of Anthropology.

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Presentation transcript:

1 Pharmacogenomics and American Indian Populations: Drug Development in the Context of Health Disparities Morris W. Foster, Ph.D. Department of Anthropology University of Oklahoma 12 th Annual Summer Public Health Research Videoconference on Minority Health

2 The promise of personalized medicine Will it really be individualized?

3 Instead of customized therapies for individuals, pharmacogenomics may just re-arrange the way in which the economics of drug development are calculated, using both historical and marker-based groupings to determine potential markets.

4 Existing social groups will be characterized by differing frequencies of variants that promote drug response, while new groupings will be based on the presence or absence of those variants.

5 To the extent that frequencies of those variants differ by social identity, existing health disparities may be exacerbated by the ways in which pharmacogenomic drug development plays out, while additional disparities may be created among those assigned to new, marker-based groups.

6 This may result in two kinds of pharmacogenomically-relevant groupings: (1) social groups that are genetically stereotyped (that is, differences in frequencies are misunderstood as the presence or absence of a variant among all group members), and

7 (2) genotyped groups that are socially identifiable.

8 Although not a pharmacogenomic drug, Bi-Dil is an example of the way in which identity-based disparities in the relative frequency of disease incidence and drug response can drive drug development and marketing.

9 The pre-existence of health disparities may shape the ways in which pharmacogenomic drug development is mapped onto social groups.

10 How might the science of pharmacogenomics play out across a landscape of social differentiation and health disparities?

11 American Indian/Alaska Native (AI/AN) populations make an interesting model for the groups that may be affected or created by that intersection of science and society.

12 AI/AN Populations % of total U.S. population (approx. 4.5 million people) 1.5% of total U.S. population (approx. 4.5 million people) 1.9 million of whom receive their primary health care through IHS 1.9 million of whom receive their primary health care through IHS Significantly lower life expectancy and significantly higher rates of heart disease, diabetes, etc. Significantly lower life expectancy and significantly higher rates of heart disease, diabetes, etc.

13 AI/AN Populations - 2 Almost twice the percentage of households below poverty as the general population Almost twice the percentage of households below poverty as the general population Diversity of specific ancestries (including European and African) Diversity of specific ancestries (including European and African)

14 Distribution of the benefits of pharmacogenomics depends both on population genetics and market economics.

15 Do common drug response variants found in other populations also exist in AI/AN populations? – Yes, as will be the case in all populations.

16 Do some otherwise rare drug response variants occur at higher frequencies in AI/AN populations? – Probably, as again will be the case in all populations.

17 Do those otherwise rare variants occur at different frequencies between tribal- and village-specific populations? – Probably.

18 When will we learn the answers to the previous three questions? – Probably after we learn similar information for other populations, due in part to internal cultural reasons and in part to external economic reasons.

19 Pharmacogenomics is itself the construction of a particular cultural context, and there will be barriers to its use when transferred to other cultural contexts, with respect both to world view and to historical relationships with the culture that created the technology.

20 Like many other populations that experience health disparities, AI/AN populations have a lesser economic capacity to: (1) attract investments in targeted drug discovery and (2) pay for access to cutting-edge diagnostics and drugs.

21 If common genetically targeted drugs do apply, it is likely that many tribal health facilities and tribal members will be unable to afford the diagnostic tests and what will probably be the higher costs of new drugs.

22 If otherwise rare drug response variants exist at higher frequencies for some AI/AN populations, will drug companies “personalize” therapies for those variants?

23 Whether or not AI/AN populations are pharmacogenomically unique, existing health disparities will be compounded by the advent of pharmacogenomics.

24 If otherwise rarer variants exist at higher frequencies for some members of some AI/AN populations, will this contribute to a perception that AI/AN people generally respond differently to drugs? That is, will differences in frequency be translated as presence or absence?

25 Does the basis for that perception already exist due to health disparities between AI/AN populations and others?

26 The IHS, for example, can be conceptualized as an example of ancestry-based medicine.

27 If pharmacogenomic drugs are provided or developed for AI/AN people through that identity- specific lens, the potential for confounding the social and the biological is considerable.

28 At the same time, the economic, cultural, and other challenges that AI/AN people face in having access to pharmacogenomic benefits may most effectively be addressed through the identity portal.

29 For example, the most effective argument for developing drugs targeted to response variants that are disproportionately found in AI/AN populations is probably that of a shared AI/AN identity, not a shared genotype among those individuals affected.

30 The ideal solution may be to insist on an identity-neutral pharmacogenomics. But is that goal as unrealistic as truly personalized medicine?

31 The engagement between pharmacogenomics and historical, social groups and identities may be unavoidable.

32