Journal of Advances in Medical and Pharmaceutical Sciences

Genomic medicine depends on reference data, biobanks and association studies that remain dominated by participants of European ancestry, while Native, Aboriginal and Tribal peoples continue to be scarcely represented. This imbalance limits variant interpretation, pharmacogenomic prescribing and polygenic prediction for communities that already carry disproportionate burdens of disease. Calls for wider inclusion, however, collide with a history of extractive sampling, secondary use without consent and stigmatising publication, and with Indigenous assertions of collective rights over biological samples and data. This critical narrative review examines how Indigenous peoples have been included in, excluded from and have shaped genomic medicine and biorepository research, and appraises the governance instruments and guidelines that now regulate that participation. Literature published from 2000 onwards was identified through biomedical and multidisciplinary scholarly databases, citation tracking and the official websites of standard-setting bodies, and was appraised qualitatively for relevance, methodological transparency, community partnership and contribution. The synthesis indicates that under-representation is well documented and has measurable clinical consequences, including more variants of uncertain significance, reduced polygenic score accuracy and incomplete pharmacogenomic coverage. Empirical studies of attitudes show conditional rather than absent willingness to participate, with support depending on community governance, local benefit and control over secondary use. Governance has moved from individual informed consent towards collective oversight, tribal research codes, data sovereignty principles and Indigenous-led biobanks, yet these instruments are unevenly enforceable and largely confined to a few high-income settler states. Evidence from Africa, Latin America, South and Southeast Asia and the Arctic is thin, and outcome evaluations of governance models are almost absent. Important unresolved questions concern whether inclusion within national datasets serves Indigenous interests, how benefit sharing can be made concrete, and how ancestry-associated risk can be studied without biologising inequities that have social causes. Equitable Indigenous genomic research appears to require durable community authority over samples and data, investment in Indigenous scientific capacity and prospective evaluation of whether partnership models deliver health benefit.