Pharmacogenomics articles from across Nature Portfolio

Innovative pharmacogenomic approaches (genetic variation related to medication response) are needed to reduce disease and disparities in Indigenous communities. We support community-based pharmacogenomics research, inclusive of Indigenous values and priorities, to improve the health and well-being of Indigenous peoples.

Indigenous peoples are under-represented in genomic datasets, which can lead to limited accuracy and utility of machine learning models in precision health. While open data sharing undermines rights of Indigenous communities to govern data decisions, federated learning may facilitate secure and community-consented data sharing.

The Pharmacogenomics Access & Reimbursement Symposium, a landmark event presented by the Golden Helix Foundation and the Pharmacogenomics Access & Reimbursement Coalition (PARC), was a one-day interactive meeting comprised of plenary keynotes from thought leaders across health care that focused on value-based strategies to improve patient access to personalized medicine. Stakeholders including patients, healthcare providers, industry, government agencies, payer organizations, health systems and health policy organizations convened to define opportunities to improve patient access to personalized medicine through best practices, successful reimbursement models, high-quality economic evaluations, and strategic alignment. Session topics included health technology assessment, health economics, health policy, and value-based payment models and innovation.

Given that it is based on heredity and has the ability to trace connections, genetics as a scientific discipline should be among those most attuned to diversity and global perspectives. Indigenous communities and scientists have much to contribute to genetics research, and they are making their voices heard. We celebrate these essential members of our larger genetics community, and we look forward to working together to learn from past examples, meet present challenges and support future opportunities.

Despite the previous identification of genes involved in the treatment response to TNF inhibition in rheumatoid arthritis, no genetic biomarkers are currently used in clinical decision-making. Might the heterogeneous nature of the disease activity score, which is often used as the outcome measure in genetic studies, partly explain this gap?