Maturing pharmacogenomic factors deliver improvements and cost efficiencies

Abstract

An ever-expanding annotation of the human genome sequence continues to promise a new era of precision medicine. Advances in knowledge management and the ability to leverage genetic information to make clinically relevant, predictive, diagnostic, and targeted therapeutic choices offer the ability to improve patient outcomes and reduce the overall cost of healthcare. However, numerous barriers have resulted in a modest start to the clinical use of genetics at scale.Examples of successful deployments include oncologic disease treatment with targeted prescribing, however, even in these cases, genome informed decision making has yet to achieve standard of care in most major health care systems. In the last two decades, advances in genetic testing, therapeutic coverage, and clinical decision support have resulted in early-stage adoption of pharmacogenomics-the use of genetic information to routinely determine the safety and efficacy profile of specific medications for individuals. Here, via their complicated histories, we review the current state of pharmacogenomic testing technologies, the information tools that can unlock clinical utility, and value-driving implementation strategies that represent the future of pharmacogenomics enabled healthcare decision-making. We conclude with real-world economic and clinical outcomes from a full-scale deployment and ultimately provide insight into potential tipping points for global adoption, including recent lessons from the rapid scale-up of highvolume test delivery during the global SARS-CoV2 epidemic.

Introducing Cambridge prisms: Precision medicine

“…Collaboration across academia, health service delivery systems, and industry, frequently called a triple helix partnership, is essential. It must include pharmaceutical, digital, and artificial intelligence companies as well as heathcare device manufacturers to be effective in delivering clinical utility, laboratory technology, user acceptance, implementation models, and economic value to the field (Jarvis, 2023 ).…”