This presentation will position personalized medicine at a turning point where genomic tools must be translated from discovery into everyday clinical care. I will discuss how I believe this transition requires new models of clinical research, ethics, health economics, and information systems that can handle multigene data, real-world variability, and patient-centered implementation.

I will discuss why I believe side effects and variability in drug response should be treated as core scientific signals, driving the discovery of genomic markers and “double-preventive” strategies that prevent both disease and drug-induced complications. I recommend focusing on multigenic, array-based diagnostics and on integrating genetics with lifestyle, environmental factors, and primary care workflows to make personalized medicine clinically actionable.

I will discuss how I believe ethical frameworks must stratify informed consent according to clinical risk, protect privacy while enabling pharmacogenetic testing, and move beyond traditional race categories toward genetically informed population definitions. I recommend developing new intellectual property, reimbursement, and outcomes research models so that personalized medicine becomes a sustainable, reimbursed standard of care rather than a niche or experimental approach.

Learning Objectives:

1. Identify History of the concept: personalized medicine vs. healthcare

2. Discuss the Technology and Clinical Decision Support

3. Recognize business models in personalized medicine.