Overview

Key messages:

Personalized medicine tailors interventions to an individual patient’s genetics and context.

1. The process of understanding an individual's genetic and molecular makeup is expensive but does not lead exclusively to high-cost treatments. It can enable targeted prevention and more cost-effective treatment selection.
2. Personalized medicine requires huge amounts of personal (genomic) data, which can only be collected and managed effectively if there is trust, appropriate infrastructure and training.
3. Strong, transparent governance can balance the needs of patients and research, build trust and encourage the sharing of personal health data for the public good.
   • Good regulation ensures confidentiality for individuals and protects them against data-driven discrimination.
   • Acknowledging the ethical, legal and social dimensions of personalized medicine, and involving the public, fosters confidence.
   • Participatory consent, opt-outs and new dynamic models reassure the public and can help overcome gaps in health literacy, but depend on clear communication.
   • Increasing cybersecurity is also important.
4. The European Commission is striving to give citizens control over their data, while enabling advances in research and personalized care.
5. Investing in infrastructure, as well as in appropriate accreditation and quality control, is critical.
   • Biobanks enable the study of biomarkers but must be seen as trustworthy.
   • Genetic sequencing and biomolecular diagnostics are prerequisites for translating research into clinical practice.
   • High-quality, interoperable electronic health record systems will be crucial to research and in delivering personalized approaches.
   • New testing facilities and new clinical decision support tools are also key but require careful validation, particularly where they use artificial intelligence.
6. Training in new technologies and for the new professional roles they create will be important.
   • Clinicians need specific skills and ethical awareness to navigate the complexities of personalized approaches and to work across disciplines.
   • Training will need to combine specialist skills in genomics, digital health, data management and ethics with cross-cutting competencies, such as communication and collaboration.
7. The costs of advanced therapies and diagnostics are a challenge.
   • Collaboration amongst stakeholders, innovation in trial design and an expanded use of real-world data can improve evidence for pricing and reimbursement models.
   • Early dialogue between manufacturers, regulators and health technology assessment bodies, plus increased collaboration and knowledge sharing public–private or public–public collaboration across EU Member States, may help in finding sustainable solutions.
   • Flexible reimbursement frameworks, such as managed entry agreements, may help balance financial sustainability with patient access and innovation.