Over the past two decades, cancer care has been transformed by advances in tumor biology and molecular science. These advancements have uncovered oncogenic driver mutations that propel the uncontrolled growth of specific types of cancer, leading to the development of targeted therapies designed to block these molecular pathways. Once considered experimental, broad-panel genomic and transcriptomic sequencing are now standard of care for most patients with advanced malignancies. As a result, most patients are assessed for known driver mutations and targeted treatment.
These breakthroughs have ushered in the era of precision medicine—the ability to match each patient’s tumor with therapies most likely to be effective based on its unique molecular profile. Precision medicine has revolutionized the “what” of cancer treatment: identifying what therapy is best for the patient’s tumor.
But the next challenge lies in addressing the “who”—the individual living with cancer.
While tumor biology determines which drugs may work best, a patient’s lived experience influences whether those drugs are taken consistently and tolerated long enough to provide full benefit. Adherence to oral cancer therapy is determined by far more than pharmacology and tumor genetics. It is a complex interplay of motivation, emotional resilience, side effects, financial pressures, social support, and comorbid conditions. For oncologists, the challenge is not only to prescribe the right therapy, but to ensure that the person prescribed that therapy can and will take it regularly.
This is where the transition from precision medicine to personalized medicine begins.
Technology—guided by behavioral science—will help bridge this gap. Modern AI systems can analyze data from a variety of sources, including electronic health records, wearable devices, and patient-reported outcomes, to identify subtle patterns that reveal who might struggle most to stay on therapy. These tools can forecast risks such as early treatment discontinuation, missed doses, or unmanaged toxicity—often before these issues are clinically apparent.
Once a patient is identified as high-risk, preventive interventions can be deployed. Personalized medication coaching, digital engagement, and supportive therapies can be used to help patients stay engaged in their care. By combining predictive analytics with a human touch, healthcare teams can move from reacting to major toxicity issues after they occur to preventing them altogether.
The impact of this approach extends beyond adherence. When patients feel supported, understood, and empowered, they experience improved quality of life, reduced treatment-related distress, and stronger therapeutic alliances with their care team. Clinicians benefit as well—through better outcomes, fewer unplanned treatment interruptions, and deeper insight into the patient experience.
The future of oncology will not be defined solely by the discovery of new molecular targets, but by our ability to align scientific precision with human personalization.
In this evolution, precision medicine provides the foundation for a promising future—but personalized medicine will deliver on that promise.
