Pennsylvania is into one of the heaviest cancer years in its history. The American Cancer Society projects 90,250 new cancer cases and 27,630 cancer deaths in the state in 2026, part of a national forecast of roughly 2.1 million new cases and about 1,700 cancer deaths every day.
Cancer remains the second leading cause of death in the United States, and behind each number is a physician making a high-stakes decision, often for a patient whose tumor is rare, aggressive, or already resistant to the first therapies tried against it. For those patients, one question is unavoidable: is a treatment chosen because it usually works on others, or because it will work for this person?
Even Precision Medicine Still Makes a Prediction
Cancer care has advanced on a foundation of prediction. The standard of care, population-based protocols validated in large clinical trials since the 1950s, predicts what should help the average patient. Molecular precision medicine narrowed that lens by sequencing a tumor’s DNA and matching mutations to targeted drugs, and it has been transformative for some cancers. But it remains a prediction: a genomic report estimates how a tumor is likely to respond, not how it actually will. Its reach is also limited. Even by 2020, an estimated 7 percent of U.S. cancer patients were projected to actually benefit from genome-targeted therapy. A mutation does not guarantee a response, and many aggressive or treatment-resistant tumors carry no actionable target at all. For most patients, precision medicine still leaves the clinician predicting—and hoping.
Functional Precision Medicine Validates What Others Predict
Functional precision medicine bridges the gap that prediction leaves open. Rather than inferring a response from genetics, it validates therapies against the disease itself. A patient’s living cancer cells, obtained by biopsy, are exposed directly to hundreds of FDA-approved drugs, and each drug’s effect is measured: actual sensitivity and resistance, not an estimate. The tumor itself, not an algorithm’s forecast, reveals which agents kill it. That is the difference between what a mutation suggests and what a drug does, and functional testing routinely surfaces effective options that molecular profiling alone overlooks. For a tumor that carries no targetable mutation, the shift is decisive: it turns an empty genomic report into a ranked list of drugs the cancer has already shown, in the laboratory, that it cannot withstand.
The evidence is maturing quickly. In children with relapsed or refractory cancers, among the hardest cases in oncology, it returned actionable treatment recommendations for most patients, often faster than genomic sequencing alone, frequently pointing to drugs that sequencing had not flagged.
AI Turns Testing Into a Timely Decision
Exposing a tumor to hundreds of drugs produces far more data than any clinician can weigh by hand, and this is where artificial intelligence becomes decisive. AI-enabled clinical decision support ranks the therapies a patient’s cancer is most sensitive to, flags effective combinations, and delivers that analysis in a clinically actionable timeframe—in days, not weeks—that can decide the outcome of an aggressive cancer. The physician still makes the call, but now from direct evidence rather than population averages, which lowers risk and raises confidence in precisely the rare, aggressive, and treatment-resistant cases where confidence is hardest to find.
The approach is drawing serious institutional attention. The American Society of Clinical Oncology (ASCO) has issued a clinical notice clarifying the status of functional precision medicine, a sign that professional oncology is actively defining where it fits and insisting its adoption be grounded in rigorous evidence.
From “Try and Hope” to “Test and Treat”
None of this replaces the standard of care; it completes it. Population-based medicine remains the essential foundation, but advances in biology, laboratory automation, and artificial intelligence now make it possible to personalize treatment at scale—to confirm, for an individual patient, what prediction can only suggest.
For Pennsylvania’s tens of thousands of newly diagnosed patients, and the physicians shouldering those decisions, the shift is profound: from choosing therapy by prediction to validating it by observation, from try-and-hope to test-and-treat. As the state’s cancer burden climbs, closing that gap is the difference between an average answer and the right one.
Raymond Rodriguez-Torres
Raymond Rodriguez-Torres is President of First Ascent Biomedical, a functional precision oncology company. A healthcare executive with more than two decades of leadership across the global pharmaceutical and biotechnology industry, he has held senior commercial roles at companies including Genentech, Roche, and Sanofi. He is also the chairman and founder of the Live Like Bella Childhood Cancer Foundation, which he established in memory of his daughter, and an author and speaker on resilience in the face of cancer. His work focuses on making personalized, biology-driven cancer care more accessible to patients and physicians.
