Cancer research has become extraordinarily good at finding new treatments, but we remain far less sophisticated at determining who should receive them.
Patient selection must become as important as drug development itself. Otherwise, we risk giving powerful medicines to patients who cannot benefit while overlooking the people for whom those same medicines could be transformative.
This matters because cancer does not behave according to averages. Two patients can have the same diagnosis and respond completely differently to the same therapy.
Yet much of oncology still asks the broad question: Does the drug work? We need to ask another question with equal urgency: For whom does it work?
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Technology Networks reported that precision approaches are increasingly guiding treatment decisions, clinical-trial design, and drug development from the earliest stages.
In the OPTIMA trial, genomic testing identified a group of patients aged 40 and over with hormone-sensitive, early-stage breast cancer who could potentially avoid chemotherapy without materially compromising outcomes.
Around 68 percent of participants had a low Prosigna score, and five-year outcomes in that group were similar with or without chemotherapy.
This illustrates how more precise patient selection can reduce unnecessary treatment and its associated toxicity.
But having more data does not necessarily mean understanding cancer better. Despite these advances, some treatment decisions still rely on a limited set of biomarkers that may not capture the full complexity of a tumor.
A tumor is not a single switch. Its biological chain runs from DNA to messenger RNA to proteins, and much of what DNA makes possible never becomes an actual cellular function.
DNA reveals much of a tumour's genetic potential, while RNA can provide additional information about which genes are being expressed.
The more faithfully we capture that biology, the better positioned we are to understand why one patient responds while another does not.
Missing Opportunities
Getting that distinction wrong has consequences far beyond a disappointing trial result. When a patient receives a treatment that has little chance of working, they may experience toxicity without therapeutic benefit while the cancer continues to grow.
As tumors evolve, they can develop additional mechanisms of resistance. For a patient with advanced disease, lost time is not an abstract cost. It can mean losing the opportunity to try something that might have worked.
The waste also spreads throughout the healthcare system. Every ineffective treatment consumes money, clinical capacity, hospital resources, and a patient’s limited time.
Every clinical trial that averages away a genuine responder population risks discarding a therapy that could have helped a specific group.
We could spend billions discovering new medicines while failing to unlock the full value of medicines we already have.
Patient Selection
Addressing this problem requires changing when and how we think about patient selection. Drug developers should build patient-selection strategies into development from the beginning, rather than retrofitting them after disappointing results.
Clinical researchers should design trials capable of identifying meaningful responder populations, not simply measuring population-wide averages.
Hospitals should preserve tumor samples, molecular information, and detailed outcome records so those data can fuel better predictive tools tomorrow.
Healthcare leaders, too, should demand the same precision in treatment decisions that they demand in the science behind the treatments.
Encouragingly, the field is beginning to move in that direction. Biomarkers are increasingly moving beyond patient stratification to actively influence treatment decisions and early-stage development.
If that momentum continues, precision oncology can become more than a way to classify patients. It can become the foundation of a healthcare system in which a patient does not have to spend precious months discovering that a treatment was never likely to work.
Their tumor is analyzed more deeply, their therapy is selected according to its biology, and unnecessary toxicity is avoided.
Clinical trials become smaller and smarter. Promising drugs are less likely to be discarded because their benefit was hidden inside an average, and healthcare resources go toward treatments that have a real chance of helping.
That is the promise of precision oncology: not simply more treatments, but better decisions about who should receive them.
Thomas H. Jensen is CEO of Allarity Therapeutics, which is developing a cancer treatment and proprietary companion diagnostic. All the views expressed in this article are his own.