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Despite decades of progress in oncology, ranging from molecular diagnostics to targeted therapies, cancer remains one of medicine’s most complex and costly challenges. While genomic sequencing and AI-assisted analytics have improved disease classification, biomarker identification, and the discovery of drugs that may help, most patients are still treated using standardized protocols driven by population-level data rather than individual tumor behavior. As cancer incidence is projected to rise sharply in the coming years, this trial-and-error approach is increasingly unsustainable for providers and healthcare systems alike and is quickly becoming unacceptable for patients.
A new class of technology, AI-driven Functional Precision Medicine (FPM), is emerging to address this gap. By combining patient-derived tumor biology with advancements in proprietary cell enrichment processes, automation, robotics, and artificial intelligence, FPM platforms enable oncologists to rapidly test how an individual patient’s cancer responds to hundreds of FDA-approved drugs and combinations, delivering ranked treatment options within days.