Advancing functional treatment prediction for precision oncology.

Abstract

Personalized cancer treatment requires stratification of patients based on biomarkers. Despite advances in biomarker-guided therapy, biomarkers are not always available or sufficient to predict treatment responses in individual patients. Functional ex vivo cancer models with the potential to assess therapeutic outcomes upfront have been developed but have not been implemented in clinical practice-despite accumulating evidence of their clinical relevance. This review describes how three essential steps in the development of personalized functional prediction tests (analytical validity, clinical validity, and clinical utility) should be combined in a multidisciplinary approach: Integrated Translational Co-design. This approach front-loads clinical utility and validation constraints into early analytical design decisions, so that biological fidelity, clinical implementation, and healthcare costs can be optimized from the start of assay development.