Molecular Oncodiagnostics in Precision Oncology: Integrating Tumor Transcriptomics, Patient Pharmacogenetics, and Ex Vivo Chemoresistance Testing to Improve Individual Chemotherapy Response

Precision oncology has matured into a multidimensional field in which static molecular profiling — encompassing genomic, transcriptomic, and other omic data — is increasingly complemented by dynamic functional assays that measure direct tumor responses to therapeutic agents. While molecular diagnostics provide critical insights into cancer biology and potential drug targets, they do not always predict real-world therapeutic efficacy, especially in tumors characterized by high heterogeneity or complex regulatory networks. Functional ex-vivo testing platforms, including patient-derived organoids and tumor slice cultures, offer a phenotypic readout of drug resistance that reflects the integrated behavior of tumor cells within their microenvironment. This review synthesizes the technological advances and practical frameworks that support the integration of multi-omic and ex-vivo data in precision oncology. We present the current landscape of predictive modeling and functional validation, including workflows that move from transcriptomic and pharmacogenetic prediction toward rapid ex-vivo confirmation of drug effects, and discuss how such integrative approaches can refine therapeutic choices. We describe clinical implementation pathways, highlight operational and regulatory challenges, and explore ethical considerations that must be addressed to bring functional precision medicine into mainstream practice. By examining clinical feasibility, existing trial evidence, and emerging platforms, we highlight both the opportunities and barriers inherent in translating functional testing into routine care. Finally, we consider future directions aimed at achieving standardized, scalable, and clinically validated functional diagnostics. The integration of molecular and functional insights offers a promising route toward more accurate, individualized cancer therapy, and suggests a future in which treatment selection is guided not only by molecular signatures but by direct functional evidence of drug efficacy.