A NEW FRONTIER IN PRECISION ONCOLOGY: ARTIFICIAL INTELLIGENCE, LIQUID BIOPSY, AND MOLECULAR BIOMARKERS IN EARLY CANCER DETECTION, THERAPEUTIC PERSONALIZATION, AND ADDRESSING HEALTH INEQUALITIES

Abstract

Precision oncology has expanded opportunities for cancer diagnosis, monitoring, and treatment by integrating molecular information, digital technologies, and individual patient characteristics. In this context, artificial intelligence, liquid biopsy, and molecular biomarkers have the potential to transform oncology practice by supporting the identification of tumor alterations, the selection of targeted therapies, and the monitoring of treatment response. This study aims to analyze the contributions of these technologies to early cancer detection and therapeutic personalization, considering their scientific, clinical, and socioeconomic challenges, particularly those related to inequalities in access to healthcare services. This is a bibliographic and documentary review with a qualitative, descriptive, and exploratory approach, based on scientific publications and institutional documents addressing precision oncology, molecular diagnosis, and technological innovation. The literature indicates that artificial intelligence algorithms may support the interpretation of medical images and genomic data, while liquid biopsy enables the investigation of circulating tumor components through minimally invasive procedures. Molecular biomarkers contribute to identifying alterations associated with tumor behavior and potential responses to specific treatments. However, the clinical application of these tools still faces limitations involving clinical validation, test sensitivity, methodological standardization, data protection, and implementation costs. Furthermore, differences in healthcare infrastructure and the availability of specialized testing may exacerbate inequalities across populations and regions. It is concluded that integrating these technologies represents a promising direction for oncology, but their benefits depend on robust clinical evidence, professional training, and public policies that promote equitable access to innovation.