Integration of Data-Driven Techniques in Nanomedicines to Address Diagnosis and Drug Delivery Strategy for Therapy

The progress of drug designing, drug delivery systems (DDS), and disease diagnostic systems has significantly advanced pharmaceutical development, as evidenced by the FDA-approved nanomedicines with enhanced selectivity, controlled release, and synergistic therapeutic effects. However, the design and large-scale development of nanomaterial-based DDS remain challenging due to difficulties in managing and analyzing complex experimental data. The integration of data-driven techniques, high-throughput experimental networks and protocols, automation, artificial intelligence (AI), and machine learning (ML)-a framework known as the fourth paradigm of scientific research that offers a promising solution. This review article highlights milestones in applying these technologies to biomarker-based diagnosis and DDS, including nanomaterial design, and explores their potential to accelerate drug development and clinical translation. It also outlines the future prospects or directions for leveraging these approaches to create highly efficient, customizable nanomedicines and smart materials with defined physicochemical properties, aiming to benefit researchers in materials science, nanotechnology, and biomedical DDS development.