Personalized medicine is transforming healthcare by tailoring medical treatment to individual characteristics, behaviors, and genetics. However, what is needed today is a framework with a sophisticated structure to integrate the entire clinical trial lifecycle that can improve the efficiency of workflows in biological research. This study presents the design and development of a three-layered intelligent cyber-biological system (ICBS), each one designed to improve the efficacy and precision of clinical trials: a Data/Information level for data collection and standardization, an Intelligent level for data analysis using artificial intelligence models to identify patterns and insights, and a Reasoning level to apply the knowledge gained in clinical trials and therapy design, enhancing efficiency and effectiveness in personalized medicine. The implementation of the three-layered ICBS in the glycation classification case study has proven both feasible and effective. The results showed a marked enhancement in the efficiency of experimental procedures and predictive accuracy, proving the efficacy of ICBS in real-world practical biomedical research scenarios.