Advances in precision medicine and personalized diabetes care are revolutionizing treatment strategies by tailoring interventions based on genetic, metabolic, and environmental factors. Unlike conventional one-size-fits-all approaches, personalized therapies utilize genetic markers, continuous glucose monitoring, and artificial intelligence to predict individual responses to treatment. Pharmacogenomics plays a crucial role in determining optimal drug efficacy and minimizing adverse effects, while lifestyle interventions are customized to enhance insulin sensitivity and metabolic health. Additionally, machine learning algorithms refine predictive analytics, identifying high-risk patients and optimizing preventive strategies. By integrating molecular profiling with real-time health data, precision medicine is paving the way for more effective and sustainable diabetes management.










Title : Vascular health with glucagon-like peptide-1 receptor agonists
Mahir Khalil Ibrahim Jallo, Thumbay University Hospital
Title : The prowess of Overripe Banana Sweetener (OBS) in enhancing nutritive values in food and ameliorating glycaemic responses in type 2 diabetes mellitus
Wan Rosli Wan Ishak, Universiti Sains Malaysia
Title : An intelligent hierarchical medical platform established upon high-quality datasets improves the effectiveness of glycemic management for patients across different levels of hospitals
Zhiheng Zhou, Southern Medical University
Title : Diabetes pathogenesis and prevention
Madhu S Malo, Stapgen LLC
Title : Effects of a structured education program on glycemic control in type 1 diabetes
Ana Paula Franco Pacheco, Estacio University of Brasília
Title : Differential diagnosis of diabetes in young and prevalence of LADA and LADY in young persons attending tertiary diabetes institute in Bengaluru, India
R Anil Kumar, Karnataka Institute of Endocrinology and Research
Title : Association between diabetes technology use and prevalent macrovascular disease in adults with type 1 diabetes: A cross-sectional analysis
Divanshi Trivedi, London Northwest Hospital NHS Foundation Trust
Title : Endocrine-specific diabetes risk modeling, glucose–insulin dynamics, and simulation-based metabolic review using the BVidAL clinical software suite
Abhishek Bansal, New Era Consultancy Services
Title : Using a multi-disciplinary clinic model to prevent diabetic foot ulcer recurrence
Kaishi Yang, Albert Einstein College of Medicine
Title : Shaping the future of diabetes care: New advancements in treatment, digital health and personalized patient care
Rupesh K Gautam, Amity Institute of Pharmacy