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.
Yong Xiao Wang
Albany Medical College, United States
F Buck Willis
Christian College of Medicine, Belize
Amy Gutman
AdventHealth; Tough Love MD, United States
Sujith Rajan
NYU Long Island School of Medicine, United States
Anil Harrison
Midwestern University, United States
Jun Dai
Des Moines University, United States
David Petch
utR Biotech, CanadaSubmit your abstract Today
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