Cardiovascular disease: the other face of diabetes

Area of Science:

• Pharmacometrics and Systems Pharmacology
• Translational Medicine
• Cardiovascular Risk Assessment

Background:

• Despite achieving glycemic control, patients with diabetes mellitus continue to experience high rates of mortality and morbidity.
• Regulatory agencies require extensive safety trials for new antidiabetic medications.
• Current limitations include the absence of reliable cardiovascular risk markers for predicting drug response.

Purpose of the Study:

• To address the need for predictive markers in antidiabetic drug development.
• To establish a model-based approach for assessing the link between hyperglycemia and cardiometabolic phenotypes.
• To enable the prediction of underlying cardiovascular risk in diabetic patients.

Main Methods:

• Development of a systems pharmacology model.
• Integration of glucose-insulin homeostasis data.
• Correlation analysis between hyperglycemia and cardiometabolic phenotypes.

Main Results:

• The study proposes a novel model-based strategy.
• This approach facilitates the assessment of hyperglycemia's impact on cardiometabolic health.
• It enables prediction of cardiovascular risk, offering a potential surrogate marker.

Conclusions:

• A model-based approach is crucial for understanding the complex relationship between hyperglycemia and cardiovascular risk in diabetes.
• This methodology can aid in identifying patients at higher risk and guide the development of safer antidiabetic therapies.
• Further research in this area is warranted to refine predictive models and improve patient outcomes.