Microsimulation to determine likely scope of pharmacogenomic testing in a Diabetic Population

Purpose: Despite metformin’s standing as the primary treatment drug for Type 2 Diabetes Mellitus, over one-third of patients on metformin monotherapy fail to achieve glycemic control, and 25% have adverse reactions. Furthermore, within 3 years, 21% start on a second drug, usually a sulfonylurea. While combination therapy is effective, 27.8% of those on sulfonylurea therapy present with hypoglycemic episodes, of which 3.6% are severe, resulting in hospitalization and/or death. An individual’s genetic makeup plays a role in their body’s ability to utilize drugs, and can affect their chances of developing potential side effects to pharmacotherapy. Pharmacogenomics utilizes a patient’s genome to establish an appropriate therapy or dosing regimen to ensure that treatments work effectively with minimal side effects. This project aims to determine whether utilizing pharmacogenomic variants to tailor drug regimens in individuals with T2DM would have clinical efficacy. Materials/Methods: We created a model diabetic population using a microsimulation technique based on Tarrant County demographics and allelic variant population frequencies for metformin and sulfonylurea pharmacogenes to determine the frequency of actionable genotypes (variants that play a role in drug pharmacodynamics). Furthermore, we determined whether actionable genotypes varied based on racial/ethnic groups. Results: Between 20 to 60% of the population had 1 or more actionable genotypes for sulfonylurea drugs, depending on race/ethnicity, with Caucasians presenting with 1 or more actionable genotypes approximately 68% of the time. Caucasians also present with actionable genotypes that affect metformin pharmacodynamics 3% of the time, followed by African Americans presenting with actionable genotypes for metformin 2% of the time. Furthermore, almost 50% of the population has 1 or more actionable genotype for either metformin or sulfonylurea pharmacodynamics. Conclusions: Oral hypoglycemic drug therapy efficacy and potential failure may be influenced by the genetic prevalence of allelic polymorphisms, and the degree of influence varies by racial/ethnic group. The data derived from these simulations will be used in an adverse drug reaction model to enable us to determine if pharmacogenomics studies will better allow for the control of HbA1c levels in T2DM, thereby decreasing the incidence of diabetic complications and adverse drug reactions.