Background: Physicians attempt to achieve glycemic goals in patients with type 2 diabetes mellitus (T2DM) through various means, including glucose-lowering medications. There is interindividual variability in response to medications, which can be partially explained by the presence of genetic polymorphisms that affect drug metabolism. Pharmacogenomics studies the hereditary basis of interpatient variations in drug response and aims to identify subgroups of patients whose drug management could be tailored accordingly. The aim of this review is to explore patient profiling in the management of T2DM with a focus on the sodium glucose transporter inhibitor canagliflozin.
Methods: The PubMed database was searched using the terms "pharmacogenomics" and "diabetes" through May 31, 2014. Published articles and abstracts presented at national/international meetings were considered.
Results and conclusion: Genome-wide association studies have opened the door for patient profiling and research into genetic variants in multifactorial T2DM. Clinically, it may be possible to tailor the type of medication used based on the presence or absence of the various genetic variants. However, the polymorphisms studied may only explain some of the variability in response to T2DM drugs and needs further validation to ensure its authenticity. There are still unidentified factors which appear to play a role in the interindividual variability seen in clinical practice. The potential exists for pharmacogenomics to promote efficacious, safe, and cost-effective individualized diabetes management. Pharmacogenomics is still in its early stages, and the idea of defining patients genetically to predict individual responses to drugs and obtain safe and effective T2DM management is promising, in spite of existing barriers. Currently, clinical profiling of patients with T2DM and using an individualized approach with most drugs, including canagliflozin, based on comorbid conditions still remains the most accepted approach for the management of T2DM.
Keywords: genetic variants; personalized medicine; pharmacogenomics.