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Diabetes is the basis for the definition of Hyperglycemia. Determining the genetic etiology of certain monogenic forms of diabetes can significantly alter treatment, allowing patients to switch from insulin to sulfonylureas. But type 2 diabetes accounts for the majority of cases of diabetes. Our understanding of the various subtypes of monogenic diabetes mellitus and the complex etiology of type 2 diabetes mellitus (T2DM) has significantly improved as a result of genomic investigations. Hyperglycemia is a complication of type 2 diabetes mellitus (T2DM), a complicated metabolic disease marked by decreased insulin supply and action. Pharmacogenomics, the study of how a person's genetic composition affects how they respond to medications, has become a viable strategy to maximize therapeutic results in the treatment of type 2 diabetes. In the context of type 2 diabetes, this abstract examines the emerging field of pharmacogenomics, identifying significant genetic variations linked to heterogeneity in drug response and their potential clinical consequences. The inability of other tissue cells to respond to insulin and use blood glucose, as well as the malfunction of pancreatic β-cells in secreting insulin, are signs of a metabolic imbalance in DMT2. But in recent times, thanks to developments in genomics and molecular analysis the substantial evidence that has been gathered up to this point regarding the pharmacogenetics of metformin, sulfonylureas, thiazolidinedione is reviewed in this review. Type 2 diabetes mellitus (T2DM) is a common disease whose incidence is rising quickly throughout the world. Controlling blood sugar levels and preventing the worsening of glycemic symptoms are the two main objectives of T2DM treatment. This article examines the clinical evidence for pharmacogenomics, the drug classes that are frequently prescribed and affected by known pharmacogenes, testing expenses, research obstacles, and requirements for clinical implementation.
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"PHARMACOGENOMICS OF TYPE-2 ANTI-DIABETICS", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.9, Issue 4, page no.1109 - 1119, April-2024, Available :http://www.ijrti.org/papers/IJRTI2404149.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator