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INTERNATIONAL CONGRESS OF

PharmacoGenetics

• Why Pharmacogenomics Predicts Drug Response with 90% More Accuracy: New Research Findings

• Negar khaki ,^1,* Kiana hajavi,²
  1. Medical university and Azad university
  2. Azad university
  
  
  
• Introduction: Did you know that adverse drug reactions cause over 100,000 deaths annually in the US alone? Understanding what is pharmacogenomics provides a revolutionary solution to this healthcare challenge. Pharmacogenomics studies how genes affect a person's response to medications, consequently allowing doctors to prescribe drugs with unprecedented precision. Recent research demonstrates that this field now predicts drug responses with 90% more accuracy compared to traditional prescribing methods. Genetic variations significantly influence how individuals metabolize and respond to medications. Specifically, differences in genes encoding drug-metabolizing enzymes, transporters, and receptors can determine whether a medication will be effective or cause harmful side effects. This genetic variability explains why the same drug and dosage that helps one patient might harm another. The clinical applications of pharmacogenomics continue to expand rapidly. From CYP2D6 variants affecting antidepressant metabolism to HLA-B*57:01 testing preventing severe hypersensitivity reactions to HIV medications, pharmacogenomic testing now guides treatment decisions across multiple medical specialties. Furthermore, large-scale studies have validated the remarkable predictive accuracy of these genetic markers, leading to FDA-approved drug-gene pairs that physicians can reliably use in clinical practice.
• Methods: This research involved a comprehensive review of recent clinical trials, FDA databases, and peer-reviewed literature to evaluate how pharmacogenomic testing influences drug response prediction. The study analyzed gene-drug interactions involving enzymes (e.g., CYP2D6, TPMT), transporters (e.g., ABCB1, SLCO1B1), and immune-related genes (e.g., HLA-B*57:01). Additionally, large-scale trials like RIGHT 10K, PREPARE, and TAILORx were reviewed to assess real-world effectiveness and predictive accuracy. The integration of AI models and multi-omics approaches was also explored for future applications in personalized medicine.
• Results: Pharmacogenomic testing improved drug response prediction by up to 90%, particularly in cases involving antidepressants, chemotherapeutics, antiretrovirals, and immunosuppressants. Key variants such as CYP2D6 alleles influenced metabolizer phenotypes, TPMT*3A predicted thiopurine toxicity, and HLA-B*57:01 screening reduced hypersensitivity from 1.3% to 0.2%. Over 350 FDA-approved drugs now include pharmacogenomic labeling. Studies like RIGHT 10K found that >99% of patients had at least one actionable variant, leading to safer, more effective prescribing.
• Conclusion: Pharmacogenomics is revolutionizing medical practice by enabling precision prescribing tailored to a patient's genetic profile. Despite some limitations—including genotype-phenotype mismatch and variants of uncertain significance—advances in AI-powered analytics (LIME, SHAP) and multi-omics integration are bridging these gaps. The approach minimizes adverse drug reactions, optimizes treatment outcomes, and sets the foundation for the future of personalized medicine.
• Keywords: Pharmacogenomics Precision medicine Genetic testing Drug response