STM Journals Peer-reviewed research from Consortium e-Learning Network

Research & Reviews: A Journal of Drug Design & Discovery Original Research

Pharmacogenomics: Unlocking the Genetic Basis of Drug Response for Precision Medicine

  1. Ankita Pramod Chaudhari Department of Pharmaceutics, S.V.S’s Dadasaheb Rawal Pharmacy College, Mandal Road, Dondaicha, Tal- Shindhkheda; Dist- Dhule
  2. Nandini Rajendra Jadhav Department of Quality Assurance, S.V.S’s Dadasaheb Rawal Pharmacy College, Mandal Road, Dondaicha, Tal- Shindhkheda; Dist- Dhule
  3. Bhagyashri Ambalal Patil Department of Pharmaceutics, P.S.G.V.P.M’s College of Pharmacy, District Nandurbar, Shahada
  4. Sujata Sanjaysing Girase Department of Pharmaceutical Chemistry, Shram Sadhana Bombay Trust’s Institute of Pharmacy, Bambhori, Jalgaon

Abstract

Pharmacogenomics, a fusion of pharmacology and genomics, explores how genetic variations influence individual responses to medications. This field is revolutionizing modern medicine by moving away from a one-size-fits-all approach toward personalized treatment strategies. By identifying specific genetic markers, pharmacogenomics aims to enhance drug efficacy, minimize adverse drug reactions, and improve overall patient outcomes. Key methodologies in this discipline include candidate gene analysis, genome-wide association studies, and haplotype analysis, all of which contribute to understanding the genetic basis of drug response variability. Pharmacogenomics is also transforming drug development by facilitating target identification, optimizing clinical trial design, and enabling more precise therapeutic interventions. Despite significant progress, several barriers – scientific, economic, legal, and commercial – continue to challenge its widespread clinical implementation. Additionally, the integration of artificial intelligence has accelerated pharmacogenomic research by enabling large-scale data analysis and predictive modeling. Looking forward, the continued advancement of this field holds promise for safer, more effective, and cost- efficient healthcare through the development of precision medicine.

Keywords

References (35)

  1. Frueh FW. Real-world Clinical Effectiveness, Regulatory Transparency and Payer Coverage: Three Ingredients for Translating Pharmacogenomics into Clinical Practice. Pharmacogenomics. 2010;11(5):657-660. doi:10.2217/pgs.10.46
  2. Trent RJ. Pathology Practice and Pharmacogenomics. Pharmacogenomics. 2009;11(1):105-111. doi:10.2217/pgs.09.150
  3. Arendt D, Musser JM, Baker CVH, Bergman A, Cepko C, Erwin DH, et al. The origin and evolution of cell types. Nature Reviews Genetics. 2016;17(12):744-757. doi:10.1038/nrg.2016.127
  4. Eichelbaum M, Ingelman-Sundberg M, Evans WE. Pharmacogenomics and Individualized Drug Therapy. Annual Review of Medicine. 2006;57(1):119-137. doi:10.1146/annurev.med.56.082103.104724
  5. Lauschke VM, Milani L, Ingelman-Sundberg M. Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future Developments. The AAPS Journal. 2017;20(1). doi:10.1208/s12248-017-0161-x
  6. Sadée W, Dai Z. Pharmacogenetics/genomics and personalized medicine. Human Molecular Genetics. 2005;14(suppl_2):R207-R214. doi:10.1093/hmg/ddi261
  7. T P A. Pharmacogenomics: The Right Drug to the Right Person. Journal of Clinical Medicine Research. 2009. doi:10.4021/jocmr2009.08.1255
  8. Åkerlund E, Gudoityte G, Moussaud-Lamodière E, Lind O, Bwanika HC, Lehti K, et al. The drug efficacy testing in 3D cultures platform identifies effective drugs for ovarian cancer patients. npj Precision Oncology. 2023;7(1). doi:10.1038/s41698-023-00463-z
  9. AACR Project Genie Consortium; André, F.; Arnedos, M.; Baras, A.S.; Baselga, J.; Zhang, H. 2017; AACR Project GENIE: Powering Precision Medicine through an International Consortium. Cancer Discov; 7, 818–831.
  10. Derry JMJ, Mangravite LM, Suver C, Furia MD, Henderson D, Schildwachter X, et al. Developing predictive molecular maps of human disease through community-based modeling. Nature Genetics. 2012;44(2):127-130. doi:10.1038/ng.1089
  11. Zhou Y, Fujikura K, Mkrtchian S, Lauschke VM. Computational Methods for the Pharmacogenetic Interpretation of Next Generation Sequencing Data. Frontiers in Pharmacology. 2018;9. doi:10.3389/fphar.2018.01437
  12. Kwon JM and Goate AM; 2000 The candidate gene approach. Alchol Res Health 2000; 24(3):164-8 63.
  13. Roses AD. Pharmacogenetics and the practice of medicine. Nature. 2000;405(6788):857-865. doi:10.1038/35015728
  14. Johnson JA. Drug Target Pharmacogenomics. American Journal of PharmacoGenomics. 2001;1(4):271-281. doi:10.2165/00129785-200101040-00004
  15. Kuznetsov V, Lee HK, Maurer-Stroh S, Molnár MJ, Pongor S, Eisenhaber B, et al. How bioinformatics influences health informatics: usage of biomolecular sequences, expression profiles and automated microscopic image analyses for clinical needs and public health. Health Information Science and Systems. 2013;1(1). doi:10.1186/2047-2501-1-2
  16. Sliwoski G, Kothiwale S, Meiler J, Lowe EW. Computational Methods in Drug Discovery. Pharmacological Reviews. 2014;66(1):334-395. doi:10.1124/pr.112.007336
  17. Luo Y, Zhao X, Zhou J, Yang J, Zhang Y, Kuang W, et al. A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-00680-8
  18. Kraljevic S, Stambrook PJ, Pavelic K. Accelerating drug discovery. The EMBO Reports. 2004;5(9):837-842. doi:10.1038/sj.embor.7400236
  19. Hughes J, Rees S, Kalindjian S, Philpott K. Principles of early drug discovery. British Journal of Pharmacology. 2011;162(6):1239-1249. doi:10.1111/j.1476-5381.2010.01127.x
  20. Cully M. Genetic information adds supporting weight. Nature Reviews Drug Discovery. 2015;14(8):525-525. doi:10.1038/nrd4692
  21. Thomsen SK, Gloyn AL. Human genetics as a model for target validation: finding new therapies for diabetes. Diabetologia. 2017;60(6):960-970. doi:10.1007/s00125-017-4270-y
  22. Mestan KK, Ilkhanoff L, Mouli S, Lin S. Genomic sequencing in clinical trials. Journal of Translational Medicine. 2011;9(1). doi:10.1186/1479-5876-9-222
  23. Scott SA. Personalizing medicine with clinical pharmacogenetics. Genetics in Medicine. 2011;13(12):987-995. doi:10.1097/gim.0b013e318238b38c
  24. Klein ME, Parvez MM, Shin JG. Clinical Implementation of Pharmacogenomics for Personalized Precision Medicine: Barriers and Solutions. Journal of Pharmaceutical Sciences. 2017;106(9):2368-2379. doi:10.1016/j.xphs.2017.04.051
  25. Ahmed S, Zhou Z, Zhou J, Chen SQ. Pharmacogenomics of Drug Metabolizing Enzymes and Transporters: Relevance to Precision Medicine. Genomics, Proteomics & Bioinformatics. 2016;14(5):298-313. doi:10.1016/j.gpb.2016.03.008
  26. Lavezzari G, Womack A. Industry perspectives on biomarker qualification. Clinical Pharmacology & Therapeutics. 2015;99(2):208-213. doi:10.1002/cpt.264
  27. Novelli G, Ciccacci C, Borgiani P, Papaluca Amati M, Abadie E. Genetic tests and genomic biomarkers: regulation, qualification and validation. Clin Cases Miner Bone Metab. 2008 May;5(2):149-54.
  28. Schuck RN, Grillo JA. Pharmacogenomic Biomarkers: an FDA Perspective on Utilization in Biological Product Labeling. The AAPS Journal. 2016;18(3):573-577. doi:10.1208/s12248-016-9891-4
  29. Magdum CS, Velingkar VS, Gupta MK. Pharmacogenomics: The search for the Individualized Therapy. Indian Journal of pharmaceutical education and research. 2006;40(2):84.
  30. Lazarou J, Pomeranz BH, Corey PN. Incidence of Adverse Drug Reactions in Hospitalized Patients. JAMA. 1998;279(15):1200. doi:10.1001/jama.279.15.1200
  31. Abdelhalim H, Berber A, Lodi M, Jain R, Nair A, Pappu A, et al. Artificial Intelligence, Healthcare, Clinical Genomics, and Pharmacogenomics Approaches in Precision Medicine. Frontiers in Genetics. 2022;13. doi:10.3389/fgene.2022.929736
  32. Iyer RK, Athreya AP, Wang L, Weinshilboum RM. Artificial Intelligence and Pharmacogenomics. Advances in Molecular Pathology. 2019;2(1):111-118. doi:10.1016/j.yamp.2019.08.003
  33. Jhawat V, Gupta S, Gulia M, Nair A. Artificial intelligence and data science in pharmacogenomics-based drug discovery: Future of medicines. Data Science for Genomics. 2023:85-97. doi:10.1016/b978-0-323-98352-5.00005-7
  34. Lazarou J, Pomeranz BH, Corey PN. Incidence of Adverse Drug Reactions in Hospitalized Patients. JAMA. 1998;279(15):1200. doi:10.1001/jama.279.15.1200
  35. Anup Ojha and Tanuj Joshi; 2016; A review on the role of pharmacogenomics in drug discovery and development; IJPSR; Vol. 7(9): 3587-3595.
Support