Pharmacogenomics: Advancing Personalized Medicine Through Genetic Profiling for Optimized Drug Therapies

Md Haroon Or Rashid; Md Mazedul Haq

doi:10.25163/biosciences.112092

Biopharmaceuticals and medical sciences | Online ISSN 3064-9226

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Pharmacogenomics: Advancing Personalized Medicine Through Genetic Profiling for Optimized Drug Therapies

Md Haroon Or Rashid ^1*, Md Mazedul Haq ²

+ Author Affiliations

Journal of Precision Biosciences 1 (1) 1-8 https://doi.org/10.25163/biosciences.112092

Submitted: 05 October 2019 Revised: 11 November 2019 Published: 15 November 2019

Abstract

Background: Pharmacogenomics, the convergence of pharmacology and genetics, is revolutionizing drug treatment approaches by customizing medication regimens to each patient's unique genetic profile. The field aims to understand how genetic variations influence individual responses to medications, encompassing drug metabolism, efficacy, and adverse effects. Recent technological advancements, particularly in genetic sequencing, have propelled pharmacogenomics to the forefront of medical research, providing opportunities for precision medicine. Methods: This study focuses on targeted gene analysis to decode the complex genetic factors that regulate individualized drug responses. By examining polymorphisms, mutations, variations, and alleles, researchers aim to improve our understanding of drug metabolism. The research also includes a review of current methodologies, tools, and clinical cases to demonstrate how pharmacogenetics can be applied to identify optimal therapy options for patients with specific genetic variations. Results: The analysis reveals that the rapid and cost-effective sequencing of individual genetic data enables more personalized and effective drug administration. This approach not only improves treatment outcomes but also minimizes the risk of adverse reactions, thereby enhancing patient safety. Additionally, some common clinical cases were presented to illustrate the application of pharmacogenomics in practice, highlighting its potential benefits and limitations. Conclusion: While pharmacogenomics presents significant opportunities for advancing personalized medicine, its widespread adoption faces several challenges, including standardizing testing procedures, addressing ethical concerns, and integrating genetic data into clinical workflows. To overcome these hurdles, it is crucial to bridge the knowledge gap among researchers, clinicians, and patients regarding the applications and benefits of pharmacogenetics. This study suggests potential strategies to incorporate pharmacogenetics as a routine diagnostic tool in personalized medicine, paving the way for more individualized and safer treatment approaches.

Keywords: Pharmacogenomics, Personalized Medicine, Genetic Variability, Drug Metabolism, Cytochrome P450

References

Abaji, R., & Krajinovic, M. (2017). Thiopurine S-methyltransferase polymorphisms in acute lymphoblastic leukemia, inflammatory bowel disease and autoimmune disorders: influence on treatment response. Pharmacogenomics and Personalized Medicine, 143-156.

Agyeman, A. A., & Ofori-Asenso, R. (2015). Perspective: Does personalized medicine hold the future for medicine?. Journal of pharmacy & bioallied sciences, 7(3), 239.

Belle, D. J., & Singh, H. (2018). Genetic factors in drug metabolism. American family physician, 77(11), 1553-1560.

Berm, E. J., Looff, M. D., Wilffert, B., Boersma, C., Annemans, L., Vegter, S., ... & Postma, M. J. (2016). Economic evaluations of pharmacogenetic and pharmacogenomic screening tests: a systematic review. Second update of the literature. PloS one, 11(1), e0146262.

Blazer, D. G., & Hernandez, L. M. (Eds.). (2016). Genes, behavior, and the social environment: Moving beyond the nature/nurture debate.

Bradford, K., & Shih, D. Q. (2011). Optimizing 6-mercaptopurine and azathioprine therapy in the management of inflammatory bowel disease. World journal of gastroenterology: WJG, 17(37), 4166.

Bullers, K. (2016). Merck manuals. Journal of the Medical Library Association: JMLA, 104(4), 369.

Chang, M. T., McCarthy, J. J., & Shin, J. (2015). Clinical application of pharmacogenetics: focusing on practical issues. Pharmacogenomics, 16(15), 1733-1741.

Cully, M. (2015). Genetic information adds supporting weight. Nature Reviews Drug Discovery, 14(8), 525-525.

Dean, L. (2012). Thioguanine therapy and TPMT genotype. Medical Genetics Summaries, Pratt V, McLeod H, Dean L, Malheiro A, and Rubinstein W, eds.(National Center for Biotechnology Information (US)).[Google Scholar].

Emily Guo, X., Ngo, B., Sandaldjian Modrek, A., & Lee, W. H. (2014). Targeting tumor suppressor networks for cancer therapeutics. Current drug targets, 15(1), 2-16.

Etienne-Grimaldi, M. C., Boyer, J. C., Thomas, F., Quaranta, S., Picard, N., Loriot, M. A., ... & Collective work by the Groupe de Pharmacologie Clinique Oncologique (GPCO-Unicancer) and the French Réseau National de Pharmacogénétique Hospitalière (RNPGx). (2015). UGT 1A1 genotype and irinotecan therapy: general review and implementation in routine practice. Fundamental & Clinical Pharmacology, 29(3), 219-237.

Fiers, W., Contreras, R., Duerinck, F., Haegeman, G., Iserentant, D., Merregaert, J., ... & Ysebaert, M. (2000). Complete nucleotide sequence of bacteriophage MS2 RNA: primary and secondary structure of the replicase gene. Nature, 260(5551), 500-507.

Filipski, K. K., Mechanic, L. E., Long, R., & Freedman, A. N. (2014). Pharmacogenomics in oncology care. Frontiers in genetics, 5, 73.

Flockhart, D. A., O'Kane, D., Williams, M. S., Watson, M. S., Gage, B., Gandolfi, R., ... & Veenstra, D. (2008). Pharmacogenetic testing of CYP2C9 and VKORC1 alleles for warfarin. Genetics in Medicine, 10(2), 139-150.

Fujita, K. I., Kubota, Y., Ishida, H., & Sasaki, Y. (2015). Irinotecan, a key chemotherapeutic drug for metastatic colorectal cancer. World journal of gastroenterology, 21(43), 12234.

Furuta, T., Sugimoto, M., Shirai, N., & Ishizaki, T. (2017). CYP2C19 pharmacogenomics associated with therapy of Helicobacter pylori infection and gastro-esophageal reflux diseases with a proton pump inhibitor.

Goodsaid, F., & Frueh, F. W. (2017). Implementing the US FDA guidance on pharmacogenomic data submissions. Environmental and molecular mutagenesis, 48(5), 354-358.

H Lee, N. (2010). Pharmacogenetics of drug metabolizing enzymes and transporters: effects on pharmacokinetics and pharmacodynamics of anticancer agents. Anti-Cancer Agents in Medicinal Chemistry (Formerly Current Medicinal Chemistry-Anti-Cancer Agents), 10(8), 583-592.

Hood, L., & Rowen, L. (2013). The human genome project: big science transforms biology and medicine. Genome Med 5 (9): 79.

Hughes, J. P., Rees, S., Kalindjian, S. B., & Philpott, K. L. (2011). Principles of early drug discovery. British journal of pharmacology, 162(6), 1239-1249.

Karazniewicz-Lada, M., Danielak, D., & Glówka, F. (2012). Genetic and non-genetic factors affecting the response to clopidogrel therapy. Expert opinion on pharmacotherapy, 13(5), 663-683.

Karczewski, K. J., Daneshjou, R., & Altman, R. B. (2012). Chapter 7: pharmacogenomics. PLoS computational biology, 8(12), e1002817.

Koscielny, G., An, P., Carvalho-Silva, D., Cham, J. A., Fumis, L., Gasparyan, R., ... & Dunham, I. (2017). Open Targets: a platform for therapeutic target identification and validation. Nucleic acids research, 45(D1), D985-D994.

Kraljevic, S., Stambrook, P. J., & Pavelic, K. (2004). Accelerating drug discovery: Although the evolution of ‘-omics’ methodologies is still in its infancy, both the pharmaceutical industry and patients could benefit from their implementation in the drug development process. EMBO reports, 5(9), 837-842.

Kuznetsov, V., Lee, H. K., Maurer-Stroh, S., Molnár, M. J., Pongor, S., Eisenhaber, B., & Eisenhaber, F. (2013). 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, 1, 1-18.

Lala, A., Berger, J. S., Sharma, G., Hochman, J. S., Braithwaite, R. S., & Ladapo, J. A. (2013). Genetic testing in patients with acute coronary syndrome undergoing percutaneous coronary intervention: a cost-effectiveness analysis. Journal of thrombosis and haemostasis, 11(1), 81-91.

Lavezzari, G., & Womack, A. W. (2016). Industry perspectives on biomarker qualification. Clinical Pharmacology & Therapeutics, 99(2), 208-213.

Lee, H. H., & Ho, R. H. (2017). Interindividual and interethnic variability in drug disposition: polymorphisms in organic anion transporting polypeptide 1B1 (OATP1B1; SLCO1B1). British journal of clinical pharmacology, 83(6), 1176-1184.

Limdi, N. A., & Veenstra, D. L. (2018). Warfarin pharmacogenetics. Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy, 28(9), 1084-1097.

Luo, Y., Zhao, X., Zhou, J., Yang, J., Zhang, Y., Kuang, W., ... & Zeng, J. (2017). A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information. Nature communications, 8(1), 573.

Ma, T. K., Lam, Y. Y., Tan, V. P., & Yan, B. P. (2011). Variability in response to clopidogrel: how important are pharmacogenetics and drug interactions?. British journal of clinical pharmacology, 72(4), 697-706.

Mestan, K. K., Ilkhanoff, L., Mouli, S., & Lin, S. (2011). Genomic sequencing in clinical trials. Journal of Translational Medicine, 9(1), 1-10.

Mohelnikova-Duchonova, B., Melichar, B., & Soucek, P. (2014). FOLFOX/FOLFIRI pharmacogenetics: the call for a personalized approach in colorectal cancer therapy. World journal of gastroenterology: WJG, 20(30), 10316.

Novelli, G., Ciccacci, C., Borgiani, P., Amati, M. P., & Abadie, E. (2018). Genetic tests and genomic biomarkers: regulation, qualification and validation. Clinical cases in mineral and bone metabolism, 5(2), 149.

Pritchard, D. E., Moeckel, F., Villa, M. S., Housman, L. T., McCarty, C. A., & McLeod, H. L. (2017). Strategies for integrating personalized medicine into healthcare practice. Personalized medicine, 14(2), 141-152.

Rasmussen-Torvik, L. J., Stallings, S. C., Gordon, A. S., Almoguera, B., Basford, M. A., Bielinski, S. J., ... & Denny, J. C. (2014). Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems. Clinical Pharmacology & Therapeutics, 96(4), 482-489.

Relling, M. V., & Evans, W. E. (2015). Pharmacogenomics in the clinic. Nature, 526(7573), 343-350.

Roses, A. D. (2000). Pharmacogenetics and the practice of medicine. Nature, 405(6788), 857-865.

Satoh, J. I., Yanaizu, M., Tosaki, Y., Sakai, K., & Kino, Y. (2016). Targeted sequencing approach to identify genetic mutations in Nasu-Hakola disease. Intractable & Rare Diseases Research, 5(4), 269-274.

Schuck, R. N., & Grillo, J. A. (2016). Pharmacogenomic biomarkers: an FDA perspective on utilization in biological product labeling. The AAPS journal, 18, 573-577.

Scott, S. A. (2011). Personalizing medicine with clinical pharmacogenetics. Genetics in medicine, 13(12), 987-995.

Sheweita, S. A. (2000). Drug-metabolizing enzymes mechanisms and functions. Current drug metabolism, 1(2), 107-132.

Sliwoski, G., Kothiwale, S., Meiler, J., & Lowe, E. W. (2014). Computational methods in drug discovery. Pharmacological reviews, 66(1), 334-395.

Spoonamore, K. G., & Johnson, N. M. (2016). Who pays? Coverage challenges for cardiovascular genetic testing in US patients. Frontiers in Cardiovascular Medicine, 3, 14.

Teh, L. K., Hashim, H., Zakaria, Z. A., & Salleh, M. Z. (2012). Polymorphisms of UGT1A1* 6, UGT1A1* 27 & UGT1A1* 28 in three major ethnic groups from Malaysia. The Indian journal of medical research, 136(2), 249.

Thomsen, S. K., & Gloyn, A. L. (2017). Human genetics as a model for target validation: finding new therapies for diabetes. Diabetologia, 60(6), 960-970.

Ventola, C. L. (2013). The role of pharmacogenomic biomarkers in predicting and improving drug response: part 2: challenges impeding clinical implementation. Pharmacy and therapeutics, 38(10), 624.

Verbelen, M., Weale, M. E., & Lewis, C. M. (2017). Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet?. The pharmacogenomics journal, 17(5), 395-402.

Vogenberg, F. R., Barash, C. I., & Pursel, M. (2010). Personalized medicine: part 1: evolution and development into theranostics. Pharmacy and Therapeutics, 35(10), 560.

Wang, Y., Probin, V., & Zhou, D. (2016). Cancer therapy-induced residual bone marrow injury: mechanisms of induction and implication for therapy. Current cancer therapy reviews, 2(3), 271-279.

Wu, J., Li, Y., & Jiang, R. (2014). Integrating multiple genomic data to predict disease-causing nonsynonymous single nucleotide variants in exome sequencing studies. PLoS genetics, 10(3), e1004237.

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