Precision sciences | Online ISSN 3064-9226
REVIEWS   (Open Access)

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) 1-9 https://doi.org/10.25163/biosciences.112092

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


Abstract

Pharmacogenomics, the intersection of pharmacology and genetics, is transforming healthcare by tailoring drug treatments to individual genetic profiles. This field focuses on understanding how genetic variations affect drug metabolism, efficacy, and adverse reactions, advancing the potential for precision medicine. Leveraging breakthroughs in genetic sequencing technology, this study utilizes targeted gene analysis to explore polymorphisms, mutations, and allelic variations that influence individualized drug responses. Additionally, the study reviews current methodologies, tools, and clinical case applications of pharmacogenomics to identify optimal therapeutic strategies. Findings highlight that rapid and cost-effective genetic sequencing enhances treatment precision, improves outcomes, and reduces adverse drug reactions, ultimately ensuring patient safety. Clinical examples illustrate the practical benefits and limitations of integrating pharmacogenomics into medical practice. Despite its promise, challenges such as standardizing procedures, addressing ethical concerns, and incorporating genetic data into clinical workflows remain. This study underscores the importance of bridging  knowledge gaps among stakeholders and proposes strategies to establish pharmacogenomics as a routine tool in personalized medicine, fostering safer and more effective 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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