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The Era of Pharmacology Toward Pharmacogenomics

Rajavarman Kittu, Anuja Mishra

Abstract


In both Modern Laboratory medicine as well medical science both the Pharmacogenomics is fast, emerging, outcome driven approach which is generally termed as precision medicine. Understanding the importance of gene-drug association and clinical implementation, effect of drug choices over the clinical subjects are kind of need of hour as it is proof of concept for evidence driven therapeutic approach. Also, in research prospective the genome wide association studies (GWAS) which helps the researches to corelate genotype data captured from the population with drug-response phenotypes gives the scopes to discover the drug efficacy and adverse drug reactions. Also, the concepts of pharmacokinetics or pharmacodynamics are having strong impacts based on the coding regions of the genes in polymorphism resolution which affects the disparate treatment outcomes. This review article focused on highlighting the nomenclatures used in pharmacogenomics, well characterised classifications, definitions provided but serval consortium of pharmacogenomics, understanding the standards of gene-drug corelation, drug efficacy, drug relations in order to improve the clinical implication and outcome of patience.

 


Keywords


Pharmacogenomics, Single nucleotide polymorphisms, Clinical Implication, Genomics Profiling, Psychiatry.

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References


Lin E, Lin CH, Lane HY. Precision psychiatry applications with pharmacogenomics: Artificial intelligence and machine learning approaches. International journal of molecular sciences. 2020;21(3):969.

Klein ME, Parvez MM, Shin JG. Clinical implementation of pharmacogenomics for personalized precision medicine: barriers and solutions. Journal of pharmaceutical sciences. 2017;106(9):2368-79.

Torres EB, Isenhower RW, Nguyen J,et al. Toward precision psychiatry: statistical platform for the personalized characterization of natural behaviors. Frontiers in neurology. 2016;7:8.

Amare AT, Schubert KO, Baune BT. Pharmacogenomics in the treatment of mood disorders: strategies and opportunities for personalized psychiatry. EPMA Journal. 2017;8(3):211-27.

Lin E, Tsai SJ. Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2016;64:334-40.

Lin E, Tsai SJ. Genome-wide microarray analysis of gene expression profiling in major depression and antidepressant therapy. Progress in Neuro-Psychopharmacology and Biological Psychiatry. 2016;64:334-40.

Thorn CF, Klein TE, Altman RB. PharmGKB. Pharmacogenomics. 2005:179-91.

Yaşar Ü. The role of pharmacogenetics of cytochrome P450s in phenytoin-induced DRESS syndrome. Central European Journal of Immunology. 2018;43(2):220-1.

Patrinos GP. The Pharmacogenomics Journal: there is a new chief in town. The Pharmacogenomics Journal. 2020;20(6):747-8.

Gaedigk A, Whirl-Carrillo M, Pratt VM, Miller NA, Klein TE. PharmVar and the landscape of pharmacogenetic resources. Clinical pharmacology and therapeutics. 2020;107(1):43.

Brandl E, Halford Z, Clark MD, Herndon C. Pharmacogenomics in Pain Management: A Review of Relevant Gene-Drug Associations and Clinical Considerations. Annals of Pharmacotherapy. 2022;55(12):1486-501.

Ramos KN, Gregornik D, Ramos KS. Pharmacogenomics insights into precision pediatric oncology. Current opinion in pediatrics. 2021;33(6):564-9.

Nagai A, Hirata M, Kamatani Y, Muto K, Matsuda K,et al. Overview of the BioBank Japan Project: study design and profile. Journal of epidemiology. 2017;27(Supplement_III):S2-8.

Stark Z, Dolman L, Manolio TA,et al. Integrating genomics into healthcare: a global responsibility. The American Journal of Human Genetics. 2019;104(1):13-20.

Pratt VM, Cavallari LH, Del Tredici AL,et al. Recommendations for clinical CYP2C9 genotyping allele selection: a joint recommendation of the Association for Molecular Pathology and College of American Pathologists. The Journal of Molecular Diagnostics. 2019;21(5):746-55.

16 Hamilton M. The Hamilton rating scale for depression. InAssessment of depression 1986 (pp. 143-152).

DeBoever C, Tanigawa Y, Aguirre et al. Assessing digital phenotyping to enhance genetic studies of human diseases. The American Journal of Human Genetics. 2020;106(5):611-22.

Denny JC, Bastarache L, Ritchie MD,et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nature biotechnology. 2013;31(12):1102-11.

McInnes G, Altman RB. Drug response pharmacogenetics for 200,000 UK Biobank participants. InBIOCOMPUTING 2021: Proceedings of the Pacific Symposium 2020 (pp. 184-195).

Lanfear DE, Luzum JA, She R,et al. Polygenic score for β-blocker survival benefit in European ancestry patients with reduced ejection fraction heart failure. Circulation: Heart Failure. 2020;13(12):e007012.

He Y, Hoskins JM, McLeod HL. Copy number variants in pharmacogenetic genes. Trends in molecular medicine. 2011;17(5):244-51.

Taliun D, Harris DN, Kessler MD,et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program. Nature. 2021;590(7845):290-9.

Aguirre M, Rivas MA, Priest J. Phenome-wide burden of copy-number variation in the UK biobank. The American Journal of Human Genetics. 2019;105(2):373-83.

Lavertu A, McInnes G, Daneshjou R,et al. Pharmacogenomics and big genomic data: from lab to clinic and back again. Human molecular genetics. 2018;27(R1):R72-8.


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