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Shaaban S, Ji Y. Pharmacogenomics and health disparities, are we helping? Front Genet 2023; 14:1099541. [PMID: 36755573 PMCID: PMC9900000 DOI: 10.3389/fgene.2023.1099541] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 01/10/2023] [Indexed: 01/24/2023] Open
Abstract
Pharmacogenomics has been at the forefront of precision medicine during the last few decades. Precision medicine carries the potential of improving health outcomes at both the individual as well as population levels. To harness the benefits of its initiatives, careful dissection of existing health disparities as they relate to precision medicine is of paramount importance. Attempting to address the existing disparities at the early stages of design and implementation of these efforts is the only guarantee of a successful just outcome. In this review, we glance at a few determinants of existing health disparities as they intersect with pharmacogenomics research and implementation. In our opinion, highlighting these disparities is imperative for the purpose of researching meaningful solutions. Failing to identify, and hence address, these disparities in the context of the current and future precision medicine initiatives would leave an already strained health system, even more inundated with inequality.
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Affiliation(s)
- Sherin Shaaban
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, United States,ARUP Laboratories, Salt Lake City, Utah, United States,*Correspondence: Sherin Shaaban,
| | - Yuan Ji
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, Utah, United States,ARUP Laboratories, Salt Lake City, Utah, United States
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Shugg T, Pasternak AL, Luzum JA. Comparison of clinical pharmacogenetic recommendations across therapeutic areas. Pharmacogenet Genomics 2022; 32:51-59. [PMID: 34412102 PMCID: PMC8702450 DOI: 10.1097/fpc.0000000000000452] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVES Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across therapeutic areas. A potential cause for this variability may involve therapeutic area-specific differences in published pharmacogenetics recommendations to clinicians. To date, however, the potential for differences in clinical pharmacogenetics recommendations by therapeutic areas from prominent US guidance sources has not been assessed. Accordingly, our objective was to comprehensively compare essential elements from clinical pharmacogenetics recommendations contained within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and clinical practice guidelines from US professional medical organizations across therapeutic areas. METHODS We analyzed clinical pharmacogenetics recommendation elements within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and professional clinical practice guidelines through 05/24/19. RESULTS We identified 606 unique clinical pharmacogenetics recommendations, with the most recommendations involving oncology (217 recommendations), hematology (79), psychiatry (65), cardiovascular (43) and anesthetic (37) medications. Within our analyses, we observed considerable variability across therapeutic areas within the following essential pharmacogenetics recommendation elements: the recommended clinical management strategy; the relevant genetic biomarkers; the organizations providing pharmacogenetics recommendations; whether routine genetic screening was recommended; and the time since recommendations were published. CONCLUSIONS On the basis of our results, we infer that observed differences in clinical pharmacogenetics recommendations across therapeutic areas may result from specific factors associated with individual disease states, the associated genetic biomarkers, and the characteristics of the organizations providing recommendations.
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Affiliation(s)
- Tyler Shugg
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Amy L. Pasternak
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI
| | - Jasmine A. Luzum
- Department of Clinical Pharmacy, University of Michigan College of Pharmacy, Ann Arbor, MI
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Cacabelos R, Naidoo V, Corzo L, Cacabelos N, Carril JC. Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions. Int J Mol Sci 2021; 22:ijms222413302. [PMID: 34948113 PMCID: PMC8704264 DOI: 10.3390/ijms222413302] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/05/2021] [Accepted: 12/06/2021] [Indexed: 02/06/2023] Open
Abstract
Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.
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Affiliation(s)
- Ramón Cacabelos
- Department of Genomic Medicine, International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Bergondo, 15165 Corunna, Spain
- Correspondence: ; Tel.: +34-981-780-505
| | - Vinogran Naidoo
- Department of Neuroscience, International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Bergondo, 15165 Corunna, Spain;
| | - Lola Corzo
- Department of Medical Biochemistry, International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Bergondo, 15165 Corunna, Spain;
| | - Natalia Cacabelos
- Department of Medical Documentation, International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Bergondo, 15165 Corunna, Spain;
| | - Juan C. Carril
- Departments of Genomics and Pharmacogenomics, International Center of Neuroscience and Genomic Medicine, EuroEspes Biomedical Research Center, Bergondo, 15165 Corunna, Spain;
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Mroz P, Michel S, Allen JD, Meyer T, McGonagle EJ, Carpentier R, Vecchia A, Schlichte A, Bishop JR, Dunnenberger HM, Yohe S, Thyagarajan B, Jacobson PA, Johnson SG. Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System. Front Genet 2021; 12:712602. [PMID: 34745204 PMCID: PMC8564018 DOI: 10.3389/fgene.2021.712602] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 09/16/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.
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Affiliation(s)
- Pawel Mroz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Stephen Michel
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Josiah D Allen
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Tim Meyer
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
| | - Erin J McGonagle
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | | | | | | | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States.,Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Henry M Dunnenberger
- Mark R Neaman Center for Personalized Medicine Center, NorthShore University HealthSystem, Evanston, IL, United States
| | - Sophia Yohe
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Pamala A Jacobson
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, Minneapolis, MN, United States
| | - Steven G Johnson
- Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States
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Tafazoli A, Guchelaar HJ, Miltyk W, Kretowski AJ, Swen JJ. Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice. Front Pharmacol 2021; 12:693453. [PMID: 34512329 PMCID: PMC8424415 DOI: 10.3389/fphar.2021.693453] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 07/26/2021] [Indexed: 11/13/2022] Open
Abstract
Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.
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Affiliation(s)
- Alireza Tafazoli
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, Bialystok, Poland
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- Leiden Network of Personalized Therapeutics, Leiden, Netherlands
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Faculty of Pharmacy with the Division of Laboratory Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Adam J. Kretowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Jesse J. Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, Netherlands
- Leiden Network of Personalized Therapeutics, Leiden, Netherlands
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Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children's Hospital. J Pers Med 2021; 11:jpm11050394. [PMID: 34064668 PMCID: PMC8150685 DOI: 10.3390/jpm11050394] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 05/03/2021] [Accepted: 05/06/2021] [Indexed: 02/07/2023] Open
Abstract
Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children’s Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.
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Cheng CM, So TW, Bubp JL. Characterization of Pharmacogenetic Information in Food and Drug Administration Drug Labeling and the Table of Pharmacogenetic Associations. Ann Pharmacother 2020; 55:1185-1194. [PMID: 33384014 DOI: 10.1177/1060028020983049] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND The US Food and Drug Administration (FDA) recommends using only FDA-reviewed pharmacogenetic information to make prescribing decisions based on genetic test results. Such information is available in drug labeling and in the Table of Pharmacogenetic Associations ("Associations table"). OBJECTIVE To compile a list of drug-gene pairs from drug labeling and the Associations table and categorize the pharmacogenetic information and clinical outcome associated with each drug-gene pair. METHODS This was a cross-sectional analysis of pharmacogenetic information in the Associations table and individual drug labeling in March 2020. We used the Table of Pharmacogenomic Biomarkers in Drug Labeling to identify drug labels to review. We categorized the pharmacogenetic information for each drug-gene pair according to whether the purpose was to describe (1) polymorphisms affecting drug disposition (metabolism or transport), (2) polymorphisms affecting a direct drug target, (3) variants associated with adverse drug reaction (ADR) susceptibility, (4) variants associated with therapeutic failure, (5) a biomarker-defined indication, or (6) a biomarker-defined ADR. We also categorized the clinical outcome-efficacy, safety, or unknown-associated with each drug-gene pair. We reported counts and proportions of drug-gene pairs in each pharmacogenetic information and clinical outcome category. RESULTS We identified 308 drug-gene pairs, of which 36% were associated with a biomarker-defined drug indication, 33% with polymorphic drug metabolism, and 28% with ADR susceptibility. Most drug-gene pairs (n = 267, 87%) were associated with an efficacy or safety-related outcome. CONCLUSION AND RELEVANCE FDA-reviewed pharmacogenetic information is available for more than 300 drug-gene pairs and can help guide prescribing decisions.
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Affiliation(s)
| | - Thomas W So
- First Databank, Inc, South San Francisco, CA, USA
| | - Jeff L Bubp
- First Databank, Inc, South San Francisco, CA, USA
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Affiliation(s)
- Gary Remington
- University of Toronto, Centre for Addiction and Mental Health (CAMH), 250 College St., Toronto, M5T 1R8, ON, Canada.
| | - Shitij Kapur
- Faculty of Medicine, Dentistry, and Health Sciences, University of Melbourne, Melbourne, 3010, Australia
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