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Johnson D, Del Fiol G, Kawamoto K, Romagnoli KM, Sanders N, Isaacson G, Jenkins E, Williams MS. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc 2024; 31:1183-1194. [PMID: 38558013 PMCID: PMC11031215 DOI: 10.1093/jamia/ocae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVES Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.
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Affiliation(s)
- Darren Johnson
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Katrina M Romagnoli
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Nathan Sanders
- School of Medicine, Geisinger Health Systems, Danville, PA 17822, United States
| | - Grace Isaacson
- Family Medicine, Penn Highlands Healthcare, DuBois, PA 16830, United States
| | - Elden Jenkins
- School of Medicine, Noorda College of Osteopathic Medicine, Provo, UT 84606, United States
| | - Marc S Williams
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
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Norris M, Dalton R, Alam B, Eddy E, Nguyen KA, Cavallari LH, Sumfest J, Wiisanen K, Cicali EJ. Lessons from clinical implementation of a preemptive pharmacogenetic panel as part of a testing pilot program with an employer-sponsored medical plan. Front Genet 2023; 14:1249003. [PMID: 37680199 PMCID: PMC10482099 DOI: 10.3389/fgene.2023.1249003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 08/07/2023] [Indexed: 09/09/2023] Open
Abstract
Introduction: This manuscript reports on a pilot program focused on implementing pharmacogenetic testing within the framework of an employer-sponsored medical plan at University of Florida (UF) Health. The aim was to understand the challenges associated with program implementation and to gather insights into patient attitudes towards PGx testing. Methods: The pilot program adopted a partially preemptive approach, targeting patients on current prescriptions for medications with relevant gene-drug associations. Patients were contacted via phone or through the MyChart system and offered pharmacogenetic testing with no additional direct costs. Results: Of 244 eligible patients, 110 agreed to participate. However, only 61 returned the mailed DNA collection kits. Among these, 89% had at least one potentially actionable genotype-based phenotype. Post-test follow-up revealed that while the majority viewed the process positively, 71% preferred a consultation with a pharmacogenetic specialist for better understanding of their results. Barriers to implementation ranged from fatigue with the healthcare system to a lack of understanding of the pharmacogenetic testing and concerns about privacy and potential misuse of genetic data. Conclusion: The findings underscore the need for clearer patient education on pharmacogenetic results and suggest the importance of the role of pharmacogenetic-trained pharmacists in delivering this education. They also highlight issues with relying on incomplete or inaccurate medication lists in patients' electronic health record. The implementation revealed less obvious challenges, the understanding of which could be beneficial for the success of future preemptive pharmacogenetic implementation programs. The insights from the pilot program served to bridge the information gap between patients, providers, and pharmacogenetic -specialists, with the ultimate goal of improving patient care.
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Affiliation(s)
- Madeline Norris
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
| | - Rachel Dalton
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
| | - Benish Alam
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
| | - Elizabeth Eddy
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
| | - Khoa A. Nguyen
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Jill Sumfest
- GatorCare Health Management Corporation, University of Florida Health, Gainesville, FL, United States
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Emily J. Cicali
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
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3
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Lemke LK, Alam B, Williams R, Starostik P, Cavallari LH, Cicali EJ, Wiisanen K. Reimbursement of pharmacogenetic tests at a tertiary academic medical center in the United States. Front Pharmacol 2023; 14:1179364. [PMID: 37645439 PMCID: PMC10461057 DOI: 10.3389/fphar.2023.1179364] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 07/17/2023] [Indexed: 08/31/2023] Open
Abstract
Introduction: Pharmacogenetics (PGx) has the potential to improve health outcomes but cost of testing is a barrier for equitable access. Reimbursement by insurance providers may lessen the financial burden for patients, but the extent to which PGx claims are covered in clinical practice has not been well-characterized in the literature. Methods: A retrospective analysis of outpatient claims submitted to payers for PGx tests from 1/1/2019 through 12/31/2021 was performed. A reimbursement rate was calculated and compared across specific test types (e.g., single genes, panel), payers, indication, and the year the claim was submitted. Results: A total of 1,039 outpatient claims for PGx testing were analyzed. The overall reimbursement rate was 46% and ranged from 36%-48% across payers. PGx panels were reimbursed at a significantly higher rate than single gene tests (74% vs. 43%, p < 0.001). Discussion: Reimbursement of claims for PGx testing is variable based on the test type, indication, year the claim was submitted, number of diagnosis codes submitted, and number of unique diagnosis codes submitted. Due to the highly variable nature of reimbursement, cost and affordability should be discussed with each patient.
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Affiliation(s)
- Lauren K. Lemke
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Benish Alam
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Roy Williams
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
| | - Petr Starostik
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, FL, United States
- UF Health Pathology Laboratories, UF Health, Gainesville, FL, United States
| | - Larisa H. Cavallari
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Emily J. Cicali
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
| | - Kristin Wiisanen
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, FL, United States
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, FL, United States
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Fahim SM, Alexander CSW, Qian J, Ngorsuraches S, Hohmann NS, Lloyd KB, Reagan A, Hart L, McCormick N, Westrick SC. Current published evidence on barriers and proposed strategies for genetic testing implementation in health care settings: A scoping review. J Am Pharm Assoc (2003) 2023; 63:998-1016. [PMID: 37119989 DOI: 10.1016/j.japh.2023.04.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 04/20/2023] [Accepted: 04/22/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND The slow uptake of genetic testing in routine clinical practice warrants the attention of researchers and practitioners to find effective strategies to facilitate implementation. OBJECTIVES This study aimed to identify the barriers to and strategies for pharmacogenetic testing implementation in a health care setting from published literature. METHODS A scoping review was conducted in August 2021 with an expanded literature search using Ovid MEDLINE, Web of Science, International Pharmaceutical Abstract, and Google Scholar to identify studies reporting implementation of pharmacogenetic testing in a health care setting, from a health care system's perspective. Articles were screened using DistillerSR and findings were organized using the 5 major domains of Consolidated Framework for Implementation Research (CFIR). RESULTS A total of 3536 unique articles were retrieved from the above sources, with only 253 articles retained after title and abstract screening. Upon screening the full texts, 57 articles (representing 46 unique practice sites) were found matching the inclusion criteria. We found that most reported barriers and their associated strategies to the implementation of pharmacogenetic testing surrounded 2 CFIR domains: intervention characteristics and inner settings. Factors relating to cost and reimbursement were described as major barriers in the intervention characteristics. In the same domain, another major barrier was the lack of utility studies to provide evidence for genetic testing uptake. Technical hurdles, such as integrating genetic information to medical records, were identified as an inner settings barrier. Collaborations and lessons from early implementers could be useful strategies to overcome majority of the barriers across different health care settings. Strategies proposed by the included implementation studies to overcome these barriers are summarized and can be used as guidance in future. CONCLUSION Barriers and strategies identified in this scoping review can provide implementation guidance for practice sites that are interested in implementing genetic testing.
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Fragala MS, Shaman JA, Lorenz RA, Goldberg SE. Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers. Popul Health Manag 2022; 25:753-762. [PMID: 36301527 DOI: 10.1089/pop.2022.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.
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A Theory-Informed Systematic Review of Barriers and Enablers to Implementing Multi-Drug Pharmacogenomic Testing. J Pers Med 2022; 12:jpm12111821. [PMID: 36579514 PMCID: PMC9696651 DOI: 10.3390/jpm12111821] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/20/2022] [Accepted: 10/26/2022] [Indexed: 11/06/2022] Open
Abstract
PGx testing requires a complex set of activities undertaken by practitioners and patients, resulting in varying implementation success. This systematic review aimed (PROSPERO: CRD42019150940) to identify barriers and enablers to practitioners and patients implementing pharmacogenomic testing. We followed PRISMA guidelines to conduct and report this review. Medline, EMBASE, CINAHL, PsycINFO, and PubMed Central were systematically searched from inception to June 2022. The theoretical domain framework (TDF) guided the organisation and reporting of barriers or enablers relating to pharmacogenomic testing activities. From the twenty-five eligible reports, eleven activities were described relating to four implementation stages: ordering, facilitating, interpreting, and applying pharmacogenomic testing. Four themes were identified across the implementation stages: IT infrastructure, effort, rewards, and unknown territory. Barriers were most consistently mapped to TDF domains: memory, attention and decision-making processes, environmental context and resources, and belief about consequences.
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Cicali EJ, Lemke L, Al Alshaykh H, Nguyen K, Cavallari LH, Wiisanen K. How to Implement a Pharmacogenetics Service at your Institution. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2022; 5:1161-1175. [PMID: 36589694 PMCID: PMC9799247 DOI: 10.1002/jac5.1699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 07/29/2022] [Indexed: 01/05/2023]
Abstract
The vast majority of patients possess one or more pharmacogenetic variants that can influence optimal medication use. When pharmacogenetic data are used to guide drug choice and dosing, evidence points to improved disease outcomes, fewer adverse effects, and lower healthcare spending. Although its science is well established, clinical use of pharmacogenetic data to guide drug therapy is still in its infancy. Pharmacogenetics essentially involves the intersection of an individual's genetic data with their medications, which makes pharmacists uniquely qualified to provide clinical support and education in this field. In fact, most pharmacogenetics implementations, to date, have been led by pharmacists as leaders or members of a multidisciplinary team or as individual practitioners. A successful large-scale pharmacogenetics implementation requires coordination and synergy among administrators, clinicians, informatics teams, laboratories, and patients. Because clinical implementation of pharmacogenetics is in its early stages, there is an urgent need for guidance and dissemination of shared experiences to provide a framework for clinicians. Many early adopters of pharmacogenetics have explored various strategies among diverse practice settings. This article relies on the experiences of early adopters to provide guidance for critical steps along the pathway to implementation, including strategies to engage stakeholders; evaluate pharmacogenetic evidence; coordinate laboratory testing, results interpretation and their integration into the electronic health record; identify reimbursement avenues; educate providers and patients; and maintain a successful program. Learning from early adopters' published experiences and strategies can allow clinicians leading a new pharmacogenetics implementation to avoid pitfalls and adapt and apply lessons learned by others to their own practice.
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Affiliation(s)
- Emily J Cicali
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Lauren Lemke
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Hana Al Alshaykh
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Khoa Nguyen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
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8
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Skryabin V, Rozochkin I, Zastrozhin M, Lauschke V, Franck J, Bryun E, Sychev D. Meta-analysis of pharmacogenetic clinical decision support systems for the treatment of major depressive disorder. THE PHARMACOGENOMICS JOURNAL 2022; 23:45-49. [PMID: 36273107 DOI: 10.1038/s41397-022-00295-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/06/2022] [Accepted: 10/10/2022] [Indexed: 11/07/2022]
Abstract
The study aimed to conduct a meta-analysis of studies comparing pharmacogenetically guided dosing of antidepressants with empiric standard of care. Publications referring to genotype-guided antidepressant therapy were identified via PubMed, Google Scholar, Scopus, Web of Science, Embase, and Cochrane databases from the inception of the databases to 2021. In addition, bibliographies of all articles were manually searched for additional references not identified in primary searches. Studies comparing clinical outcomes between two groups of patients who received antidepressant treatment were included in meta-analysis. Analysis of the data revealed statistically significant differences between the experimental group receiving pharmacogenetically guided dosing and the empirically treated controls. Specifically, genotype-guided treatment significantly improved response and remission of patients after both eight and twelve weeks of therapy, whereas no effect on the development of adverse drug reactions was observed. This meta-analysis indicates that the use of preemptive genotyping to guide dosing of antidepressants might increase treatment efficacy.
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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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McDermott JH, Wright S, Sharma V, Newman WG, Payne K, Wilson P. Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review. Front Med (Lausanne) 2022; 9:945352. [PMID: 36059837 PMCID: PMC9433561 DOI: 10.3389/fmed.2022.945352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/29/2022] [Indexed: 12/11/2022] Open
Abstract
Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.
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Affiliation(s)
- John H. McDermott
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
- *Correspondence: John H. McDermott,
| | - Stuart Wright
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Videha Sharma
- Division of Informatics, Centre for Health Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - William G. Newman
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
| | - Katherine Payne
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Paul Wilson
- Division of Population Health, Centre for Primary Care and Health Services Research, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
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11
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Wang L, Scherer SE, Bielinski SJ, Muzny DM, Jones LA, Black JL, Moyer AM, Giri J, Sharp RR, Matey ET, Wright JA, Oyen LJ, Nicholson WT, Wiepert M, Sullard T, Curry TB, Vitek CRR, McAllister TM, Sauver JL, Caraballo PJ, Lazaridis KN, Venner E, Qin X, Hu J, Kovar CL, Korchina V, Walker K, Doddapaneni H, Wu TJ, Raj R, Denson S, Liu W, Chandanavelli G, Zhang L, Wang Q, Kalra D, Karow MB, Harris KJ, Sicotte H, Peterson SE, Barthel AE, Moore BE, Skierka JM, Kluge ML, Kotzer KE, Kloke K, Vander Pol JM, Marker H, Sutton JA, Kekic A, Ebenhoh A, Bierle DM, Schuh MJ, Grilli C, Erickson S, Umbreit A, Ward L, Crosby S, Nelson EA, Levey S, Elliott M, Peters SG, Pereira N, Frye M, Shamoun F, Goetz MP, Kullo IJ, Wermers R, Anderson JA, Formea CM, El Melik RM, Zeuli JD, Herges JR, Krieger CA, Hoel RW, Taraba JL, Thomas SR, Absah I, Bernard ME, Fink SR, Gossard A, Grubbs PL, Jacobson TM, Takahashi P, Zehe SC, Buckles S, Bumgardner M, Gallagher C, Fee-Schroeder K, Nicholas NR, Powers ML, Ragab AK, Richardson DM, Stai A, Wilson J, Pacyna JE, Olson JE, Sutton EJ, Beck AT, Horrow C, Kalari KR, Larson NB, Liu H, Wang L, Lopes GS, Borah BJ, Freimuth RR, Zhu Y, Jacobson DJ, Hathcock MA, Armasu SM, McGree ME, Jiang R, Koep TH, Ross JL, Hilden M, Bosse K, Ramey B, Searcy I, Boerwinkle E, Gibbs RA, Weinshilboum RM. Implementation of preemptive DNA sequence-based pharmacogenomics testing across a large academic medical center: The Mayo-Baylor RIGHT 10K Study. Genet Med 2022; 24:1062-1072. [PMID: 35331649 PMCID: PMC9272414 DOI: 10.1016/j.gim.2022.01.022] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 12/12/2022] Open
Abstract
PURPOSE The Mayo-Baylor RIGHT 10K Study enabled preemptive, sequence-based pharmacogenomics (PGx)-driven drug prescribing practices in routine clinical care within a large cohort. We also generated the tools and resources necessary for clinical PGx implementation and identified challenges that need to be overcome. Furthermore, we measured the frequency of both common genetic variation for which clinical guidelines already exist and rare variation that could be detected by DNA sequencing, rather than genotyping. METHODS Targeted oligonucleotide-capture sequencing of 77 pharmacogenes was performed using DNA from 10,077 consented Mayo Clinic Biobank volunteers. The resulting predicted drug response-related phenotypes for 13 genes, including CYP2D6 and HLA, affecting 21 drug-gene pairs, were deposited preemptively in the Mayo electronic health record. RESULTS For the 13 pharmacogenes of interest, the genomes of 79% of participants carried clinically actionable variants in 3 or more genes, and DNA sequencing identified an average of 3.3 additional conservatively predicted deleterious variants that would not have been evident using genotyping. CONCLUSION Implementation of preemptive rather than reactive and sequence-based rather than genotype-based PGx prescribing revealed nearly universal patient applicability and required integrated institution-wide resources to fully realize individualized drug therapy and to show more efficient use of health care resources.
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Affiliation(s)
- Liewei Wang
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN
| | - Steven E. Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX
| | - Suzette J. Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Donna M. Muzny
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Leila A. Jones
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - John Logan Black
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Ann M. Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Wayne T. Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | - Mathieu Wiepert
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Terri Sullard
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Timothy B. Curry
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Jennifer L. Sauver
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Pedro J. Caraballo
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Konstantinos N. Lazaridis
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Eric Venner
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Xiang Qin
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Jianhong Hu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Christie L. Kovar
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Viktoriya Korchina
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Kimberly Walker
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | | | - Tsung-Jung Wu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Ritika Raj
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Shawn Denson
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Wen Liu
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Gauthami Chandanavelli
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Lan Zhang
- Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX
| | - Qiaoyan Wang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Mary Beth Karow
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Hugues Sicotte
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Sandra E. Peterson
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Amy E. Barthel
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Brenda E. Moore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Michelle L. Kluge
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Katrina E. Kotzer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Karen Kloke
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | | | - Heather Marker
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joseph A. Sutton
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | | | | | - Dennis M. Bierle
- Division of General Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | - Audrey Umbreit
- Department of Pharmacy, Mayo Clinic Health System, Mankato, MN
| | - Leah Ward
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | - Sheena Crosby
- Department of Pharmacy, Mayo Clinic, Jacksonville, FL
| | | | - Sharon Levey
- Department of Clinical Genomics, Mayo Clinic, Scottsdale, AZ
| | - Michelle Elliott
- Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Steve G. Peters
- Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Naveen Pereira
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN
| | - Mark Frye
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN
| | - Fadi Shamoun
- Department of Cardiovascular Medicine Mayo Clinic, Phoenix, AZ
| | - Matthew P. Goetz
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, MN
| | | | - Robert Wermers
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | - Scott R. Thomas
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Imad Absah
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Stephanie R. Fink
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Andrea Gossard
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Paul Takahashi
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | | | - Susan Buckles
- Department of Public Affairs, Mayo Clinic, Rochester, MN
| | | | | | | | | | - Melody L. Powers
- Biospecimens Accessioning and Processing Laboratory, Mayo Clinic, Rochester, MN
| | - Ahmed K. Ragab
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | | | - Anthony Stai
- Department of Information Technology, Mayo Clinic, Rochester, MN
| | - Jaymi Wilson
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN
| | - Joel E. Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Janet E. Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Erica J. Sutton
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Annika T. Beck
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Caroline Horrow
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Krishna R. Kalari
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Nicholas B. Larson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Hongfang Liu
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Liwei Wang
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Guilherme S. Lopes
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN,Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Bijan J. Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN
| | - Debra J. Jacobson
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Matthew A. Hathcock
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Sebastian M. Armasu
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Michaela E. McGree
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | - Ruoxiang Jiang
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | - Eric Boerwinkle
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Human Genome Sequencing Center Clinical Laboratory, Baylor College of Medicine, Houston, TX,School of Public Health, University of Texas Health Science Center at Houston, Houston, TX
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX,Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX,Corresponding Authors (), ()
| | - Richard M. Weinshilboum
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN,Division of Clinical Pharmacology, Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN,Corresponding Authors (), ()
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12
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Grande KJ, Dalton R, Moyer NA, Arwood MJ, Nguyen KA, Sumfest J, Ashcraft KC, Cooper-DeHoff RM. Assessment of a Manual Method versus an Automated, Probability-Based Algorithm to Identify Patients at High Risk for Pharmacogenomic Adverse Drug Outcomes in a University-Based Health Insurance Program. J Pers Med 2022; 12:jpm12020161. [PMID: 35207649 PMCID: PMC8878761 DOI: 10.3390/jpm12020161] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/21/2021] [Accepted: 12/29/2021] [Indexed: 12/21/2022] Open
Abstract
We compared patient cohorts selected for pharmacogenomic testing using a manual method or automated algorithm in a university-based health insurance network. The medication list was compiled from claims data during 4th quarter 2018. The manual method selected patients by number of medications by the health system’s list of medications for pharmacogenomic testing. The automated method used YouScript’s pharmacogenetic interaction probability (PIP) algorithm to select patients based on the probability that testing would result in detection of one or more clinically significant pharmacogenetic interactions. A total of 6916 patients were included. Patient cohorts selected by each method differed substantially, including size (manual n = 218, automated n = 286) and overlap (n = 41). The automated method was over twice as likely to identify patients where testing may reveal a clinically significant pharmacogenetic interaction than the manual method (62% vs. 29%, p < 0.0001). The manual method captured more patients with significant drug–drug or multi-drug interactions (80.3% vs. 40.2%, respectively, p < 0.0001), higher average number of significant drug interactions per patient (3.3 vs. 1.1, p < 0.0001), and higher average number of unique medications per patient (9.8 vs. 7.4, p < 0.0001). It is possible to identify a cohort of patients who would likely benefit from pharmacogenomic testing using manual or automated methods.
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Affiliation(s)
| | - Rachel Dalton
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
| | | | | | - Khoa A. Nguyen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
| | - Jill Sumfest
- GatorCare, University of Florida, Gainesville, FL 32610, USA;
| | | | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA; (R.D.); (K.A.N.)
- Division of Cardiology, College of Medicine, University of Florida, Gainesville, FL 32610, USA
- Correspondence: ; Tel.: +1-352-359-2658
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13
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Elchynski AL, Cicali EJ, Ferrer Del Busto MC, Hamilton A, Chang KL, Schmidt SO, Weiner B, Davis R, Estores D, Max Smith D, Wiisanen K, Johnson JA, Cavallari LH. Determining the potential clinical value of panel-based pharmacogenetic testing in patients with chronic pain or gastroesophageal reflux disease. THE PHARMACOGENOMICS JOURNAL 2021; 21:657-663. [PMID: 34075203 PMCID: PMC8605985 DOI: 10.1038/s41397-021-00244-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 04/29/2021] [Accepted: 05/19/2021] [Indexed: 12/31/2022]
Abstract
We aimed to determine the potential value of panel-based pharmacogenetic (PGx) testing in patients with chronic pain or gastroesophageal reflux disease (GERD) who underwent single-gene PGx testing to guide opioid or proton pump inhibitor (PPI) therapy, respectively. Of 448 patients included (chronic pain, n = 337; GERD, n = 111), mean age was 57 years, 68% were female, and 73% were white. Excluding opiates for the pain cohort and PPIs for the GERD cohort, 76.6% of patients with pain and 71.2% with GERD were prescribed at least one additional medication with a high level of PGx evidence, most commonly ondansetron or selective serotonin reuptake inhibitors. The most common genes that could inform PGx drug prescribing were CYP2C19, CYP2D6, CYP2C9, and SLCO1B1. Our findings suggest that patients with chronic pain or GERD are commonly prescribed drugs with a high level of evidence for a PGx-guided approach, supporting panel-based testing in these populations.
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Affiliation(s)
- Amanda L Elchynski
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Emily J Cicali
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Maria C Ferrer Del Busto
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Alessandra Hamilton
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Ku-Lang Chang
- Department of Community Health and Family Medicine, College of Medicine University of Florida, Gainesville, FL, USA
| | - Siegfried O Schmidt
- Department of Community Health and Family Medicine, College of Medicine University of Florida, Gainesville, FL, USA
| | - Brian Weiner
- Division of Gastroenterology, Hepatology and Nutrition, University of Florida, Gainesville, FL, USA
- Charles E. Schmidt School of Medicine, Florida Atlantic University, Boca Raton, FL, USA
- Digestive Disease Institute at the Cleveland Clinic, Weston, FL, USA
| | - Richard Davis
- Division of Gastroenterology, Hepatology and Nutrition, University of Florida, Gainesville, FL, USA
| | - David Estores
- Division of Gastroenterology, Hepatology and Nutrition, University of Florida, Gainesville, FL, USA
| | - D Max Smith
- MedStar Health, Columbia, MD, USA
- Department of Oncology, Georgetown University Medical Center, Washington, DC, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL, USA.
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL, USA.
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14
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Abstract
Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.
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15
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Hayashi M, Hamdy DA, Mahmoud SH. Applications for pharmacogenomics in pharmacy practice: A scoping review. Res Social Adm Pharm 2021; 18:3094-3118. [PMID: 34474980 DOI: 10.1016/j.sapharm.2021.08.009] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/19/2021] [Accepted: 08/18/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Pharmacogenomics (PGx) can provide valuable pharmacokinetic and pharmacodynamic information for the pharmacist's assessment of drug therapy, especially within medication therapy management (MTM) services. However, no review has comprehensively mapped the pharmacists' use of PGx in practice-based research. Doing so would allow future researchers, practitioners, and policy-makers to identify the ideal populations and settings for PGx implementation within the pharmacy. OBJECTIVE The purpose of this review is to identify the evidence to date of PGx use in pharmacy practice. METHODS A scoping review was conducted to find all studied non-oncologic pharmacy practices incorporating PGx testing. Search terms were applied to 5 databases and relevant journals. Characteristics of patients, pharmacy settings, genetic tests, and outcomes were summarized to determine models most likely to benefit patients. RESULTS The search identified 43 studies on the use of PGx by pharmacists published between 2007 and 2020. CYP2C19 testing with antiplatelets was the most studied model, found in both community and institutional settings. It also was the most actionable test: approximately 30% of patients have polymorphisms indicating a need for alternative antiplatelets, and identifying these patients can reduce morbidity and mortality by more than 50%. As technology shifts, broader studies using multi-gene panel tests within MTM demonstrate an approximate 50% decrease in emergency visits and hospitalizations in elderly polypharmacy patients. Clinical benefit or drug-gene interactions are also found in other cardiovascular, psychiatric, analgesic, and gastrointestinal indications. No evaluations of actual costs or of pharmacist prescribing within pharmacy-based PGx have been performed. Facilitators towards successful PGx implementation included pharmacist education, collaboration with other healthcare providers, and the use of clinical decision software. CONCLUSIONS Pharmacogenomic testing has demonstrated feasibility and improved medication outcomes in pharmacy practice, including in the community pharmacy. Further PGx research should be directed towards pharmacist prescribing, pharmacist education, and pharmacoeconomics.
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Affiliation(s)
- Meagan Hayashi
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada.
| | - Dalia A Hamdy
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada; AbEx Health Services LTD, Fort Saskatchewan, Alberta, Canada.
| | - Sherif Hanafy Mahmoud
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, Alberta, Canada.
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16
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Multisite investigation of strategies for the clinical implementation of pre-emptive pharmacogenetic testing. Genet Med 2021; 23:2335-2341. [PMID: 34282303 PMCID: PMC8633054 DOI: 10.1038/s41436-021-01269-9] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/28/2021] [Accepted: 06/29/2021] [Indexed: 11/08/2022] Open
Abstract
PURPOSE The increased availability of clinical pharmacogenetic (PGx) guidelines and decreasing costs for genetic testing have slowly led to increased utilization of PGx testing in clinical practice. Pre-emptive PGx testing, where testing is performed in advance of drug prescribing, is one means to ensure results are available at the time of prescribing decisions. However, the most efficient and effective methods to clinically implement this strategy remain unclear. METHODS In this report, we compare and contrast implementation strategies for pre-emptive PGx testing by 15 early-adopter institutions. We surveyed these groups, collecting data on testing approaches, team composition, and workflow dynamics, in addition to estimated third-party reimbursement rates. RESULTS We found that while pre-emptive PGx testing models varied across sites, institutions shared several commonalities, including methods to identify patients eligible for testing, involvement of a precision medicine clinical team in program leadership, and the implementation of pharmacogenes with Clinical Pharmacogenetics Implementation Consortium guidelines available. Finally, while reimbursement rate data were difficult to obtain, the data available suggested that reimbursement rates for pre-emptive PGx testing remain low. CONCLUSION These findings should inform the establishment of future implementation efforts at institutions considering a pre-emptive PGx testing program.
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Cook KJ, Duong BQ, Seligson ND, Arn P, Funanage VL, Gripp KW, Kirwin SM, Lawless ST, Lee MM, Robbins KM, West D, Blake KV. Key Considerations for Selecting a Genomic Decision Support Platform for Implementing Pharmacogenomics. Clin Pharmacol Ther 2021; 110:555-558. [PMID: 34254671 DOI: 10.1002/cpt.2328] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/19/2021] [Indexed: 11/06/2022]
Affiliation(s)
- Kelsey J Cook
- Department of Pharmacotherapy and Translational Research, The University of Florida College of Pharmacy, Jacksonville, Florida, USA.,Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Benjamin Q Duong
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Nathan D Seligson
- Department of Pharmacotherapy and Translational Research, The University of Florida College of Pharmacy, Jacksonville, Florida, USA.,Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Pamela Arn
- Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Vicky L Funanage
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Karen W Gripp
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Susan M Kirwin
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Stephen T Lawless
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Mary M Lee
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Katherine M Robbins
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - David West
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Kathryn V Blake
- Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
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18
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Luczak T, Brown SJ, Armbruster D, Hundertmark M, Brown J, Stenehjem D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 2021; 22:345-364. [PMID: 33829852 DOI: 10.2217/pgs-2020-0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.
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Affiliation(s)
- Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, MN 55455, USA
| | - Danielle Armbruster
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Megan Hundertmark
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Jacob Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
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19
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Shah SN, Gammal RS, Amato MG, Alobaidly M, Reyes DD, Hasan S, Seger DL, Krier JB, Bates DW. Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events. Drug Saf 2021; 44:601-607. [PMID: 33620701 DOI: 10.1007/s40264-021-01050-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy. OBJECTIVE We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing. METHODS Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs. RESULTS Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction. CONCLUSION Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.
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Affiliation(s)
- Sonam N Shah
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA. .,Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA.
| | - Roseann S Gammal
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA.,Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Mary G Amato
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA.,Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Maryam Alobaidly
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Dariel Delos Reyes
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Sarah Hasan
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Diane L Seger
- Clinical Quality Analysis, Partners Healthcare, Somerville, MA, USA
| | - Joel B Krier
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - David W Bates
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA.,Clinical Quality Analysis, Partners Healthcare, Somerville, MA, USA.,Harvard Medical School, Boston, MA, USA
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20
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Venkatakrishnan K, van der Graaf PH, Holstein SA. The Changing Face of Oncology Research, Drug Development, and Clinical Practice: Toward Patient-Focused Precision Therapeutics. Clin Pharmacol Ther 2021; 108:399-404. [PMID: 33439492 DOI: 10.1002/cpt.1979] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Accepted: 06/26/2020] [Indexed: 12/19/2022]
Affiliation(s)
- Karthik Venkatakrishnan
- EMD Serono Research & Development Institute, Inc., Billerica, Massachusetts, USA.,A Business of, Merck KGaA, Darmstadt, Germany
| | | | - Sarah A Holstein
- Division of Oncology and Hematology, Department of Internal Medicine, University of Nebraska Medical Center, Omaha, Nebraska, USA
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Zammarchi G, Del Zompo M, Squassina A, Pisanu C. Increasing engagement in pharmacology and pharmacogenetics education using games and online resources: The PharmacoloGenius mobile app. Drug Dev Res 2020; 81:985-993. [PMID: 32633017 DOI: 10.1002/ddr.21714] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 12/31/2022]
Abstract
Mobile applications represent useful instruments to convey information and engage the users even during traveling, thanks to the wide diffusion of smartphones, tablets, smartwatches, and similar devices. As such, they have high potential as learning tools that can act complementary to traditional teaching approaches. In the field of pharmacology, mobile applications are increasingly being used to improve adherence of patients or to help them report suspect adverse drug reactions. However, they have been scarcely applied to pharmacology education. In this article, we present PharmacoloGenius, a free Android mobile application integrating resources useful for students as well as healthcare professionals or researchers to expand knowledge on pharmacological topics. We gave particular emphasis to pharmacogenetics, as it is a fundamental tool to achieve personalized treatment. The application offers original games such as pharmacological trivia based on textbooks or special "journal club" trivia based on research articles conveying the state of the art on specific topics. Additionally, the app offers a curated list of online resources to study pharmacology and pharmacogenetics (e.g., free online courses, videos, and databases) as well as updated news on conferences, grants, and opportunities for pharmacologists. In conclusion, PharmacoloGenius aims to be a useful instrument for people interested in expanding their knowledge on pharmacology in an engaging way.
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Affiliation(s)
- Gianpaolo Zammarchi
- Department of Economics and Business Science, University of Cagliari, Cagliari, Italy
| | - Maria Del Zompo
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessio Squassina
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Claudia Pisanu
- Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
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van der Graaf PH. Clinical Pharmacology and Therapeutics: 2020 in Review. Clin Pharmacol Ther 2020; 108:1117-1119. [PMID: 33185892 DOI: 10.1002/cpt.2061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 09/23/2020] [Indexed: 11/06/2022]
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Arwood MJ, Dietrich EA, Duong BQ, Smith DM, Cook K, Elchynski A, Rosenberg EI, Huber KN, Nagoshi YL, Wright A, Budd JT, Holland NP, Maska E, Panna D, Elsey AR, Cavallari LH, Wiisanen K, Johnson JA, Gums JG. Design and Early Implementation Successes and Challenges of a Pharmacogenetics Consult Clinic. J Clin Med 2020; 9:E2274. [PMID: 32708920 PMCID: PMC7408871 DOI: 10.3390/jcm9072274] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 12/13/2022] Open
Abstract
Pharmacogenetic testing (PGT) is increasingly being used as a tool to guide clinical decisions. This article describes the development of an outpatient, pharmacist-led, pharmacogenetics consult clinic within internal medicine, its workflow, and early results, along with successes and challenges. A pharmacogenetics-trained pharmacist encouraged primary care physicians (PCPs) to refer patients who were experiencing side effects/ineffectiveness from certain antidepressants, opioids, and/or proton pump inhibitors. In clinic, the pharmacist confirmed the need for and ordered CYP2C19 and/or CYP2D6 testing, provided evidence-based pharmacogenetic recommendations to PCPs, and educated PCPs and patients on the results. Operational and clinical metrics were analyzed. In two years, 91 referred patients were seen in clinic (mean age 57, 67% women, 91% European-American). Of patients who received PGT, 77% had at least one CYP2C19 and/or CYP2D6 phenotype that would make conventional prescribing unfavorable. Recommendations suggested that physicians change a medication/dose for 59% of patients; excluding two patients lost to follow-up, 87% of recommendations were accepted. Challenges included PGT reimbursement and referral maintenance. High frequency of actionable results suggests physician education on who to refer was successful and illustrates the potential to reduce trial-and-error prescribing. High recommendation acceptance rate demonstrates the pharmacist's effectiveness in providing genotype-guided recommendations, emphasizing a successful pharmacist-physician collaboration.
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Affiliation(s)
- Meghan J. Arwood
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Eric A. Dietrich
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
| | - Benjamin Q. Duong
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - D. Max Smith
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Kelsey Cook
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Amanda Elchynski
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Eric I. Rosenberg
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Katherine N. Huber
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Ying L. Nagoshi
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Ashleigh Wright
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Jeffrey T. Budd
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Neal P. Holland
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Edlira Maska
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Danielle Panna
- Division of General Internal Medicine, College of Medicine, University of Florida, 1329 SW 16th St, Gainesville, FL 32608, USA; (E.I.R.); (K.N.H.); (Y.L.N.); (A.W.); (J.T.B.); (N.P.H.); (E.M.); (D.P.)
| | - Amanda R. Elsey
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Clinical and Translational Science Institute, University of Florida, 2004 Mowry Rd, Gainesville, FL 32610, USA
| | - Larisa H. Cavallari
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
- Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA
| | - John G. Gums
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, 1345 Center Dr, Gainesville, FL 32603, USA; (E.A.D.); (B.Q.D.); (D.M.S.); (K.C.); (A.E.); (A.R.E.); (L.H.C.); (K.W.); (J.A.J.); (J.G.G.)
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