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Hoffecker G, Keat K, Mulugeta-Gordon L, Risman M, Verma SS, Deagostino-Kelly M, Tuteja S. Estimated clinical utility of multi-gene pharmacogenetic testing in a retrospective cohort of gynecology patients. Pharmacogenomics 2024:1-8. [PMID: 39545769 DOI: 10.1080/14622416.2024.2428585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Accepted: 11/08/2024] [Indexed: 11/17/2024] Open
Abstract
OBJECTIVE This study aimed to estimate the clinical utility of performing multi-gene pharmacogenetic testing on patients undergoing gynecologic surgery/procedure by evaluating the prescribing rate of Clinical Pharmacogenetics Implementation Consortium (CPIC) level A medications and frequency of drug-gene interactions (DGIs). METHODS The electronic health record was queried for 76 current procedural terminology codes to identify gynecologic surgeries/procedures that occurred between 1 January 2015 to 31 December 2020 in patients with at least one of 152 international classification of disease codes. Prescription data for CPIC level A medications was extracted. Those enrolled in the Penn Medicine Biobank were assessed for DGIs. RESULTS The cohort consisted of 7798 female patients and 682 were in the biobank. Up to 6 years following their surgery or procedure, 80% were ordered ≥1 CPIC level A medication. Over half (54%) of these medications were ordered within 3 days after their surgery or procedure. The most common CPIC level A medications ordered were ibuprofen (57%) and ondansetron (42%). Overall, 7% of the cohort had ≥1 known or predicted DGI with medications they were prescribed. CONCLUSION Multi-gene pharmacogenetic testing may be beneficial to gynecologic surgery/procedure patients by assisting clinicians with prescribing postoperative analgesics and future medications.
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Affiliation(s)
- Glenda Hoffecker
- Department of Pharmacy, Penn Medicine Hospital of University of Pennsylvania, Philadelphia, PA, USA
| | - Karl Keat
- Genomics & Computational Biology PhD Program, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
| | - Lakeisha Mulugeta-Gordon
- Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Penn Medicine Hospital of University of Pennsylvania, Philadelphia, PA, USA
| | - Marjorie Risman
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Shefali S Verma
- Department of Pathology & Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mary Deagostino-Kelly
- Division of General Obstetrics and Gynecology, Department of Obstetrics and Gynecology, Penn Medicine Hospital of the University of Pennsylvania, Philadelphia, PA, USA
| | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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2
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Shugg T, Tillman EM, Breman AM, Hodge JC, McDonald CA, Ly RC, Rowe EJ, Osei W, Smith TB, Schwartz PH, Callaghan JT, Pratt VM, Lynch S, Eadon MT, Skaar TC. Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned. Clin Pharmacol Ther 2024; 116:914-931. [PMID: 39169556 PMCID: PMC11452286 DOI: 10.1002/cpt.3402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/25/2024] [Indexed: 08/23/2024]
Abstract
In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.
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Affiliation(s)
- Tyler Shugg
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Emma M. Tillman
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Amy M. Breman
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jennelle C. Hodge
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Christine A. McDonald
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Reynold C. Ly
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Elizabeth J. Rowe
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Wilberforce Osei
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tayler B. Smith
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Peter H. Schwartz
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - John T. Callaghan
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Victoria M. Pratt
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sheryl Lynch
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T. Eadon
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Todd C. Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
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Wu A, Raack EJ, Ross CJD, Carleton BC. Implementation and Evaluation Strategies for Pharmacogenetic Testing in Hospital Settings: A Scoping Review. Ther Drug Monit 2024:00007691-990000000-00266. [PMID: 39264345 DOI: 10.1097/ftd.0000000000001243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 05/01/2024] [Indexed: 09/13/2024]
Abstract
BACKGROUND Pharmacogenetic testing in clinical settings has improved the safety and efficacy of drug treatment. There is a growing number of studies evaluating pharmacogenetic implementation and identifying barriers and facilitators. However, no review has focused on bridging the gap between identifying barriers and facilitators of testing and the clinical strategies adopted in response. This review was conducted to understand the implementation and evaluation strategies of pharmacogenetic testing programs. METHODS A PRISMA-compliant scoping review was conducted. The included studies discussed pharmacogenetic testing programs implemented in a hospital setting. Quantitative, qualitative, and mixed design methods were included. RESULTS A total of 232 of the 7043 articles that described clinical pharmacogenetic programs were included. The most common specialties that described pharmacogenetic implementation were psychiatry (26%) and oncology (16%), although many studies described institutional programs implemented across multiple specialties (19%). Different specialties reported different clinical outcomes, but all reported similar program performance indicators, such as test uptake and the number of times the test recommendations were followed. There were benefits and drawbacks to delivering test results through research personnel, pharmacists, and electronic alerts, but active engagement of physicians was necessary for the incorporation of pharmacogenetic results into clinical decision making. CONCLUSIONS Further research is required on the maintenance and sustainability of pharmacogenetic testing initiatives. These findings provide an overview of the implementation and evaluation strategies of different specialties that can be used to improve pharmacogenetic testing.
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Affiliation(s)
- Angela Wu
- Department of Experimental Medicine, University of British Columbia
- BC Children's Hospital Research Institute
| | - Edward J Raack
- BC Children's Hospital Research Institute
- Department of Medical Genetics, University of British Columbia
| | - Colin J D Ross
- BC Children's Hospital Research Institute
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia; and
| | - Bruce C Carleton
- BC Children's Hospital Research Institute
- Department of Medical Genetics, University of British Columbia
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia; and
- Therapeutic Evaluation Unit, Provincial Health Services Authority, Vancouver, British Columbia, Canada
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Farmaki A, Manolopoulos E, Natsiavas P. Will Precision Medicine Meet Digital Health? A Systematic Review of Pharmacogenomics Clinical Decision Support Systems Used in Clinical Practice. OMICS : A JOURNAL OF INTEGRATIVE BIOLOGY 2024; 28:442-460. [PMID: 39136110 DOI: 10.1089/omi.2024.0131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Digital health, an emerging scientific domain, attracts increasing attention as artificial intelligence and relevant software proliferate. Pharmacogenomics (PGx) is a core component of precision/personalized medicine driven by the overarching motto "the right drug, for the right patient, at the right dose, and the right time." PGx takes into consideration patients' genomic variations influencing drug efficacy and side effects. Despite its potentials for individually tailored therapeutics and improved clinical outcomes, adoption of PGx in clinical practice remains slow. We suggest that e-health tools such as clinical decision support systems (CDSSs) can help accelerate the PGx, precision/personalized medicine, and digital health emergence in everyday clinical practice worldwide. Herein, we present a systematic review that examines and maps the PGx-CDSSs used in clinical practice, including their salient features in both technical and clinical dimensions. Using Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines and research of the literature, 29 relevant journal articles were included in total, and 19 PGx-CDSSs were identified. In addition, we observed 10 technical components developed mostly as part of research initiatives, 7 of which could potentially facilitate future PGx-CDSSs implementation worldwide. Most of these initiatives are deployed in the United States, indicating a noticeable lack of, and the veritable need for, similar efforts globally, including Europe.
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Affiliation(s)
- Anastasia Farmaki
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Evangelos Manolopoulos
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, Alexandroupoli, Greece
| | - Pantelis Natsiavas
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
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Hashimi SR, Babatunde O, Alrajeh K, Dixon RJ, Okpeku A, Price ET. Pharmacogenomics in Clinical Practice for Older People. Sr Care Pharm 2024; 39:132-136. [PMID: 38528338 DOI: 10.4140/tcp.n.2024.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Older people are over-represented among individuals that experience adverse drug reactions (ADR) and adverse drug events (ADE). Furthermore, older people are over-represented among individuals that visit emergency departments and are hospitalized because of ADRs. Moreover, older people are overrepresented among those who suffer ADEs while hospitalized. Finally, older people are among those most likely to have an anaphylactic response to prescription medications. Therefore, older people are prime candidates for efforts aimed at optimizing pharmacotherapeutic outcomes. Pharmacogenomics is an approach of using genetic data to optimize pharmacotherapeutic outcomes. Over the last two decades, pharmacogenomics grew from research initiatives into the current environment of pharmacogenomics implementation. Specifically, implementing pharmacogenomics into clinical settings or within health care systems has proven beneficial in optimizing pharmacotherapeutic outcomes. Therefore, pharmacists focused on optimizing pharmacotherapeutic outcomes for older people should be aware of the approaches to and resources available for implementing pharmacogenomics. KEY WORDS: Drug labeling biomarkers, Genes, Older adults, Pharmacogenomics.
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Affiliation(s)
- Syeda R Hashimi
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Olajumoke Babatunde
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Khalifa Alrajeh
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Richard J Dixon
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Aimalohi Okpeku
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Elvin T Price
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
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Principi N, Petropulacos K, Esposito S. Impact of Pharmacogenomics in Clinical Practice. Pharmaceuticals (Basel) 2023; 16:1596. [PMID: 38004461 PMCID: PMC10675377 DOI: 10.3390/ph16111596] [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: 09/16/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.
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Affiliation(s)
| | | | - Susanna Esposito
- Pediatric Clinic, Department of Medicine and Surgery, University Hospital of Parma, 43126 Parma, Italy
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Haga SB. The Critical Role of Pharmacists in the Clinical Delivery of Pharmacogenetics in the U.S. PHARMACY 2023; 11:144. [PMID: 37736916 PMCID: PMC10514841 DOI: 10.3390/pharmacy11050144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 09/05/2023] [Accepted: 09/05/2023] [Indexed: 09/23/2023] Open
Abstract
Since the rebirth of pharmacogenomics (PGx) in the 1990s and 2000s, with new discoveries of genetic variation underlying adverse drug response and new analytical technologies such as sequencing and microarrays, there has been much interest in the clinical application of PGx testing. The early involvement of pharmacists in clinical studies and the establishment of organizations to support the dissemination of information about PGx variants have naturally resulted in leaders in clinical implementation. This paper presents an overview of the evolving role of pharmacists, and discusses potential challenges and future paths, primarily focused in the U.S. Pharmacists have positioned themselves as leaders in clinical PGx testing, and will prepare the next generation to utilize PGx testing in their scope of practice.
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Affiliation(s)
- Susanne B Haga
- Division of General Internal Medicine, Department of Medicine, School of Medicine, Duke University, 101 Science Drive, Durham, NC 27708, USA
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8
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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: 3] [Impact Index Per Article: 3.0] [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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Saepoo J, Pangsomboon K, Tianviwat S. Awareness of HLA-B* 15:02 screening in trigeminal neuralgia and the gene screening policy among dentists in Southern Thailand. SPECIAL CARE IN DENTISTRY 2023; 43:286-293. [PMID: 35973978 DOI: 10.1111/scd.12768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/26/2022] [Accepted: 07/26/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVES To determine the factors associated with public hospital dentists' awareness of HLA-B*15:02 screening in trigeminal neuralgia (TN) and the national gene screening policy in Thailand. METHODS Cross-sectional study. A validated questionnaire was distributed to public hospital dentists with at least 1 year of practice in Southern Thailand (n = 760) to assess their knowledge of TN, carbamazepine (CBZ) use, awareness of HLA-B*15:02 screening, and the gene screening policy. RESULTS A total of 385 dentists participated (50.7% response rate); 81.3% of respondents were aware of HLA-B*15:02 screening. However, 18.7% of dentists were not aware of the importance of gene testing. Furthermore, dentists who were aware of gene screening had significantly better knowledge of TN diagnosis and CBZ use than "unaware" dentists. Awareness of HLA-B*15:02 screening was also significantly associated with dental specialty. Moreover, 80.5% of respondents were not aware of the gene screening policy. The primary problems related to the policy were its inefficient publication, poor implementation, and lack of clinical practice guidelines (CPGs) to encourage dentists to follow the policy and prescribe gene tests. CONCLUSION While most hospital dentists were aware of the necessity of HLA-B*15:02 screening prior to prescribing CBZ in TN, the majority were unaware of the national gene screening policy. Dental specialty and knowledge were associated with awareness of HLA-B*15:02 screening.
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Affiliation(s)
- Jirayu Saepoo
- Section of Oral Medicine, Department of Oral Diagnostic Sciences, Faculty of Dentistry, Prince of Songkla University, Hatyai, Songkhla, Thailand
| | - Kanokporn Pangsomboon
- Section of Oral Medicine, Department of Oral Diagnostic Sciences, Faculty of Dentistry, Prince of Songkla University, Hatyai, Songkhla, Thailand
| | - Sukanya Tianviwat
- Department of Preventive Dentistry, Faculty of Dentistry, Prince of Songkla University, Hatyai, Songkhla, Thailand
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Cavallari LH, Pratt VM. Building Evidence for Clinical Use of Pharmacogenomics and Reimbursement for Testing. Clin Lab Med 2022; 42:533-546. [PMID: 36368780 PMCID: PMC9896522 DOI: 10.1016/j.cll.2022.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, PO Box 100486, Gainesville, FL 32610-0486, USA.
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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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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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13
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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: 17] [Impact Index Per Article: 8.5] [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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Sperber NR, Cragun D, Roberts MC, Bendz LM, Ince P, Gonzales S, Haga SB, Wu RR, Petry NJ, Ramsey L, Uber R. A Mixed-Methods Protocol to Identify Best Practices for Implementing Pharmacogenetic Testing in Clinical Settings. J Pers Med 2022; 12:1313. [PMID: 36013262 PMCID: PMC9410119 DOI: 10.3390/jpm12081313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/05/2022] [Accepted: 08/09/2022] [Indexed: 11/16/2022] Open
Abstract
Using a patient's genetic information to inform medication prescriptions can be clinically effective; however, the practice has not been widely implemented. Health systems need guidance on how to engage with providers to improve pharmacogenetic test utilization. Approaches from the field of implementation science may shed light on the complex factors affecting pharmacogenetic test use in real-world settings and areas to target to improve utilization. This paper presents an approach to studying the application of precision medicine that utilizes mixed qualitative and quantitative methods and implementation science frameworks to understand which factors or combinations consistently account for high versus low utilization of pharmocogenetic testing. This approach involves two phases: (1) collection of qualitative and quantitative data from providers-the cases-at four clinical institutions about their experiences with, and utilization of, pharmacogenetic testing to identify salient factors; and (2) analysis using a Configurational Comparative Method (CCM), using a mathematical algorithm to identify the minimally necessary and sufficient factors that distinguish providers who have higher utilization from those with low utilization. Advantages of this approach are that it can be used for small to moderate sample sizes, and it accounts for conditions found in real-world settings by demonstrating how they coincide to affect utilization.
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Affiliation(s)
- Nina R. Sperber
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
- Durham VA Health Care System, Durham, NC 27705, USA
| | - Deborah Cragun
- College of Public Health, University of South Florida, Tampa, FL 33612, USA
| | - Megan C. Roberts
- UNC Eshelman School of Pharmacy, University of North Carolina–Chapel Hill, Chapel Hill, NC 27599, USA
| | - Lisa M. Bendz
- Center for Medication Policy and Drug Information, Department of Pharmacy, Duke University Hospital, Durham, NC 27710, USA
| | - Parker Ince
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
| | - Sarah Gonzales
- Department of Population Health Sciences, School of Medicine, Duke University, Durham, NC 27701, USA
| | - Susanne B. Haga
- Department of Medicine, Duke University, Durham, NC 27701, USA
| | - R. Ryanne Wu
- Durham VA Health Care System, Durham, NC 27705, USA
- Department of Medicine, Duke University, Durham, NC 27701, USA
| | - Natasha J. Petry
- School of Pharmacy, North Dakota State University/Sanford Health Imagenetics, Fargo, ND 58108, USA
| | - Laura Ramsey
- Department of Pediatrics, Divisions of Clinical Pharmacology and Research in Patient Services, University of Cincinnati College of Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Ryley Uber
- Center for Pharmacy Innovation and Outcomes, Geisinger, Danville, CA 17822, USA
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15
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Blazy C, Ellingrod V, Ward K. Variability Between Clinical Pharmacogenetics Implementation Consortium (CPIC®) Guidelines and a Commercial Pharmacogenetics Laboratory in Genotype to Phenotype Interpretations For Patients Utilizing Psychotropics. Front Pharmacol 2022; 13:939313. [PMID: 35814245 PMCID: PMC9263441 DOI: 10.3389/fphar.2022.939313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 06/06/2022] [Indexed: 11/19/2022] Open
Abstract
Clinical practice environments without in-house pharmacogenetic testing often rely on commercial laboratories, especially in the setting of pharmacogenetic testing intended to guide psychotropic use. There are occasionally differences in phenotype assignment and medication recommendations between commercial laboratories and the Clinical Pharmacogenetics Implementation Consortium (CPIC). This may be problematic as many institutions that implement pharmacogenetics consider CPIC to be an important source of guidelines for recommended prescribing actions based on genetics, as well as a tool towards standardizing pharmacogenetics implementation. Here, we completed a retrospective chart review of our academic health system’s (Michigan Medicine) electronic health record with the goal of comparing phenotypic assignment of CYP2D6 and CYP2C19 genotypes between the commercial pharmacogenetic lab used most at our institution, and CPIC. Ultimately, we identified 205 patients with available pharmacogenetic results from this lab. The prevalence of conflicting phenotype assignment was 28.8% for CYP2D6 and 32.2% for CYP2C19 genotypes when comparing the commercial lab to CPIC guidelines. In several cases, the phenotypic assignment differences for antidepressants led to significant differences in medication recommendations when comparing the commercial lab report and CPIC guidelines. These results may also have implications for medications outside of psychiatry with recommendations for dose adjustments based on CYP2D6 or CYP2C19 metabolizing phenotype.
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Affiliation(s)
- Christopher Blazy
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States
| | - Vicki Ellingrod
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States
| | - Kristen Ward
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, MI, United States
- Clinical Pharmacy Department, Michigan Medicine, Ann Arbor, MI, United States
- *Correspondence: Kristen Ward,
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16
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Gammal RS, Fieg E. Pharmacist and genetic counselor collaboration in pharmacogenomics. Am J Health Syst Pharm 2022; 79:1516-1520. [PMID: 35732271 DOI: 10.1093/ajhp/zxac168] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.
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Affiliation(s)
- Roseann S Gammal
- Massachusetts College of Pharmacy and Health Sciences Boston, MA, USA
| | - Elizabeth Fieg
- Genetics & Genomic Medicine Service Brigham and Women's Hospital Boston, MA, USA
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17
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Sakon CM, Tillman EM. Pharmacogenomics: a tool to improve medication safety and efficacy in patients with cystic fibrosis. Pharmacogenomics 2022; 23:559-556. [PMID: 35670256 DOI: 10.2217/pgs-2022-0025] [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: 11/21/2022] Open
Abstract
Cystic fibrosis is a genetic, multiorgan system disease that involves the use of many medications to control symptoms associated with the underlying condition. Many of these medications have Clinical Pharmacogenetics Implementation Consortium evidence-based guidelines for pharmacogenomics that are available to guide dosing. The aim of this article is to review relevant literature and evaluate the utility of preemptive pharmacogenomics testing for persons with cystic fibrosis and propose a pharmacogenomics panel that could be considered standard of care for persons with cystic fibrosis.
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Affiliation(s)
- Colleen M Sakon
- Pharmacy Department, Indiana University Health, Indianapolis, IN, USA
| | - Emma M Tillman
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN, USA
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18
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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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19
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O'Shea J, Ledwidge M, Gallagher J, Keenan C, Ryan C. Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review. THE PHARMACOGENOMICS JOURNAL 2022; 22:89-99. [PMID: 35194175 PMCID: PMC8975737 DOI: 10.1038/s41397-021-00260-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 10/19/2021] [Accepted: 10/21/2021] [Indexed: 01/11/2023]
Abstract
Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.
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Affiliation(s)
- Joseph O'Shea
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Mark Ledwidge
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Joseph Gallagher
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | | | - Cristín Ryan
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland.
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20
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The Value of Pharmacogenetics to Reduce Drug-Related Toxicity in Cancer Patients. Mol Diagn Ther 2022; 26:137-151. [PMID: 35113367 PMCID: PMC8975257 DOI: 10.1007/s40291-021-00575-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/19/2021] [Indexed: 10/19/2022]
Abstract
Many anticancer drugs cause adverse drug reactions (ADRs) that negatively impact safety and reduce quality of life. The typical narrow therapeutic range and exposure-response relationships described for anticancer drugs make precision dosing critical to ensure safe and effective drug exposure. Germline mutations in pharmacogenes contribute to inter-patient variability in pharmacokinetics and pharmacodynamics of anticancer drugs. Patients carrying reduced-activity or loss-of-function alleles are at increased risk for ADRs. Pretreatment genotyping offers a proactive approach to identify these high-risk patients, administer an individualized dose, and minimize the risk of ADRs. In the field of oncology, the most well-studied gene-drug pairs for which pharmacogenetic dosing recommendations have been published to improve safety are DPYD-fluoropyrimidines, TPMT/NUDT15-thiopurines, and UGT1A1-irinotecan. Despite the presence of these guidelines, the scientific evidence showing the benefits of pharmacogenetic testing (e.g., improved safety and cost-effectiveness) and the development of efficient multi-gene genotyping panels, routine pretreatment testing for these gene-drug pairs has not been implemented widely in the clinic. Important considerations required for widespread clinical implementation include pharmacogenetic education of physicians, availability or allocation of institutional resources to build an efficient clinical infrastructure, international standardization of guidelines, uniform adoption of guidelines by regulatory agencies leading to genotyping requirements in drug labels, and development of cohesive reimbursement policies for pretreatment genotyping. Without clinical implementation, the potential of pharmacogenetics to improve patient safety remains unfulfilled.
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21
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Qureshi S, Latif A, Condon L, Akyea RK, Kai J, Qureshi N. Understanding the barriers and enablers of pharmacogenomic testing in primary care: a qualitative systematic review with meta-aggregation synthesis. Pharmacogenomics 2022; 23:135-154. [PMID: 34911350 PMCID: PMC8759425 DOI: 10.2217/pgs-2021-0131] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Introduction: Pharmacogenomic testing can indicate which drugs may have limited therapeutic action or lead to adverse effects, hence guiding rational and safe prescribing. However, in the UK and other countries, there are still significant barriers to implementation of testing in primary care. Objective: This systematic review presents the barriers and enablers to the implementation of pharmacogenomics in primary care setting. Materials & methods: MEDLINE, EMBASE, PsycINFO and CINAHL databases were searched through to July 2020 for studies that reported primary qualitative data of primary care professionals and patient views. Following screening, data extraction and quality assessment, data synthesis was undertaken using meta-aggregation based on the theoretical domain's framework (TDF). Confidence in the synthesized findings relating to credibility and dependability was established using CONQual. Eligible papers were categorized into six TDF domains - knowledge; social and professional roles; behavioral regulation; beliefs and consequences; environmental context and resources; and social influences. Results: From 1669 citations, eighteen eligible studies were identified across seven countries, with a sample size of 504 participants including both primary care professionals and patients. From the data, 15 synthesized statements, all with moderate CONQual rating emerged. These categories range from knowledge, awareness among Primary Care Physicians and patients, professional relationships, negative impact of PGx, belief that PGx can reduce adverse drug reactions, clinical evidence, cost-effectiveness, informatics, reporting issues and social issues. Conclusion: Through use of TDF, fifteen synthesized statements provide policymakers with valuable recommendations for the implementation of pharmacogenomics in primary care. In preparation, policymakers need to consider the introduction of effective educational strategies for both PCPs and patients to raise knowledge, awareness, and engagement. The actual introduction of PGx will require reorganization with decision support tools to aid use of PGx in primary care, with a clear delegation of roles and responsibilities between general professionals and pharmacists supplemented by a local pool of experts. Furthermore, policy makers need to address the cost effectiveness of pharmacogenomics and having appropriate infrastructure supporting testing and interpretation including informatic solutions for utilizing pharmacogenomic results.
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Affiliation(s)
- Sadaf Qureshi
- NHS Derby & Derbyshire Clinical Commissioning Group, Medicines Management,10 Nottingham Road, Derby, DE1 3QT, UK,Author for correspondence:
| | - Asam Latif
- School of Health Sciences, University Park, University of Nottingham, NG2 7RD, UK
| | - Laura Condon
- Primary Care Stratified Medicine Research Group (PRISM), School of Medicine, University Park, University of Nottingham, NG2 7RD, UK
| | - Ralph K Akyea
- Primary Care Stratified Medicine Research Group (PRISM), School of Medicine, University Park, University of Nottingham, NG2 7RD, UK
| | - Joe Kai
- Primary Care Stratified Medicine Research Group (PRISM), School of Medicine, University Park, University of Nottingham, NG2 7RD, UK
| | - Nadeem Qureshi
- Primary Care Stratified Medicine Research Group (PRISM), School of Medicine, University Park, University of Nottingham, NG2 7RD, UK
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22
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Qin W, Lu X, Shu Q, Duan H, Li H. Building an information system to facilitate pharmacogenomics clinical translation with clinical decision support. Pharmacogenomics 2021; 23:35-48. [PMID: 34787504 DOI: 10.2217/pgs-2021-0110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Pharmacogenomics clinical decision support (PGx-CDS) is an important tool to incorporate PGx information into existing clinical workflows and facilitate PGx clinical translation. However, due to the lack of a computable formalization to represent the primary PGx knowledge, the complexity of genomics information and the lag of current commercial electronic health record (EHR) system for precision medicine, it is difficult to develop computerized PGx-CDS. Therefore, we explored a novel approach to build an information system, named the Pharmacogenomics Clinical Translation Platform (PCTP), for PGx clinical implementation. The PCTP can represent, store, and manage the primary PGx knowledge in a structured and computable format. Moreover, it has the potential to provide various PGx-CDS services and simplify the integration of PGx-CDS into EHRs.
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Affiliation(s)
- Weifeng Qin
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China.,College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Xudong Lu
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Qiang Shu
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China
| | - Huilong Duan
- College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Haomin Li
- The Children's Hospital, Zhejiang University School of Medicine & National Clinical Research Center for Child Health, Hangzhou 310052, PR China
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Liu M, Van Driest SL, Vnencak-Jones CL, Saucier LAG, Roland BP, Gatto CL, Just SL, Weitkamp AO, Peterson JF. Impact of Updating Pharmacogenetic Results: Lessons Learned from the PREDICT Program. J Pers Med 2021; 11:jpm11111051. [PMID: 34834403 PMCID: PMC8617828 DOI: 10.3390/jpm11111051] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/09/2021] [Accepted: 10/13/2021] [Indexed: 12/26/2022] Open
Abstract
Pharmacogenomic (PGx) evidence for selective serotonin reuptake inhibitors (SSRIs) continues to evolve. For sites offering testing, maintaining up-to-date interpretations and implementing new clinical decision support (CDS) driven by existing results creates practical and technical challenges. Vanderbilt University Medical Center initiated panel testing in 2010, added CYP2D6 testing in 2017, and released CDS for SSRIs in 2020. We systematically reinterpreted historic CYP2C19 and CYP2D6 genotypes to update phenotypes to current nomenclature and to launch provider CDS and patient-oriented content for SSRIs. Chart review was conducted to identify and recontact providers caring for patients with current SSRI therapy and new actionable recommendations. A total of 15,619 patients’ PGx results were reprocessed. Of the non-deceased patients reprocessed, 21% (n = 3278) resulted in CYP2C19*1/*17 reinterpretations. Among 289 patients with an actionable recommendation and SSRI medication prescription, 31.8% (n = 92) did not necessitate contact of a clinician, while 43.2% (n = 125) resulted in clinician contacted, and for 25% (n = 72) no appropriate clinician was able to be identified. Maintenance of up-to-date interpretations and recommendations for PGx results over the lifetime of a patient requires continuous effort. Reprocessing is a key strategy for maintenance and expansion of PGx content to be periodically considered and implemented.
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Affiliation(s)
- Michelle Liu
- Department of Pharmacy, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Correspondence:
| | - Sara L. Van Driest
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Cindy L. Vnencak-Jones
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
- Department of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leigh Ann G. Saucier
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Bartholomew P. Roland
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
| | - Cheryl L. Gatto
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (L.A.G.S.); (B.P.R.); (C.L.G.)
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Shari L. Just
- Health IT Decision Support and Knowledge Engineering, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Asli O. Weitkamp
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
| | - Josh F. Peterson
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA; (S.L.V.D.); (J.F.P.)
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
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Rahma AT, Elbarazi I, Ali BR, Patrinos GP, Ahmed LA, Elsheik M, Al-Maskari F. Development of the pharmacogenomics and genomics literacy framework for pharmacists. Hum Genomics 2021; 15:62. [PMID: 34656176 PMCID: PMC8520199 DOI: 10.1186/s40246-021-00361-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Accepted: 10/05/2021] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Pharmacists play a unique role in integrating genomic medicine and pharmacogenomics into the clinical practice and to translate pharmacogenomics from bench to bedside. However, the literature suggests that the knowledge gap in pharmacogenomics is a major challenge; therefore, developing pharmacists' skills and literacy to achieve this anticipated role is highly important. We aim to conceptualize a personalized literacy framework for the adoption of genomic medicine and pharmacogenomics by pharmacists in the United Arab Emirates with possible regional and global relevance. RESULTS A qualitative approach using focus groups was used to design and to guide the development of a pharmacogenomics literacy framework. The Health Literacy Skills framework was used as a guide to conceptualize the pharmacogenomics literacy for pharmacists. The framework included six major components with specific suggested factors to improve pharmacists' pharmacogenomics literacy. Major components include individual inputs, demand, skills, knowledge, attitude and sociocultural factors. CONCLUSION This framework confirms a holistic bottom-up approach toward the implementation of pharmacogenomics. Personalized medicine entails personalized efforts and frameworks. Similar framework can be created for other healthcare providers, patients and stakeholders.
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Affiliation(s)
- Azhar T Rahma
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE
| | - Iffat Elbarazi
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE
| | - Bassam R Ali
- Department of Genetics and Genomics, College of Medicine and Health Science, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.,Zayed Center for Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE
| | - George P Patrinos
- Department of Genetics and Genomics, College of Medicine and Health Science, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.,Zayed Center for Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.,Department of Pharmacy, School of Health Sciences, University of Patras, 26504, Patras, Greece
| | - Luai A Ahmed
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.,Zayed Center for Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE
| | - Mahanna Elsheik
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.,Zayed Center for Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE
| | - Fatma Al-Maskari
- Institute of Public Health, College of Medicine and Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE. .,Zayed Center for Health Sciences, United Arab Emirates University, P.O. Box 17666, Al Ain, Abu Dhabi, UAE.
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25
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Clinical implementation of drug metabolizing gene-based therapeutic interventions worldwide. Hum Genet 2021; 141:1137-1157. [PMID: 34599365 DOI: 10.1007/s00439-021-02369-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/09/2021] [Indexed: 02/05/2023]
Abstract
Over the last few years, the field of pharmacogenomics has gained considerable momentum. The advances of new genomics and bioinformatics technologies propelled pharmacogenomics towards its implementation in the clinical setting. Since 2007, and especially the last-5 years, many studies have focused on the clinical implementation of pharmacogenomics while identifying obstacles and proposed strategies and approaches for overcoming them in the real world of primary care as well as outpatients and inpatients clinics. Here, we outline the recent pharmacogenomics clinical implementation projects and provide details of the study designs, including the most predominant and innovative, as well as clinical studies worldwide that focus on outpatients and inpatient clinics, and primary care. According to these studies, pharmacogenomics holds promise for improving patients' health in terms of efficacy and toxicity, as well as in their overall quality of life, while simultaneously can contribute to the minimization of healthcare expenditure.
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26
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Bright DR, Petry N, Roath E, Gibb T. Engaging pharmacogenomics in pain management and opioid selection. Pharmacogenomics 2021; 22:927-937. [PMID: 34521258 DOI: 10.2217/pgs-2021-0044] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Opioid misuse and mismanagement has been a public health crisis for several years. Pharmacogenomics (PGx) has been proposed as another tool to enhance opioid selection and optimization, with recent studies demonstrating successful implementation and outcomes. However, broad engagement with PGx for opioid management is presently limited. The purpose of this article is to highlight a series of barriers to PGx implementation within the specific context of opioid management. Areas of advancement needed for more robust pharmacogenomic engagement with opioids will be discussed, including clinical and economic research needs, education and training needs, policy and public health considerations, as well as legal and ethical issues. Continuing efforts to address these issues may help to further operationalize PGx toward improving opioid use.
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Affiliation(s)
- David R Bright
- Department of Pharmaceutical Sciences, Ferris State University College of Pharmacy, 220 Ferris Dr, Big Rapids, MI 49307, USA
| | - Natasha Petry
- Department of Pharmacy Practice, College of Health Professions, North Dakota State University, PO Box 6050, Fargo, ND 58108, USA.,Sanford Imagenetics, 1321 W 22nd St, Sioux Falls, SD 57105, USA
| | - Eric Roath
- SpartanNash, 1550 Gezon Parkway, Wyoming, MI 49509, USA
| | - Tyler Gibb
- Department of Medical Ethics, Humanities, & Law, Homer Stryker MD School of Medicine, Western Michigan University, 1000 Oakland Drive, Kalamazoo, MI 49008, USA
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27
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Zubiaur P, Mejía-Abril G, Navares-Gómez M, Villapalos-García G, Soria-Chacartegui P, Saiz-Rodríguez M, Ochoa D, Abad-Santos F. PriME-PGx: La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics. J Clin Med 2021; 10:jcm10173772. [PMID: 34501219 PMCID: PMC8432257 DOI: 10.3390/jcm10173772] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 12/18/2022] Open
Abstract
The implementation of clinical pharmacogenetics in daily practice is limited for various reasons. Today, however, it is a discipline in full expansion. Accordingly, in the recent times, several initiatives promoted its implementation, mainly in the United States but also in Europe. In this document, the genotyping results since the establishment of our Pharmacogenetics Unit in 2006 are described, as well as the historical implementation process that was carried out since then. Finally, this progress justified the constitution of La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx), promoted by the Clinical Pharmacology Department of Hospital Universitario de La Princesa (Madrid, Spain). Here, we present the initiative along with the two first ongoing projects: the PROFILE project, which promotes modernization of pharmacogenetic reporting (i.e., from classic gene-drug pair reporting to complete pharmacogenetic reporting or the creation of pharmacogenetic profiles specific to the Hospital’s departments) and the GENOTRIAL project, which promotes the communication of relevant pharmacogenetic findings to any healthy volunteer participating in any bioequivalence clinical trial at the Clinical Trials Unit of Hospital Universitario de La Princesa (UECHUP).
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Affiliation(s)
- Pablo Zubiaur
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
| | - Gina Mejía-Abril
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Marcos Navares-Gómez
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Gonzalo Villapalos-García
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Paula Soria-Chacartegui
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Miriam Saiz-Rodríguez
- Research Unit, Fundación Burgos por la Investigación de la Salud (FBIS), Hospital Universitario de Burgos, 09006 Burgos, Spain;
| | - Dolores Ochoa
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28200 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
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28
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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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29
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Hicks JK, El Rouby N, Ong HH, Schildcrout JS, Ramsey LB, Shi Y, Tang LA, Aquilante CL, Beitelshees AL, Blake KV, Cimino JJ, Davis BH, Empey PE, Kao DP, Lemkin DL, Limdi NA, Lipori GP, Rosenman MB, Skaar TC, Teal E, Tuteja S, Wiley LK, Williams H, Winterstein AG, Van Driest SL, Cavallari LH, Peterson JF. Opportunity for Genotype-Guided Prescribing Among Adult Patients in 11 US Health Systems. Clin Pharmacol Ther 2021; 110:179-188. [PMID: 33428770 PMCID: PMC8217370 DOI: 10.1002/cpt.2161] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 12/24/2020] [Indexed: 12/11/2022]
Abstract
The value of utilizing a multigene pharmacogenetic panel to tailor pharmacotherapy is contingent on the prevalence of prescribed medications with an actionable pharmacogenetic association. The Clinical Pharmacogenetics Implementation Consortium (CPIC) has categorized over 35 gene-drug pairs as "level A," for which there is sufficiently strong evidence to recommend that genetic information be used to guide drug prescribing. The opportunity to use genetic information to tailor pharmacotherapy among adult patients was determined by elucidating the exposure to CPIC level A drugs among 11 Implementing Genomics In Practice Network (IGNITE)-affiliated health systems across the US. Inpatient and/or outpatient electronic-prescribing data were collected between January 1, 2011 and December 31, 2016 for patients ≥ 18 years of age who had at least one medical encounter that was eligible for drug prescribing in a calendar year. A median of ~ 7.2 million adult patients was available for assessment of drug prescribing per year. From 2011 to 2016, the annual estimated prevalence of exposure to at least one CPIC level A drug prescribed to unique patients ranged between 15,719 (95% confidence interval (CI): 15,658-15,781) in 2011 to 17,335 (CI: 17,283-17,386) in 2016 per 100,000 patients. The estimated annual exposure to at least 2 drugs was above 7,200 per 100,000 patients in most years of the study, reaching an apex of 7,660 (CI: 7,632-7,687) per 100,000 patients in 2014. An estimated 4,748 per 100,000 prescribing events were potentially eligible for a genotype-guided intervention. Results from this study show that a significant portion of adults treated at medical institutions across the United States is exposed to medications for which genetic information, if available, should be used to guide prescribing.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Nihal El Rouby
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
- James Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH
| | - Henry H. Ong
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | | | - Laura B. Ramsey
- Department of Pediatrics, College of Medicine, University of Cincinnati, Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH
| | - Yaping Shi
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
| | - Leigh Anne Tang
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
| | - Christina L. Aquilante
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado, Aurora, CO
| | | | | | - James J. Cimino
- Informatics Institute, University of Alabama at Birmingham, Birmingham, AL
| | - Brittney H. Davis
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Philip E. Empey
- Department of Pharmacy & Therapeutics, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA
| | - David P. Kao
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL
| | - Gloria P. Lipori
- University of Florida Health and University of Florida Health Sciences Center, Gainesville, FL
| | - Marc B. Rosenman
- Indiana University School of Medicine, Indianapolis, IN
- Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL
| | - Todd C. Skaar
- Indiana University School of Medicine, Indianapolis, IN
| | | | - Sony Tuteja
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Laura K. Wiley
- School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | | | - Almut G. Winterstein
- Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL
| | - Sara L. Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | - Larisa H. Cavallari
- Department of Pharmacotherapy & Translational Research, University of Florida, Gainesville, FL
| | - Josh F. Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
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30
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Sasnovskaya V, Kumor LM, Stubbings J, Chevalier A. A pharmacist-managed virtual consult service to improve tuberculosis screening. Am J Health Syst Pharm 2021; 79:e41-e49. [PMID: 34170283 DOI: 10.1093/ajhp/zxab257] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
DISCLAIMER In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE To describe a pharmacist-managed virtual consult service practice model to improve medication safety in a population of rheumatology patients and evaluate its initial impact on guideline compliance. SUMMARY Optimal pharmacologic care of patients with rheumatologic conditions often revolves around the use of specialty medications such as self-injectable biologics and infused therapies, including biologic response modifiers (BRMs), nearly all of which carry risks of serious adverse events due to their immune-suppressive properties. Possible adverse events include serious infections such as reactivation of tuberculosis (TB) and viral hepatitis B (HBV). This articles describes a pharmacist-managed virtual consult service introduced by a large university-affiliated health system in 2018 to integrate clinical, specialty pharmacy, and therapeutic infusion services for proactive medication and safety management for patients with rheumatologic conditions requiring specialty or infused medications. During a 4-month evaluation period, 157 referrals were sent to the consult service; of 137 consults included in the analysis, 42% were for self-injectable biologic medications, 28% were for intra-articular injections, 26% were for infusions, and 4% were for oral specialty medications. Forty-one percent of the pharmacy benefit consult orders required an intervention prior to submission of prior authorization requests. Most interventions (61%) were clinical in nature and involved the pharmacists ensuring that necessary laboratory work, clinical disease activity scoring, or radiographic imaging were completed prior to submission of the consult results for insurer approval. CONCLUSION National rates of HBV screening and TB screening for patients prescribed BRMs continue to be suboptimal. The pharmacist-managed virtual consult service is a novel practice model to increase the screening rate to 100% to ensure the safety and appropriate monitoring of patients who are starting or continued on these complex medications.
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Affiliation(s)
| | - Lisa M Kumor
- University of Illinois at Chicago Hospital and Health Sciences System, Chicago, IL
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA
| | - JoAnn Stubbings
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA
| | - Aimee Chevalier
- Department of Pharmacy Practice, University of Illinois at Chicago College of Pharmacy, Chicago, IL, USA
- Arthritis and Kidney Center, University of Illinois Hospital and Health Sciences System, Chicago, IL
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31
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Luzum JA, Petry N, Taylor AK, Van Driest SL, Dunnenberger HM, Cavallari LH. Moving Pharmacogenetics Into Practice: It's All About the Evidence! Clin Pharmacol Ther 2021; 110:649-661. [PMID: 34101169 DOI: 10.1002/cpt.2327] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 05/27/2021] [Indexed: 12/19/2022]
Abstract
The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.
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Affiliation(s)
- Jasmine A Luzum
- Department of Clinical Pharmacy, College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA
| | - Natasha Petry
- Department of Pharmacy Practice, College of Health Professions, North Dakota State University, Fargo, North Dakota, USA.,Sanford Imagenetics, Sioux Falls, South Dakota, USA
| | - Annette K Taylor
- Colorado Coagulation, Laboratory Corporation of America Holdings, Englewood, Colorado, USA
| | - Sara L Van Driest
- Departments of Pediatrics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, Florida, USA
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Young J, Bhattacharya K, Ramachandran S, Lee A, Bentley JP. Rates of genetic testing in patients prescribed drugs with pharmacogenomic information in FDA-approved labeling. THE PHARMACOGENOMICS JOURNAL 2021; 21:318-325. [PMID: 33589791 PMCID: PMC7883752 DOI: 10.1038/s41397-021-00211-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 12/08/2020] [Accepted: 01/15/2021] [Indexed: 12/21/2022]
Abstract
This study examined rates of genetic testing in two cohorts of publicly insured individuals who have newly prescribed medication with FDA pharmacogenomic labeling guidance. Genetic testing was rare (4.4% and 10.5% in Medicaid and Medicare cohorts, respectively) despite the fact that all participants selected were taking medications that contained pharmacogenomic labeling information. When testing was conducted it was typically done before the initial use of a target medication. Factors that emerged as predictors of the likelihood of undergoing genetic testing included White ethnicity (vs. Black), female gender, and age. Cost analyses indicated higher expenditures in groups receiving genetic testing vs. matched comparators with no genetic testing, as well as disparities between proactively and reactively tested groups (albeit in opposite directions across cohorts). Results are discussed in terms of the possible reasons for the low base rate of testing, mechanisms of increased cost, and barriers to dissemination and implementation of these tests.
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Affiliation(s)
- John Young
- Department of Psychology, University of Mississippi, University, MS, USA.
| | - Kaustuv Bhattacharya
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
| | - Sujith Ramachandran
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
| | - Aaron Lee
- Department of Psychology, University of Mississippi, University, MS, USA
| | - John P Bentley
- Department of Pharmacy Administration, University of Mississippi, University, MS, USA
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Tillman EM, Beavers CJ, Afanasjeva J, Momary KM, Strnad KG, Yerramilli A, Williams AM, Smith BA, Florczykowski B, Fahmy M. Current and future state of clinical pharmacist‐led precision medicine initiatives. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2021. [DOI: 10.1002/jac5.1447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Monica Fahmy
- American College of Clinical Pharmacy Lenexa Kansas USA
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Hicks JK, Howard R, Reisman P, Adashek JJ, Fields KK, Gray JE, McIver B, McKee K, O'Leary MF, Perkins RM, Robinson E, Tandon A, Teer JK, Markowitz J, Rollison DE. Integrating Somatic and Germline Next-Generation Sequencing Into Routine Clinical Oncology Practice. JCO Precis Oncol 2021; 5:PO.20.00513. [PMID: 34095711 PMCID: PMC8169076 DOI: 10.1200/po.20.00513] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2020] [Revised: 02/14/2021] [Accepted: 04/20/2021] [Indexed: 12/27/2022] Open
Abstract
Next-generation sequencing (NGS) is rapidly expanding into routine oncology practice. Genetic variations in both the cancer and inherited genomes are informative for hereditary cancer risk, prognosis, and treatment strategies. Herein, we focus on the clinical perspective of integrating NGS results into patient care to assist with therapeutic decision making. Five key considerations are addressed for operationalization of NGS testing and application of results to patient care as follows: (1) NGS test ordering and workflow design; (2) result reporting, curation, and storage; (3) clinical consultation services that provide test interpretations and identify opportunities for molecularly guided therapy; (4) presentation of genetic information within the electronic health record; and (5) education of providers and patients. Several of these key considerations center on informatics tools that support NGS test ordering and referencing back to the results for therapeutic purposes. Clinical decision support tools embedded within the electronic health record can assist with NGS test utilization and identifying opportunities for targeted therapy including clinical trial eligibility. Challenges for project and change management in operationalizing NGS-supported, evidence-based patient care in the context of current information technology systems with appropriate clinical data standards are discussed, and solutions for overcoming barriers are provided.
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Affiliation(s)
- J. Kevin Hicks
- Department of Individualized Cancer Management, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
| | - Rachel Howard
- Department of Health Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Phillip Reisman
- Department of Health Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Jacob J. Adashek
- Department of Internal Medicine, University of South Florida, Tampa, FL
| | - Karen K. Fields
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Clinical Pathways, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Jhanelle E. Gray
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Thoracic Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Bryan McIver
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Head and Neck-Endocrine Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Kelly McKee
- Department of Clinical Pathways, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Mandy F. O'Leary
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Pathology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Randa M. Perkins
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Clinical Informatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Edmondo Robinson
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Internal Medicine, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Ankita Tandon
- Department of Internal Medicine, University of South Florida, Tampa, FL
| | - Jamie K. Teer
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Biostatistics and Bioinformatics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Joseph Markowitz
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Cutaneous Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
| | - Dana E. Rollison
- Department of Oncologic Sciences, University of South Florida, Tampa, FL
- Department of Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL
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Kisor DF, Petry NJ, Bright DR. Pharmacogenomics in the United States Community Pharmacy Setting: The Clopidogrel- CYP2C19 Example. Pharmgenomics Pers Med 2021; 14:569-577. [PMID: 34040417 PMCID: PMC8140945 DOI: 10.2147/pgpm.s224894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 04/26/2021] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenomics (PGx) is expanding across health-care practice settings, including the community pharmacy. In the United States, models of implementation of PGx in the community pharmacy have described independent services and those layered on to medication therapy management. The drug-gene pair of clopidogrel-CYP2C19 has been a focus of implementation of PGx in community pharmacy and serves as an example of the evolution of the application of drug-gene interaction information to help optimize drug therapy. Expanded information related to this drug-gene pair has been provided by the US Food and Drug Administration and clinical PGx guidelines have and continue to be updated to support clinical decision-making. Most recently direct-to-consumer (DTC) PGx has resulted in patient generated sample collection and submission to a genetic testing-related company for analysis, with reporting of genotype and related phenotype information directly to the patient without a health-care professional guiding or even being involved in the process. The DTC testing approach needs to be considered in the development or modification of PGx service models in the community pharmacy setting. The example of clopidogrel-CYP2C19 is discussed and current models of PGx implementation in the community pharmacy in the United States are presented. New approaches to PGx services are offered as implementation continues to evolve and may now include DTC information.
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Affiliation(s)
- David F Kisor
- Manchester University, Department of Pharmaceutical Sciences and Pharmacogenomics, Fort Wayne, IN, USA
| | - Natasha J Petry
- North Dakota State University, College of Health Professions, Department of Pharmacy Practice, Fargo, ND, USA
- Sanford Imagenetics, Sioux Falls, ND, USA
| | - David R Bright
- Ferris State University, Department of Pharmaceutical Sciences, Big Rapids, MI, USA
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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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37
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Liko I, Corbin L, Tobin E, Aquilante CL, Lee YM. Implementation of a pharmacist-provided pharmacogenomics service in an executive health program. Am J Health Syst Pharm 2021; 78:1094-1103. [PMID: 33772264 DOI: 10.1093/ajhp/zxab137] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
PURPOSE We describe the implementation of a pharmacist-provided pharmacogenomics (PGx) service in an executive health program (EHP) at an academic medical center. SUMMARY As interest in genomic testing grows, pharmacists have the opportunity to advance the use of PGx in EHPs, in collaboration with other healthcare professionals. In November 2018, a pharmacist-provided PGx service was established in the EHP at the University of Colorado Hospital. The team members included 3 physicians, a pharmacist trained in PGx, a registered dietitian/exercise physiologist, a nurse, and 2 medical assistants. We conducted 4 preimplementation steps: (1) assessment of the patient population, (2) selection of a PGx test, (3) establishment of a visit structure, and (4) selection of a billing model. The PGx consultations involved two 1-hour visits. The first visit encompassed pretest PGx education, review of the patient's current medications and previous medication intolerances, and DNA sample collection for genotyping. After this visit, the pharmacist developed a therapeutic plan based on the PGx test results, discussed the results and plan with the physician, and created a personalized PGx report. At the second visit, the pharmacist reviewed the PGx test results, personalized the PGx report, and discussed the PGx-guided therapeutic plan with the patient. Overall, the strategy worked well; minor challenges included evaluation of gene-drug pairs with limited PGx evidence, communication of information to non-EHP providers, scheduling issues, and reimbursement. CONCLUSION The addition of a PGx service within an EHP was feasible and provided pharmacists the opportunity to lead PGx efforts and collaborate with physicians to expand the precision medicine footprint at an academic medical center.
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Affiliation(s)
- Ina Liko
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO,USA
| | - Lisa Corbin
- Division of General Internal Medicine, University of Colorado School of Medicine, Aurora, CO,USA
| | - Eric Tobin
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO,USA
| | - Christina L Aquilante
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO,USA
| | - Yee Ming Lee
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, CO,USA
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Zhang Z, Yan C, Mesa DA, Sun J, Malin BA. Ensuring electronic medical record simulation through better training, modeling, and evaluation. J Am Med Inform Assoc 2021; 27:99-108. [PMID: 31592533 DOI: 10.1093/jamia/ocz161] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Revised: 07/29/2019] [Accepted: 08/15/2019] [Indexed: 12/15/2022] Open
Abstract
OBJECTIVE Electronic medical records (EMRs) can support medical research and discovery, but privacy risks limit the sharing of such data on a wide scale. Various approaches have been developed to mitigate risk, including record simulation via generative adversarial networks (GANs). While showing promise in certain application domains, GANs lack a principled approach for EMR data that induces subpar simulation. In this article, we improve EMR simulation through a novel pipeline that (1) enhances the learning model, (2) incorporates evaluation criteria for data utility that informs learning, and (3) refines the training process. MATERIALS AND METHODS We propose a new electronic health record generator using a GAN with a Wasserstein divergence and layer normalization techniques. We designed 2 utility measures to characterize similarity in the structural properties of real and simulated EMRs in the original and latent space, respectively. We applied a filtering strategy to enhance GAN training for low-prevalence clinical concepts. We evaluated the new and existing GANs with utility and privacy measures (membership and disclosure attacks) using billing codes from over 1 million EMRs at Vanderbilt University Medical Center. RESULTS The proposed model outperformed the state-of-the-art approaches with significant improvement in retaining the nature of real records, including prediction performance and structural properties, without sacrificing privacy. Additionally, the filtering strategy achieved higher utility when the EMR training dataset was small. CONCLUSIONS These findings illustrate that EMR simulation through GANs can be substantially improved through more appropriate training, modeling, and evaluation criteria.
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Affiliation(s)
- Ziqi Zhang
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Chao Yan
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA
| | - Diego A Mesa
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jimeng Sun
- College of Computing, Georgia Institute of Technology, Atlanta, Georgia, USA
| | - Bradley A Malin
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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39
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Caraballo PJ, Sutton JA, Giri J, Wright JA, Nicholson WT, Kullo IJ, Parkulo MA, Bielinski SJ, Moyer AM. Integrating pharmacogenomics into the electronic health record by implementing genomic indicators. J Am Med Inform Assoc 2021; 27:154-158. [PMID: 31591640 DOI: 10.1093/jamia/ocz177] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 08/19/2019] [Accepted: 09/11/2019] [Indexed: 12/27/2022] Open
Abstract
Pharmacogenomics (PGx) clinical decision support integrated into the electronic health record (EHR) has the potential to provide relevant knowledge to clinicians to enable individualized care. However, past experience implementing PGx clinical decision support into multiple EHR platforms has identified important clinical, procedural, and technical challenges. Commercial EHRs have been widely criticized for the lack of readiness to implement precision medicine. Herein, we share our experiences and lessons learned implementing new EHR functionality charting PGx phenotypes in a unique repository, genomic indicators, instead of using the problem or allergy list. The Gen-Ind has additional features including a brief description of the clinical impact, a hyperlink to the original laboratory report, and links to additional educational resources. The automatic generation of genomic indicators from interfaced PGx test results facilitates implementation and long-term maintenance of PGx data in the EHR and can be used as criteria for synchronous and asynchronous CDS.
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Affiliation(s)
- Pedro J Caraballo
- Division of General Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph A Sutton
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota
| | - Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Jessica A Wright
- Department of Pharmacy Services, Mayo Clinic, Rochester, Minnesota, USA
| | - Wayne T Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Mark A Parkulo
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
- Division of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
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40
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Roosan D, Hwang A, Roosan MR. Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy. THE PHARMACOGENOMICS JOURNAL 2021; 21:1-7. [PMID: 32843688 PMCID: PMC7840503 DOI: 10.1038/s41397-020-00182-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 06/18/2020] [Accepted: 08/12/2020] [Indexed: 11/08/2022]
Abstract
The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients' electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers.
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Affiliation(s)
- Don Roosan
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA.
| | - Angela Hwang
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA
| | - Moom R Roosan
- Department of Pharmacy Practice, School of Pharmacy, Chapman University, School of Pharmacy, Irvine, CA, USA.
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41
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Li D, Xie AH, Liu Z, Li D, Ning B, Thakkar S, Tong W, Xu J. Linking Pharmacogenomic Information on Drug Safety and Efficacy with Ethnic Minority Populations. Pharmaceutics 2020; 12:pharmaceutics12111021. [PMID: 33113799 PMCID: PMC7693750 DOI: 10.3390/pharmaceutics12111021] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 10/22/2020] [Accepted: 10/23/2020] [Indexed: 11/20/2022] Open
Abstract
Numerous prescription drugs’ labeling contains pharmacogenomic (PGx) information to aid health providers and patients in the safe and effective use of drugs. However, clinical studies for such PGx biomarkers and related drug doses are generally not conducted in diverse ethnic populations. Thus, it is urgently important to incorporate PGx information with genetic characteristics of racial and ethnic minority populations and utilize it to promote minority health. In this project a bioinformatics approach was developed to enhance the collection of PGx information related to ethnic minorities to pave the way toward understanding the population-wide utility of PGx information. To address this challenge, we first gathered PGx information from drug labels. Second, we extracted data on the allele frequency information of genetic variants in ethnic minority groups from public resources. Then, we collected published research articles on PGx biomarkers and related drugs for reference. Finally, the data were integrated and formatted to build a new PGx database containing information on known drugs and biomarkers for ethnic minority groups. This database provides scientific information needed to evaluate available PGx information to enhance drug dose selection and drug safety for ethnic minority populations.
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Affiliation(s)
- Dan Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
| | - April Hui Xie
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
- School of Pharmacy, Virginia Commonwealth University, Richmond, VA 23298, USA
| | - Zhichao Liu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
| | - Dongying Li
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
| | - Baitang Ning
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
| | - Shraddha Thakkar
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
- Office of Computational Sciences, Office of Translational Sciences, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA
| | - Weida Tong
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
| | - Joshua Xu
- Division of Bioinformatics and Biostatistics, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, AR 72079, USA; (D.L.); (A.H.X.); (Z.L.); (D.L.); (B.N.); (S.T.); (W.T.)
- Correspondence:
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J Sargent L, Mackiewicz M, Roman Y, Diallo A, Russell S, Falls K, Zimmerman KM, Dixon DL, Prom-Wormley E, Hobgood S, Lageman SK, Zanjani F, Price ET. The Translational Approaches to Personalized Health Collaborative: Pharmacogenomics for African American Older Adults. Clin Transl Sci 2020; 14:437-444. [PMID: 33026148 PMCID: PMC7993264 DOI: 10.1111/cts.12885] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 08/17/2020] [Indexed: 11/29/2022] Open
Abstract
Older adults (i.e., 60 years and older), are the leading consumers of medications, and consequently are suffering the most from medication‐related adverse events. Not only are older adults the largest consumers of medications, they are more likely to experience an adverse drug event contributing to increased hospitalization, utilization of emergency medical services, and mortality. Translational Approaches to Personalized Health (TAPH) is a transdisciplinary team of researchers conducting community‐engaged participatory research focused on the discovery and translation of pharmacogenomic (PGx) data to improve health outcomes. Underserved and ethnically diverse older adults living in urban settings are significantly under‐represented in PGx studies. To address the issue of under‐representation, our study enrolls older African American adults into a community‐based PGx study. Therefore, we will characterize the frequency of actionable PGx genotypes and identify novel PGx response genes in our cohort of older community dwelling African Americans. The translational component of our work is to use the PGx findings to improve therapeutic outcomes for medication management in older adults. Such findings will serve as a foundation for translational PGx studies aimed at improving medication efficacy and safety for older adults. In this article, we describe the process for launching the TAPH collaborative group, which includes the transdisciplinary team, community‐engaged participatory research model, study measures, and the evaluation of PGx genes.
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Affiliation(s)
- Lana J Sargent
- School of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.,Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA
| | - Marissa Mackiewicz
- Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.,Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Youssef Roman
- Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Ana Diallo
- School of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA.,Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA
| | - Sally Russell
- School of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Katherine Falls
- School of Nursing, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Kristin M Zimmerman
- Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Center for Pharmacy Practice Innovation, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Dave L Dixon
- Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Center for Pharmacy Practice Innovation, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Elizabeth Prom-Wormley
- Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.,Division of Epidemiology, Department of Family Medicine and Population Health, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Sarah Hobgood
- School of Medicine, Department of Geriatrics, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Sarah K Lageman
- School of Medicine, Neuropsychology Program Director and Department of Neurology, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Faika Zanjani
- Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.,Department of Gerontology, College of Health Professions, Virginia Commonwealth University, Richmond, Virginia, USA
| | - Elvin T Price
- Geriatric Pharmacotherapy Program, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA.,Institute for Inclusion, Inquiry and Innovation (iCubed): Health and Wellness in Aging Populations Core, Richmond, Virginia, USA.,Department of Pharmacotherapy and Outcomes Science, School of Pharmacy, Virginia Commonwealth University, Richmond, Virginia, USA
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Chang WC, Tanoshima R, Ross CJD, Carleton BC. Challenges and Opportunities in Implementing Pharmacogenetic Testing in Clinical Settings. Annu Rev Pharmacol Toxicol 2020; 61:65-84. [PMID: 33006916 DOI: 10.1146/annurev-pharmtox-030920-025745] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The clinical implementation of pharmacogenetic biomarkers continues to grow as new genetic variants associated with drug outcomes are discovered and validated. The number of drug labels that contain pharmacogenetic information also continues to expand. Published, peer-reviewed clinical practice guidelines have also been developed to support the implementation of pharmacogenetic tests. Incorporating pharmacogenetic information into health care benefits patients as well as clinicians by improving drug safety and reducing empiricism in drug selection. Barriers to the implementation of pharmacogenetic testing remain. This review explores current pharmacogenetic implementation initiatives with a focus on the challenges of pharmacogenetic implementation and potential opportunities to overcome these challenges.
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Affiliation(s)
- Wan-Chun Chang
- Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia V6H 3V4, Canada; .,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Reo Tanoshima
- Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia V6H 3V4, Canada; .,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
| | - Colin J D Ross
- BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada.,Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Bruce C Carleton
- Division of Translational Therapeutics, Department of Pediatrics, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia V6H 3V4, Canada; .,BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada.,Pharmaceutical Outcomes Programme, BC Children's Hospital Research Institute, Vancouver, British Columbia V5Z 4H4, Canada
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Zhong M, van der Walt A, Campagna MP, Stankovich J, Butzkueven H, Jokubaitis V. The Pharmacogenetics of Rituximab: Potential Implications for Anti-CD20 Therapies in Multiple Sclerosis. Neurotherapeutics 2020; 17:1768-1784. [PMID: 33058021 PMCID: PMC7851267 DOI: 10.1007/s13311-020-00950-2] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/09/2020] [Indexed: 12/13/2022] Open
Abstract
There are a broad range of disease-modifying therapies (DMTs) available in relapsing-remitting multiple sclerosis (RRMS), but limited biomarkers exist to personalise DMT choice. All DMTs, including monoclonal antibodies such as rituximab and ocrelizumab, are effective in preventing relapses and preserving neurological function in MS. However, each agent harbours its own risk of therapeutic failure or adverse events. Pharmacogenetics, the study of the effects of genetic variation on therapeutic response or adverse events, could improve the precision of DMT selection. Pharmacogenetic studies of rituximab in MS patients are lacking, but pharmacogenetic markers in other rituximab-treated autoimmune conditions have been identified. This review will outline the wider implications of pharmacogenetics and the mechanisms of anti-CD20 agents in MS. We explore the non-MS rituximab literature to characterise pharmacogenetic variants that could be of prognostic relevance in those receiving rituximab, ocrelizumab or other monoclonal antibodies for MS.
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Affiliation(s)
- Michael Zhong
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia.
- Department of Neurology, Alfred Health, Level 6, Alfred Centre, 99 Commercial Road, Melbourne, Victoria, 3004, Australia.
| | - Anneke van der Walt
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Level 6, Alfred Centre, 99 Commercial Road, Melbourne, Victoria, 3004, Australia
| | - Maria Pia Campagna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Jim Stankovich
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Level 6, Alfred Centre, 99 Commercial Road, Melbourne, Victoria, 3004, Australia
| | - Vilija Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Level 6, Alfred Centre, 99 Commercial Road, Melbourne, Victoria, 3004, Australia
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45
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Hoffman JM, Flynn AJ, Juskewitch JE, Freimuth RR. Biomedical Data Science and Informatics Challenges to Implementing Pharmacogenomics with Electronic Health Records. Annu Rev Biomed Data Sci 2020. [DOI: 10.1146/annurev-biodatasci-020320-093614] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic information must be incorporated into electronic health records (EHRs) with clinical decision support in order to fully realize its potential to improve drug therapy. Supported by various clinical knowledge resources, pharmacogenomic workflows have been implemented in several healthcare systems. Little standardization exists across these efforts, however, which limits scalability both within and across clinical sites. Limitations in information standards, knowledge management, and the capabilities of modern EHRs remain challenges for the widespread use of pharmacogenomics in the clinic, but ongoing efforts are addressing these challenges. Although much work remains to use pharmacogenomic information more effectively within clinical systems, the experiences of pioneering sites and lessons learned from those programs may be instructive for other clinical areas beyond genomics. We present a vision of what can be achieved as informatics and data science converge to enable further adoption of pharmacogenomics in the clinic.
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Affiliation(s)
- James M. Hoffman
- Department of Pharmaceutical Sciences and the Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Allen J. Flynn
- Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Justin E. Juskewitch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Center for Individualized Medicine, and Information and Knowledge Management, Mayo Clinic, Rochester, Minnesota 55905, USA
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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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47
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Duong BQ, Arwood MJ, Hicks JK, Beitelshees AL, Franchi F, Houder JT, Limdi NA, Cook KJ, Owusu Obeng A, Petry N, Tuteja S, Elsey AR, Cavallari LH, Wiisanen K. Development of Customizable Implementation Guides to Support Clinical Adoption of Pharmacogenomics: Experiences of the Implementing GeNomics In pracTicE (IGNITE) Network. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2020; 13:217-226. [PMID: 32765043 PMCID: PMC7373415 DOI: 10.2147/pgpm.s241599] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Accepted: 05/08/2020] [Indexed: 12/13/2022]
Abstract
Introduction Clinical adoption of genomic medicine has lagged behind the pace of scientific discovery. Practice-based resources can help overcome implementation challenges. Methods In 2015, the IGNITE (Implementing GeNomics In pracTicE) Network created an online genomic medicine implementation resource toolbox that was expanded in 2017 to incorporate the ability for users to create targeted implementation guides. This expansion was led by a multidisciplinary team that developed an evidence-based, structured framework for the guides, oversaw the technical process/build, and pilot tested the first guide, CYP2C19-Clopidogrel Testing Implementation. Results Sixty-five resources were collected from 12 institutions and categorized according to a seven-step implementation framework for the pilot CYP2C19-Clopidogrel Testing Implementation Guide. Five months after its launch, 96 CYP2C19-Clopidogrel Testing Implementation Guides had been created. Eighty percent of the resources most frequently selected by users were created by IGNITE to fill an identified resource gap. Resources most often included in guides were from the test reimbursement (22%), Implementation support gathering (22%), EHR integration (17%), and genetic testing workflow steps (17%). Conclusion Lessons learned from this implementation guide development process provide insight for prioritizing development of future resources and support the value of collaborative efforts to create resources for genomic medicine implementation.
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Affiliation(s)
- Benjamin Q Duong
- Department of Precision Medicine, Nemours/Alfred I. DuPont Hospital for Children, Wilmington, DE, USA
| | - Meghan J Arwood
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics & Precision Medicine, University of Florida College of Pharmacy, Gainesville, FL, USA
| | - J Kevin Hicks
- Department of Individualized Cancer Management, Moffitt Cancer Center, Tampa, FL, USA
| | - Amber L Beitelshees
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Francesco Franchi
- Department of Cardiology, University of Florida College of Medicine, Jacksonville, FL, USA
| | - John T Houder
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics & Precision Medicine, University of Florida College of Pharmacy, Gainesville, FL, USA
| | - Nita A Limdi
- University of Alabama School at Birmingham, Birmingham, AL, USA
| | - Kelsey J Cook
- Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Jacksonville, FL, USA.,Department of Precision Medicine, Nemours Children's Specialty Care, Jacksonville, FL, USA
| | - Aniwaa Owusu Obeng
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Natasha Petry
- Department of Pharmacy Practice, North Dakota State University College of Health Professions, Fargo, ND, USA
| | - Sony Tuteja
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Amanda R Elsey
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics & Precision Medicine, University of Florida College of Pharmacy, Gainesville, FL, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics & Precision Medicine, University of Florida College of Pharmacy, Gainesville, FL, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics & Precision Medicine, University of Florida College of Pharmacy, Gainesville, FL, USA
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Levchenko A, Nurgaliev T, Kanapin A, Samsonova A, Gainetdinov RR. Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders. Heliyon 2020; 6:e03990. [PMID: 32462093 PMCID: PMC7240336 DOI: 10.1016/j.heliyon.2020.e03990] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Revised: 10/31/2019] [Accepted: 05/12/2020] [Indexed: 12/13/2022] Open
Abstract
A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.
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Affiliation(s)
- Anastasia Levchenko
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Timur Nurgaliev
- Institute of Translational Biomedicine, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Alexander Kanapin
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Anastasia Samsonova
- Theodosius Dobzhansky Center for Genome Bioinformatics, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
| | - Raul R. Gainetdinov
- Institute of Translational Biomedicine, Saint Petersburg State University, 7/9 Universitetskaya nab., Saint Petersburg, 199034, Russia
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49
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Aquilante CL, Kao DP, Trinkley KE, Lin CT, Crooks KR, Hearst EC, Hess SJ, Kudron EL, Lee YM, Liko I, Lowery J, Mathias RA, Monte AA, Rafaels N, Rioth MJ, Roberts ER, Taylor MR, Williamson C, Barnes KC. Clinical implementation of pharmacogenomics via a health system-wide research biobank: the University of Colorado experience. Pharmacogenomics 2020; 21:375-386. [PMID: 32077359 PMCID: PMC7226704 DOI: 10.2217/pgs-2020-0007] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.
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Affiliation(s)
- Christina L Aquilante
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - David P Kao
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Katy E Trinkley
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Chen-Tan Lin
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,University of Colorado Health, Aurora, CO 80045, USA
| | - Kristy R Crooks
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | | | - Steven J Hess
- University of Colorado Health, Aurora, CO 80045, USA
| | - Elizabeth L Kudron
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Yee Ming Lee
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Ina Liko
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA.,Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Jan Lowery
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Rasika A Mathias
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Andrew A Monte
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Matthew J Rioth
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Emily R Roberts
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | - Matthew Rg Taylor
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
| | | | - Kathleen C Barnes
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO 80045, USA
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50
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Cost-effectiveness of CYP2C19-guided antiplatelet therapy in patients with acute coronary syndrome and percutaneous coronary intervention informed by real-world data. THE PHARMACOGENOMICS JOURNAL 2020; 20:724-735. [PMID: 32042096 DOI: 10.1038/s41397-020-0162-5] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 01/25/2020] [Accepted: 01/29/2020] [Indexed: 12/25/2022]
Abstract
Current guidelines recommend dual antiplatelet therapy (DAPT) consisting of aspirin and a P2Y12 inhibitors following percutaneous coronary intervention (PCI). CYP2C19 genotype can guide DAPT selection, prescribing ticagrelor or prasugrel for loss-of-function (LOF) allele carriers (genotype-guided escalation). Cost-effectiveness analyses (CEA) are traditionally grounded in clinical trial data. We conduct a CEA using real-world data using a 1-year decision-analytic model comparing primary strategies: universal empiric clopidogrel (base case), universal ticagrelor, and genotype-guided escalation. We also explore secondary strategies commonly implemented in practice, wherein all patients are prescribed ticagrelor for 30 days post PCI. After 30 days, all patients are switched to clopidogrel irrespective of genotype (nonguided de-escalation) or to clopidogrel only if patients do not harbor an LOF allele (genotype-guided de-escalation). Compared with universal clopidogrel, both universal ticagrelor and genotype-guided escalation were superior with improvement in quality-adjusted life years (QALY's). Only genotype-guided escalation was cost-effective ($42,365/QALY) and demonstrated the highest probability of being cost-effective across conventional willingness-to-pay thresholds. In the secondary analysis, compared with the nonguided de-escalation strategy, although genotype-guided de-escalation and universal ticagrelor were more effective, with ICER of $188,680/QALY and $678,215/QALY, respectively, they were not cost-effective. CYP2C19 genotype-guided antiplatelet prescribing is cost-effective compared with either universal clopidogrel or universal ticagrelor using real-world implementation data. The secondary analysis suggests genotype-guided and nonguided de-escalation may be viable strategies, needing further evaluation.
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