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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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2
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Shriver SP, Adams D, McKelvey BA, McCune JS, Miles D, Pratt VM, Ashcraft K, McLeod HL, Williams H, Fleury ME. Overcoming Barriers to Discovery and Implementation of Equitable Pharmacogenomic Testing in Oncology. J Clin Oncol 2024:JCO2301748. [PMID: 38386947 DOI: 10.1200/jco.23.01748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/08/2023] [Accepted: 12/12/2023] [Indexed: 02/24/2024] Open
Abstract
Pharmacogenomics (PGx), the study of inherited genomic variation and drug response or safety, is a vital tool in precision medicine. In oncology, testing to identify PGx variants offers patients the opportunity for customized treatments that can minimize adverse effects and maximize the therapeutic benefits of drugs used for cancer treatment and supportive care. Because individuals of shared ancestry share specific genetic variants, PGx factors may contribute to outcome disparities across racial and ethnic categories when genetic ancestry is not taken into account or mischaracterized in PGx research, discovery, and application. Here, we examine how the current scientific understanding of the role of PGx in differential oncology safety and outcomes may be biased toward a greater understanding and more complete clinical implementation of PGx for individuals of European descent compared with other genetic ancestry groups. We discuss the implications of this bias for PGx discovery, access to care, drug labeling, and patient and provider understanding and use of PGx approaches. Testing for somatic genetic variants is now the standard of care in treatment of many solid tumors, but the integration of PGx into oncology care is still lacking despite demonstrated actionable findings from PGx testing, reduction in avoidable toxicity and death, and return on investment from testing. As the field of oncology is poised to expand and integrate germline genetic variant testing, it is vital that PGx discovery and application are equitable for all populations. Recommendations are introduced to address barriers to facilitate effective and equitable PGx application in cancer care.
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Affiliation(s)
| | | | | | - Jeannine S McCune
- City of Hope/Beckman Research Institute Department of Hematologic Malignancies Translational Sciences, Duarte, CA
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3
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Bui VL, Alvarez-Arango S, Stevenson JM. Pharmacogenetics to prevent hypersensitivity reactions to antiepileptic drugs: is testing performed when indicated? Pharmacogenet Genomics 2024; 34:16-19. [PMID: 37830946 PMCID: PMC10841751 DOI: 10.1097/fpc.0000000000000510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Extensive scientific evidence consistently demonstrates the clinical validity and utility of HLA-B*15:02 pre-screening in averting severe cutaneous adverse reactions (SCARs), namely Stevens-Johnson syndrome and toxic epidermal necrolysis, associated with carbamazepine or oxcarbazepine usage. Current practice guidelines and drug labeling actively advocate for pharmacogenetic pre-screening before initiating these antiepileptic drugs (AED), with particular emphasis on patients of Asian descent. However, there is a potential need to strengthen compliance with these recommendations. This retrospective study aimed to describe the pharmacogenetic pre-screening, documentation, and SCARs incidence for patients of Asian ancestry initiated on carbamazepine or oxcarbazepine at a large Northeastern USA healthcare system. Between 1 July 2016 and August 1, 2021, 27 patients with documented Asian heritage in the electronic health record (EHR) were included. The overall rate of HLA-B*15:02 pre-screening before carbamazepine or oxcarbazepine initiation was 4%. None who underwent pharmacogenetic pre-screening carried the associated HLA-B risk allele, and no SCARs were reported. Notably, pharmacogenetic results were not discretely entered into the EHR, and the results were only found as attached documents in the miscellaneous section of the EHR. There remains a significant opportunity for improving HLA-B*15:02 pre-screening for patients starting carbamazepine and oxcarbazepine to prevent SCARs in the USA.
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Affiliation(s)
- Vy L. Bui
- Department of Pharmacy, The Johns Hopkins Hospital, Baltimore, MD
| | - Santiago Alvarez-Arango
- Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Division of Allergy and Clinical Immunology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
| | - James M. Stevenson
- Division of Clinical Pharmacology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD
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4
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Cecchin E, Posocco B, Mezzalira S, Appetecchia M, Toffoli G. The Role of Gender Pharmacogenetics in the Personalization of Drug Treatment. J Pharmacol Exp Ther 2023; 386:190-197. [PMID: 37001987 DOI: 10.1124/jpet.122.001416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 03/21/2023] [Indexed: 07/20/2023] Open
Abstract
The use of pharmacogenetic guidelines in personalizing treatments has shown the potential to reduce interindividual variability in drug response by enabling genotype-matched dosing and drug selection. However, other important factors, such as patient gender, may interact strongly with pharmacogenetics in determining the individual profile of toxicity and efficacy but are still rarely considered when planning pharmacological treatment. The literature indicates that males and females respond differently to drugs, with women being at higher risk for toxicity and having different plasma exposure to drugs at standard doses. Recent studies have shown that pharmacogenetic variants may have different predictive value in different sexes, as in the case of treatment with opioids, angiotensin-converting enzyme inhibitors, or proton pump inhibitors. Of particular interest is the case of treatment with fluoropyrimidines for cancer. A significant increase in toxicity has been described in female patients, with a more pronounced effect of specific DPYD and TYMS polymorphisms also noted. This manuscript reviews the major findings in the field of sex-specific pharmacogenomics. SIGNIFICANCE STATEMENT: Interindividual variability in drug response is an emerging issue in pharmacology. The genetic profile of patients, as well as their gender, may play a role in the identification of patients more exposed to the risk of adverse drug reactions or poor efficacy. This article reviews the current state of research on the interaction between gender and pharmacogenetics in addressing interindividual variability.
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Affiliation(s)
- Erika Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Bianca Posocco
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Silvia Mezzalira
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Marialuisa Appetecchia
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
| | - Giuseppe Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano PN, Italy (E.C., B.P., S.M., G.T.); and Oncological Endocrinology Unit, IRCCS Regina Elena National Cancer Institute-IFO, Rome, Italy (M.A.)
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5
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Smith DM, Wake DT, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Scoping Review. Clin Pharmacol Ther 2023; 113:803-815. [PMID: 35838358 DOI: 10.1002/cpt.2711] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 07/10/2022] [Indexed: 11/06/2022]
Abstract
Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed.
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Affiliation(s)
- D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, District of Columbia, USA
| | - Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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6
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Dolin RH, Heale BSE, Alterovitz G, Gupta R, Aronson J, Boxwala A, Gothi SR, Haines D, Hermann A, Hongsermeier T, Husami A, Jones J, Naeymi-Rad F, Rapchak B, Ravishankar C, Shalaby J, Terry M, Xie N, Zhang P, Chamala S. Introducing HL7 FHIR Genomics Operations: a developer-friendly approach to genomics-EHR integration. J Am Med Inform Assoc 2022; 30:485-493. [PMID: 36548217 PMCID: PMC9933060 DOI: 10.1093/jamia/ocac246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/16/2022] [Accepted: 12/02/2022] [Indexed: 12/24/2022] Open
Abstract
OBJECTIVE Enabling clinicians to formulate individualized clinical management strategies from the sea of molecular data remains a fundamentally important but daunting task. Here, we describe efforts towards a new paradigm in genomics-electronic health record (HER) integration, using a standardized suite of FHIR Genomics Operations that encapsulates the complexity of molecular data so that precision medicine solution developers can focus on building applications. MATERIALS AND METHODS FHIR Genomics Operations essentially "wrap" a genomics data repository, presenting a uniform interface to applications. More importantly, operations encapsulate the complexity of data within a repository and normalize redundant data representations-particularly relevant in genomics, where a tremendous amount of raw data exists in often-complex non-FHIR formats. RESULTS Fifteen FHIR Genomics Operations have been developed, designed to support a wide range of clinical scenarios, such as variant discovery; clinical trial matching; hereditary condition and pharmacogenomic screening; and variant reanalysis. Operations are being matured through the HL7 balloting process, connectathons, pilots, and the HL7 FHIR Accelerator program. DISCUSSION Next-generation sequencing can identify thousands to millions of variants, whose clinical significance can change over time as our knowledge evolves. To manage such a large volume of dynamic and complex data, new models of genomics-EHR integration are needed. Qualitative observations to date suggest that freeing application developers from the need to understand the nuances of genomic data, and instead base applications on standardized APIs can not only accelerate integration but also dramatically expand the applications of Omic data in driving precision care at scale for all.
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Affiliation(s)
- Robert H Dolin
- Corresponding Author: Robert H. Dolin, MD, Elimu Informatics, 1709 Julian Ct, El Cerrito, CA 94530, USA;
| | | | - Gil Alterovitz
- Brigham and Women’s Hospital, Boston, Massachusetts, USA,Harvard/MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, Massachusetts, USA
| | - Rohan Gupta
- Shri Mata Vaishno Devi University, Katra, Jammu and Kashmir, India
| | | | | | - Shaileshbhai R Gothi
- Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, USA
| | - David Haines
- Leap of Faith Technologies, Libertyville, Illinois, USA
| | - Arthur Hermann
- Department of Health IT Strategy & Policy, Kaiser Permanente, Pasadena, California, USA
| | | | - Ammar Husami
- Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - James Jones
- Computational Health Informatics Program, Boston Children’s Hospital, Boston, Massachusetts, USA
| | | | | | | | | | - May Terry
- MITRE Corporation, McLean, Virginia, USA
| | - Ning Xie
- Biomedical Cybernetics Laboratory, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts, USA
| | - Powell Zhang
- Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Srikar Chamala
- Keck School of Medicine, Department of Pathology, University of Southern California, Los Angeles, California, USA,Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, California, USA
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7
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Nguyen JQ, Crews KR, Moore BT, Kornegay NM, Baker DK, Hasan M, Campbell PK, Dean SM, Relling MV, Hoffman JM, Haidar CE. Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts. J Am Med Inform Assoc 2022; 30:132-138. [PMID: 36228116 PMCID: PMC9748527 DOI: 10.1093/jamia/ocac187] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 09/26/2022] [Accepted: 10/02/2022] [Indexed: 12/15/2022] Open
Abstract
Thoughtful integration of interruptive clinical decision support (CDS) alerts within the electronic health record is essential to guide clinicians on the application of pharmacogenomic results at point of care. St. Jude Children's Research Hospital implemented a preemptive pharmacogenomic testing program in 2011 in a multidisciplinary effort involving extensive education to clinicians about pharmacogenomic implications. We conducted a retrospective analysis of clinicians' adherence to 4783 pharmacogenomically guided CDS alerts that triggered for 12 genes and 60 drugs. Clinicians adhered to the therapeutic recommendations provided in 4392 alerts (92%). In our population of pediatric patients with catastrophic illnesses, the most frequently presented gene/drug CDS alerts were TPMT/NUDT15 and thiopurines (n = 3850), CYP2D6 and ondansetron (n = 667), CYP2D6 and oxycodone (n = 99), G6PD and G6PD high-risk medications (n = 51), and CYP2C19 and proton pump inhibitors (omeprazole and pantoprazole; n = 50). The high adherence rate was facilitated by our team approach to prescribing and our collaborative CDS design and delivery.
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Affiliation(s)
- Jenny Q Nguyen
- 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
| | - Ben T Moore
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Nancy M Kornegay
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Donald K Baker
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Murad Hasan
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Patrick K Campbell
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
| | - Shannon M Dean
- Department of Information Services, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
- Department of Pediatrics, St. Jude Children’s Research Hospital, Memphis, Tennesse, USA
| | - Mary V Relling
- 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
- Department of the Office of Quality and Patient Safety, St. Jude Children’s Research Hospital, Memphis, Tennesse, USA
| | - Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee, USA
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8
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Fragala MS, Shaman JA, Lorenz RA, Goldberg SE. Role of Pharmacogenomics in Comprehensive Medication Management: Considerations for Employers. Popul Health Manag 2022; 25:753-762. [PMID: 36301527 DOI: 10.1089/pop.2022.0075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.
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9
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Rodriguez-Antona C, Savieo JL, Lauschke VM, Sangkuhl K, Drögemöller BI, Wang D, van Schaik RHN, Gilep AA, Peter AP, Boone EC, Ramey BE, Klein TE, Whirl-Carrillo M, Pratt VM, Gaedigk A. PharmVar GeneFocus: CYP3A5. Clin Pharmacol Ther 2022; 112:1159-1171. [PMID: 35202484 PMCID: PMC9399309 DOI: 10.1002/cpt.2563] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/11/2022] [Indexed: 01/31/2023]
Abstract
The Pharmacogene Variation Consortium (PharmVar) catalogs star (*) allele nomenclature for the polymorphic human CYP3A5 gene. Genetic variation within the CYP3A5 gene locus impacts the metabolism of several clinically important drugs, including the immunosuppressants tacrolimus, sirolimus, cyclosporine, and the benzodiazepine midazolam. Variable CYP3A5 activity is of clinical importance regarding tacrolimus metabolism. This GeneFocus provides a CYP3A5 gene summary with a focus on aspects regarding standardized nomenclature. In addition, this review also summarizes recent changes and updates, including the retirement of several allelic variants and provides an overview of how PharmVar CYP3A5 star allele nomenclature is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).
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Affiliation(s)
- Cristina Rodriguez-Antona
- Hereditary Endocrine Cancer Group, Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | | | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Britt I Drögemöller
- Department of Biochemistry and Medical Genetics, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- CancerCare Manitoba Research Institute, Winnipeg, Manitoba, Canada
- Children's Hospital Research Institute of Manitoba, Winnipeg, Manitoba, Canada
| | - Danxin Wang
- Department of Pharmacotherapy and Translational Research, University of Florida, Gainesville, Florida, USA
| | - Ron H N van Schaik
- Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Andrei A Gilep
- Institute of Bioorganic Chemistry, National Academy of Sciences of Belarus, Minsk, Belarus
- Institute of Biomedical Chemistry, Moscow, Russia
| | - Arul P Peter
- Coriell Life Sciences, Philadelphia, Pennsylvania, USA
| | - Erin C Boone
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
| | | | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | | | - Victoria M Pratt
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
- School of Medicine, University of Missouri-Kansas City, Kansas City, Missouri, USA
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10
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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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11
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Mostafa S, Polasek TM, Bousman CA, Müeller DJ, Sheffield LJ, Rembach J, Kirkpatrick CM. Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing. Pharmacogenomics 2022; 23:857-867. [PMID: 36169629 DOI: 10.2217/pgs-2022-0104] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.
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Affiliation(s)
- Sam Mostafa
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia.,MyDNA Life, Australia Limited, South Yarra, Victoria, Australia
| | - Thomas M Polasek
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia.,Certara, Princeton, NJ 08540, USA.,Department of Clinical Pharmacology, Royal Adelaide Hospital, Adelaide, South Australia, 5000, Australia
| | - Chad A Bousman
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Melbourne, Victoria, 3010, Australia.,The Cooperative Research Centre (CRC) for Mental Health, Carlton, Victoria, 3053, Australia.,Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.,Departments of Medical Genetics, Psychiatry, & Physiology & Pharmacology, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
| | - Daniel J Müeller
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, M5T 1R8, Canada
| | | | - Joel Rembach
- MyDNA Life, Australia Limited, South Yarra, Victoria, Australia
| | - Carl Mj Kirkpatrick
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia
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12
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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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13
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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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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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15
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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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16
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Gong J, Sihag V, Kong Q, Zhao L. Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research: Bibliometric Analysis. JMIR Med Inform 2021; 9:e31142. [PMID: 34723823 PMCID: PMC8593818 DOI: 10.2196/31142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 08/17/2021] [Accepted: 09/17/2021] [Indexed: 11/13/2022] Open
Abstract
Background The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots. Objective The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis. Methods We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence. Results The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention. Conclusions Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including “allocative value,” “technology value,” and “personalized value.”
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Affiliation(s)
- Jianxia Gong
- School of Economics and Management, Southeast University, Nanjing, China
| | - Vikrant Sihag
- Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Qingxia Kong
- Department of Technology and Operations Management, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Lindu Zhao
- School of Economics and Management, Southeast University, Nanjing, China
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17
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Tuteja S, Salloum RG, Elchynski AL, Smith DM, Rowe E, Blake KV, Limdi NA, Aquilante CL, Bates J, Beitelshees AL, Cipriani A, Duong BQ, Empey PE, Formea CM, Hicks JK, Mroz P, Oslin D, Pasternak AL, Petry N, Ramsey LB, Schlichte A, Swain SM, Ward KM, Wiisanen K, Skaar TC, Van Driest SL, Cavallari LH, Bishop JR. Multisite evaluation of institutional processes and implementation determinants for pharmacogenetic testing to guide antidepressant therapy. Clin Transl Sci 2021; 15:371-383. [PMID: 34562070 PMCID: PMC8841452 DOI: 10.1111/cts.13154] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/11/2021] [Accepted: 08/16/2021] [Indexed: 12/11/2022] Open
Abstract
There is growing interest in utilizing pharmacogenetic (PGx) testing to guide antidepressant use, but there is lack of clarity on how to implement testing into clinical practice. We administered two surveys at 17 sites that had implemented or were in the process of implementing PGx testing for antidepressants. Survey 1 collected data on the process and logistics of testing. Survey 2 asked sites to rank the importance of Consolidated Framework for Implementation Research (CFIR) constructs using best‐worst scaling choice experiments. Of the 17 sites, 13 had implemented testing and four were in the planning stage. Thirteen offered testing in the outpatient setting, and nine in both outpatient/inpatient settings. PGx tests were mainly ordered by psychiatry (92%) and primary care (69%) providers. CYP2C19 and CYP2D6 were the most commonly tested genes. The justification for antidepressants selected for PGx guidance was based on Clinical Pharmacogenetics Implementation Consortium guidelines (94%) and US Food and Drug Administration (FDA; 75.6%) guidance. Both institutional (53%) and commercial laboratories (53%) were used for testing. Sites varied on the methods for returning results to providers and patients. Sites were consistent in ranking CFIR constructs and identified patient needs/resources, leadership engagement, intervention knowledge/beliefs, evidence strength and quality, and the identification of champions as most important for implementation. Sites deployed similar implementation strategies and measured similar outcomes. The process of implementing PGx testing to guide antidepressant therapy varied across sites, but key drivers for successful implementation were similar and may help guide other institutions interested in providing PGx‐guided pharmacotherapy for antidepressant management.
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Affiliation(s)
- Sony Tuteja
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramzi G Salloum
- University of Florida College of Medicine, Gainesville, Florida, USA
| | | | - D Max Smith
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Elizabeth Rowe
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Nita A Limdi
- University of Alabama School of Medicine, Birmingham, Alabama, USA
| | | | - Jill Bates
- Durham VA Healthcare System, Durham, North Carolina, USA
| | | | - Amber Cipriani
- University of North Carolina Medical Center, Chapel Hill, North Carolina, USA
| | | | - Philip E Empey
- University of Pittsburgh School of Pharmacy, Pittsburgh, Pennsylvania, USA
| | | | | | - Pawel Mroz
- University of Minnesota Medical School, Minneapolis, Minnesota, USA
| | - David Oslin
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA.,Corporal Michael J. Crescenz VA Medical Center, Philadelphia, Pennsylvania, USA
| | - Amy L Pasternak
- University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
| | - Natasha Petry
- North Dakota State University/Sanford Health, Fargo, North Dakota, USA
| | - Laura B Ramsey
- Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | | | - Sandra M Swain
- MedStar Health, Georgetown University Medical Center, Washington, DC, USA
| | - Kristen M Ward
- University of Michigan College of Pharmacy, Ann Arbor, Michigan, USA
| | - Kristin Wiisanen
- University of Florida College of Pharmacy, Gainesville, Florida, USA
| | - Todd C Skaar
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | - Jeffrey R Bishop
- University of Minnesota Medical School, Minneapolis, Minnesota, USA.,University of Minnesota College of Pharmacy, Minneapolis, Minnesota, USA
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18
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Sangkuhl K, Claudio-Campos K, Cavallari LH, Agundez JAG, Whirl-Carrillo M, Duconge J, Del Tredici AL, Wadelius M, Rodrigues Botton M, Woodahl EL, Scott SA, Klein TE, Pratt VM, Daly AK, Gaedigk A. PharmVar GeneFocus: CYP2C9. Clin Pharmacol Ther 2021; 110:662-676. [PMID: 34109627 PMCID: PMC8607432 DOI: 10.1002/cpt.2333] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 06/02/2021] [Indexed: 12/12/2022]
Abstract
The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C9 gene. Genetic variation within the CYP2C9 gene locus impacts the metabolism or bioactivation of many clinically important drugs, including nonsteroidal anti-inflammatory drugs, phenytoin, antidiabetic agents, and angiotensin receptor blockers. Variable CYP2C9 activity is of particular importance regarding efficacy and safety of warfarin and siponimod as indicated in their package inserts. This GeneFocus provides a comprehensive overview and summary of CYP2C9 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium.
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Affiliation(s)
- Katrin Sangkuhl
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA
| | - Karla Claudio-Campos
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, Florida, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Florida, USA
| | - Jose A G Agundez
- University Institute of Molecular Pathology Biomarkers, University of Extremadura, Asthma, Adverse Drug Reactions and Allergy (ARADyAL) Institute de Salud Carlos III, Cáceres, Spain
| | - Michelle Whirl-Carrillo
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA
| | - Jorge Duconge
- School of Pharmacy, University of Puerto Rico Medical Sciences Campus, San Juan, Puerto Rico, USA
| | | | - Mia Wadelius
- Department of Medical Sciences, Clinical Pharmacology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Erica L Woodahl
- Department of Biomedical and Pharmaceutical Sciences, University of Montana, Missoula, Montana, USA
| | - Stuart A Scott
- Department of Pathology, Stanford University, Stanford, California, USA
- Stanford Health Care Clinical Genomics Laboratory, Palo Alto, California, USA
| | - Teri E Klein
- Department of Biomedical Data Science, School of Medicine, Stanford University, Stanford, California, USA
| | - Victoria M Pratt
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ann K Daly
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy Kansas City, Kansas City, Missouri, USA
- School of Medicine, University of Missouri - Kansas City, Kansas City, Missouri, USA
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19
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Wake DT, Smith DM, Kazi S, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision. Clin Pharmacol Ther 2021; 112:44-57. [PMID: 34365648 PMCID: PMC9291515 DOI: 10.1002/cpt.2387] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.
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Affiliation(s)
- Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, DC, USA
| | - Sadaf Kazi
- Georgetown University Medical Center, Washington, DC, USA.,National Center for Human Factors in Healthcare, MedStar Health Research Institute Washington, Washington, DC, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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20
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Cook KJ, Duong BQ, Seligson ND, Arn P, Funanage VL, Gripp KW, Kirwin SM, Lawless ST, Lee MM, Robbins KM, West D, Blake KV. Key Considerations for Selecting a Genomic Decision Support Platform for Implementing Pharmacogenomics. Clin Pharmacol Ther 2021; 110:555-558. [PMID: 34254671 DOI: 10.1002/cpt.2328] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 05/19/2021] [Indexed: 11/06/2022]
Affiliation(s)
- Kelsey J Cook
- Department of Pharmacotherapy and Translational Research, The University of Florida College of Pharmacy, Jacksonville, Florida, USA.,Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Benjamin Q Duong
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Nathan D Seligson
- Department of Pharmacotherapy and Translational Research, The University of Florida College of Pharmacy, Jacksonville, Florida, USA.,Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Pamela Arn
- Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
| | - Vicky L Funanage
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Karen W Gripp
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Susan M Kirwin
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Stephen T Lawless
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Mary M Lee
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA.,Sidney Kimmel Medical College, Philadelphia, Pennsylvania, USA
| | - Katherine M Robbins
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - David West
- Precision Medicine Program, Nemours Children's Health, Wilmington, Delaware, USA
| | - Kathryn V Blake
- Precision Medicine Program, Nemours Children's Health, Jacksonville, Florida, USA
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21
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Russell LE, Zhou Y, Almousa AA, Sodhi JK, Nwabufo CK, Lauschke VM. Pharmacogenomics in the era of next generation sequencing - from byte to bedside. Drug Metab Rev 2021; 53:253-278. [PMID: 33820459 DOI: 10.1080/03602532.2021.1909613] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.
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Affiliation(s)
| | - Yitian Zhou
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ahmed A Almousa
- Department of Pharmacy, London Health Sciences Center, Victoria Hospital, London, ON, Canada
| | - Jasleen K Sodhi
- Department of Bioengineering and Therapeutic Sciences, Schools of Pharmacy and Medicine, University of California San Francisco, San Francisco, CA, USA.,Department of Drug Metabolism and Pharmacokinetics, Plexxikon, Inc., Berkeley, CA, USA
| | | | - Volker M Lauschke
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
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22
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Takahashi PY, Ryu E, Cerhan JR, Bielinski SJ, Olson JE. Pathway to Ascertain the Role of Pharmacogenomics in Healthcare Utilization Outcomes [Response to Letter]. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2021; 14:545-546. [PMID: 33986611 PMCID: PMC8111333 DOI: 10.2147/pgpm.s316851] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 04/21/2021] [Indexed: 11/23/2022]
Affiliation(s)
- Paul Y Takahashi
- Division of Community Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
| | - Euijung Ryu
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - James R Cerhan
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Janet E Olson
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
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23
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Loudon E, Scott SA, Rigobello R, Scott ER, Zinberg R, Naik H. Pharmacogenomic education among genetic counseling training programs in North America. J Genet Couns 2021; 30:1500-1508. [PMID: 33882174 DOI: 10.1002/jgc4.1417] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 02/22/2021] [Accepted: 02/25/2021] [Indexed: 11/06/2022]
Abstract
The increasing number of genetic counselors participating directly in clinical pharmacogenomic post-test counseling prompted our evaluation of pharmacogenomic education across genetic counseling training programs in North America. Thirty-one program leadership participants from both the United States (U.S.) and Canada responded to a survey assessing pharmacogenomics education and the role of genetic counselors. Eighty-five percent of respondents agreed pharmacogenomics is currently within the scope of genetic counseling practice, and 96.3% indicated their training programs currently provide education on pharmacogenomics, with the majority reporting < 7 hr of education. Lectures on pharmacogenomics were the most common method for didactics; however, some programs also included practical modalities (e.g., case studies, clinical rotations) and online resources. Barriers to expanding pharmacogenomic education included the constrained timeline of training, and lack of resources and local expertise. Moreover, participants suggested that genetic counselors ideally should be able to order pharmacogenomic tests and counsel patients on pharmacogenomics, including result interpretation, as they believe pharmacogenomics does fall within the scope of practice of genetic counseling. Our novel results also confirm that training program leadership support a pharmacogenomic service delivery model that includes a combined effort between genetic counselors and pharmacists to utilize their synergistic expertise. However, this model likely still necessitates expanding pharmacogenomic didactics in genetic counseling training programs through more practical training and/or by leveraging online pharmacogenomic courses dedicated to supporting clinical implementation.
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Affiliation(s)
- Elizabeth Loudon
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Stuart A Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Sema4, Stamford, CT, USA.,Clinical Genomics Laboratory, Stanford Health Care, Palo Alto, CA, USA
| | | | - Erick R Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Randi Zinberg
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Hetanshi Naik
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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24
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Patel JN, Boselli D, Jandrisevits EJ, Hamadeh IS, Salem A, Meadors P, Walsh D. Potentially actionable pharmacogenetic variants and symptom control medications in oncology. Support Care Cancer 2021; 29:5927-5934. [PMID: 33758969 DOI: 10.1007/s00520-021-06170-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/18/2021] [Indexed: 01/26/2023]
Abstract
PURPOSE We estimated the prevalence of potentially actionable pharmacogenetic (PGx) variants related to symptom control medications (SCMs) based on institutional prescribing patterns and correlated presenting symptoms with SCM prescribing. METHODS This was a retrospective study of adult ambulatory cancer patients undergoing electronic distress screening (EDS) within 90 days of intake to the cancer hospital. We estimated the proportion prescribed SCM(s) with PGx evidence within 90 days of intake. Those with potentially actionable variants were estimated using population frequency data from 1000 genomes. The expected number at risk of altered drug response was estimated. The associations between symptom scores and SCM(s) were estimated with logistic regression and threshold analyses performed with receiver operating characteristic (ROC) curves. RESULTS Of 6985 patients, 3222 (46%) received ≥ one SCM. Of these, 2760 (86%) received SCM(s) with PGx evidence for CYP2B6, CYP2C19, CYP2D6, or SLC6A4; 2719 (84%) received a drug metabolized by CYP2D6, most commonly hydrocodone (40.4%), ondansetron (35.6%), oxycodone (24.2%), and/or tramadol (7.1%). Based on this, about one quarter were expected to have altered metabolism and/or drug response. One third were prescribed two or more SCMs with PGx evidence. About half reported at least one severe symptom, which significantly correlated with SCM prescribing (p < 0.001). Threshold scores were identified that highly correlated with SCM prescribing for anxiety, depression, nausea, neuropathy, pain, and sleep. CONCLUSION About half presented with significant symptom burden, which highly correlated with SCM prescribing. Most received SCMs with PGx evidence. Preemptive PGx testing for these variants should be evaluated in prospective trials to evaluate the impact on symptom control.
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Affiliation(s)
- Jai N Patel
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA.
| | - Danielle Boselli
- Department of Biostatistics, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
| | - Elizabeth J Jandrisevits
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Issam S Hamadeh
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Ahmed Salem
- Department of Cancer Pharmacology & Pharmacogenomics, Atrium Health Levine Cancer Institute, 1021 Morehead Medical Drive, Charlotte, NC, 28204, USA
| | - Patrick Meadors
- Section of Psycho-oncology, Center for Supportive Care and Survivorship, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
| | - Declan Walsh
- Department of Supportive Oncology, Atrium Health Levine Cancer Institute, Charlotte, NC, USA
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25
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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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26
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Botton MR, Whirl-Carrillo M, Del Tredici AL, Sangkuhl K, Cavallari LH, Agúndez JAG, Duconge J, Lee MTM, Woodahl EL, Claudio-Campos K, Daly AK, Klein TE, Pratt VM, Scott SA, Gaedigk A. PharmVar GeneFocus: CYP2C19. Clin Pharmacol Ther 2021; 109:352-366. [PMID: 32602114 PMCID: PMC7769975 DOI: 10.1002/cpt.1973] [Citation(s) in RCA: 63] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 06/15/2020] [Indexed: 12/17/2022]
Abstract
The Pharmacogene Variation Consortium (PharmVar) catalogues star (*) allele nomenclature for the polymorphic human CYP2C19 gene. CYP2C19 genetic variation impacts the metabolism of many drugs and has been associated with both efficacy and safety issues for several commonly prescribed medications. This GeneFocus provides a comprehensive overview and summary of CYP2C19 and describes how haplotype information catalogued by PharmVar is utilized by the Pharmacogenomics Knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC).
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Affiliation(s)
| | | | | | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | | | - José A G Agúndez
- UNEx, ARADyAL, Instituto de Salud Carlos III, University Institute of Molecular Pathology Biomarkers, Cáceres, Spain
| | - Jorge Duconge
- School of Pharmacy, University of Puerto Rico, San Juan, Puerto Rico
| | | | - Erica L Woodahl
- Department of Biomedical and Pharmaceutical Sciences, University of Montana, Missoula, Montana, USA
| | | | - Ann K Daly
- Newcastle University, Newcastle upon Tyne, UK
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Victoria M Pratt
- Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Stuart A Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Sema4, Stamford, Connecticut, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children's Mercy, Kansas City, Missouri, USA
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27
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Kannan V, Basit MA, Bajaj P, Carrington AR, Donahue IB, Flahaven EL, Medford R, Melaku T, Moran BA, Saldana LE, Willett DL, Youngblood JE, Toomay SM. User stories as lightweight requirements for agile clinical decision support development. J Am Med Inform Assoc 2021; 26:1344-1354. [PMID: 31512730 PMCID: PMC6798563 DOI: 10.1093/jamia/ocz123] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 05/17/2019] [Accepted: 07/01/2019] [Indexed: 02/02/2023] Open
Abstract
Objective We sought to demonstrate applicability of user stories, progressively elaborated by testable acceptance criteria, as lightweight requirements for agile development of clinical decision support (CDS). Materials and Methods User stories employed the template: As a [type of user], I want [some goal] so that [some reason]. From the “so that” section, CDS benefit measures were derived. Detailed acceptance criteria were elaborated through ensuing conversations. We estimated user story size with “story points,” and depicted multiple user stories with a use case diagram or feature breakdown structure. Large user stories were split to fit into 2-week iterations. Results One example user story was: As a rheumatologist, I want to be advised if my patient with rheumatoid arthritis is not on a disease-modifying anti-rheumatic drug (DMARD), so that they receive optimal therapy and can experience symptom improvement. This yielded a process measure (DMARD use), and an outcome measure (Clinical Disease Activity Index). Following implementation, the DMARD nonuse rate decreased from 3.7% to 1.4%. Patients with a high Clinical Disease Activity Index improved from 13.7% to 7%. For a thromboembolism prevention CDS project, diagrams organized multiple user stories. Discussion User stories written in the clinician’s voice aid CDS governance and lead naturally to measures of CDS effectiveness. Estimation of relative story size helps plan CDS delivery dates. User stories prove to be practical even on larger projects. Conclusions User stories concisely communicate the who, what, and why of a CDS request, and serve as lightweight requirements for agile development to meet the demand for increasingly diverse CDS.
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Affiliation(s)
- Vaishnavi Kannan
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.,Health System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Mujeeb A Basit
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Puneet Bajaj
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Angela R Carrington
- Health System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Irma B Donahue
- Health System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Emily L Flahaven
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA
| | - Richard Medford
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Tsedey Melaku
- Clinical Informatics, Parkland Health and Hospital System, Dallas, Texas, USA
| | - Brett A Moran
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Clinical Informatics, Parkland Health and Hospital System, Dallas, Texas, USA
| | - Luis E Saldana
- Clinical Informatics, Texas Health Resources, Arlington, Texas, USA
| | - Duwayne L Willett
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Josh E Youngblood
- Health System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA
| | - Seth M Toomay
- Clinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA
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28
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Qin W, Du Z, Xiao J, Duan H, Shu Q, Li H. Evaluation of clinical impact of pharmacogenomics knowledge involved in CPIC guidelines on Chinese pediatric patients. Pharmacogenomics 2021; 21:209-219. [PMID: 31967514 DOI: 10.2217/pgs-2019-0153] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Aim: To evaluate the clinical benefits of implementing pharmacogenomics testing for Chinese pediatric patients. Materials & methods : Based on the drug-gene interactions involved in the Clinical Pharmacogenetics Implementation Consortium guidelines, whole-genome sequencing data from the Chinese Academy of Sciences Precision Medicine Initiative project and the medication data of pediatric patients from a children's hospital, the prevalence of the Chinese population with actionable pharmacogenomic variants was calculated, the prescribing pattern for pediatric patients was analyzed. Results: 37.0% of the drugs involved in the Clinical Pharmacogenetics Implementation Consortium guidelines were used by Chinese pediatric patients, 8.91% inpatients and 0.89% outpatients received at least one pharmacogenomics medication, 1.24% (4803) inpatients and 0.16% (2940) outpatients were estimated to be at high risk of pharmacogenomic-related adverse therapeutic outcomes. Conclusion: Implementing pharmacogenomics testing can improve therapeutic outcomes for many Chinese pediatric patients.
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Affiliation(s)
- Weifeng Qin
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China.,College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Zhenglin Du
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Jingfa Xiao
- Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, PR China
| | - Huilong Duan
- College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, PR China
| | - Qiang Shu
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China
| | - Haomin Li
- The Children's Hospital, Zhejiang University School of Medicine and National Clinical Research Center for Child Health, Hangzhou 310052, PR China
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29
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Johengen EK, Ward KM, Coe AB, Pasternak AL. Assessing the knowledge, perceptions, and practices of primary care clinicians toward pharmacogenetics. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2021. [DOI: 10.1002/jac5.1341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
| | - Kristen M. Ward
- Michigan Medicine Ann Arbor Michigan USA
- Department of Clinical Pharmacy University of Michigan College of Pharmacy Ann Arbor Michigan USA
| | - Antoinette B. Coe
- Department of Clinical Pharmacy University of Michigan College of Pharmacy Ann Arbor Michigan USA
| | - Amy L. Pasternak
- Michigan Medicine Ann Arbor Michigan USA
- Department of Clinical Pharmacy University of Michigan College of Pharmacy Ann Arbor Michigan USA
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30
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Nicholson WT, Formea CM, Matey ET, Wright JA, Giri J, Moyer AM. Considerations When Applying Pharmacogenomics to Your Practice. Mayo Clin Proc 2021; 96:218-230. [PMID: 33308868 DOI: 10.1016/j.mayocp.2020.03.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 02/24/2020] [Accepted: 03/17/2020] [Indexed: 10/22/2022]
Abstract
Many practitioners who have not had pharmacogenomic education are required to apply pharmacogenomics to their practices. Although many aspects of pharmacogenomics are similar to traditional concepts of drug-drug interactions, there are some differences. We searched PubMed with the search terms pharmacogenomics and pharmacogenetics (January 1, 2005, through December 31, 2019) and selected articles that supported the application of pharmacogenomics to practice. For inclusion, we gave preference to national and international consortium guidelines for implementation of pharmacogenomics. We discuss special considerations important in the application of pharmacogenomics to assist clinicians with ordering, interpreting, and applying pharmacogenomics in their practices.
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Affiliation(s)
- Wayne T Nicholson
- Department of Anesthesiology and Perioperative Medicine, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN.
| | - Christine M Formea
- Intermountain Healthcare Department of Pharmacy Services Pharmacy Services, Salt Lake City, UT; Intermountain Precision Genomics, Intermountain Healthcare, St George, UT
| | - Eric T Matey
- Department of Pharmacy, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN
| | - Jessica A Wright
- Department of Pharmacy, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN
| | - Jyothsna Giri
- Mayo Clinic Center for Individualized Medicine, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN
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31
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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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Optimising Seniors' Metabolism of Medications and Avoiding Adverse Drug Events Using Data on How Metabolism by Their P450 Enzymes Varies with Ancestry and Drug-Drug and Drug-Drug-Gene Interactions. J Pers Med 2020; 10:jpm10030084. [PMID: 32796505 PMCID: PMC7563167 DOI: 10.3390/jpm10030084] [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: 06/28/2020] [Revised: 08/01/2020] [Accepted: 08/06/2020] [Indexed: 12/16/2022] Open
Abstract
Many individuals ≥65 have multiple illnesses and polypharmacy. Primary care physicians prescribe >70% of their medications and renew specialists’ prescriptions. Seventy-five percent of all medications are metabolised by P450 cytochrome enzymes. This article provides unique detailed tables how to avoid adverse drug events and optimise prescribing based on two key databases. DrugBank is a detailed database of 13,000 medications and both the P450 and other complex pathways that metabolise them. The Flockhart Tables are detailed lists of the P450 enzymes and also include all the medications which inhibit or induce metabolism by P450 cytochrome enzymes, which can result in undertreatment, overtreatment, or potentially toxic levels. Humans have used medications for a few decades and these enzymes have not been subject to evolutionary pressure. Thus, there is enormous variation in enzymatic functioning and by ancestry. Differences for ancestry groups in genetic metabolism based on a worldwide meta-analysis are discussed and this article provides advice how to prescribe for individuals of different ancestry. Prescribing advice from two key organisations, the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium is summarised. Currently, detailed pharmacogenomic advice is only available in some specialist clinics in major hospitals. However, this article provides detailed pharmacogenomic advice for primary care and other physicians and also physicians working in rural and remote areas worldwide. Physicians could quickly search the tables for the medications they intend to prescribe.
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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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Rasmussen LV, Smith ME, Almaraz F, Persell SD, Rasmussen-Torvik LJ, Pacheco JA, Chisholm RL, Christensen C, Herr TM, Wehbe FH, Starren JB. An ancillary genomics system to support the return of pharmacogenomic results. J Am Med Inform Assoc 2020; 26:306-310. [PMID: 30778576 DOI: 10.1093/jamia/ocy187] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 10/15/2018] [Accepted: 12/20/2018] [Indexed: 01/26/2023] Open
Abstract
Existing approaches to managing genetic and genomic test results from external laboratories typically include filing of text reports within the electronic health record, making them unavailable in many cases for clinical decision support. Even when structured computable results are available, the lack of adopted standards requires considerations for processing the results into actionable knowledge, in addition to storage and management of the data. Here, we describe the design and implementation of an ancillary genomics system used to receive and process heterogeneous results from external laboratories, which returns a descriptive phenotype to the electronic health record in support of pharmacogenetic clinical decision support.
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Affiliation(s)
- Luke V Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Maureen E Smith
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL.,Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Federico Almaraz
- Department of Information Technology, Northwestern Memorial HealthCare, Chicago, IL
| | - Stephen D Persell
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Laura J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Jennifer A Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Rex L Chisholm
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Carl Christensen
- Department of Information Technology, Northwestern Memorial HealthCare, Chicago, IL.,Department of Information Technology, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Timothy M Herr
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Firas H Wehbe
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
| | - Justin B Starren
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
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Cornett EM, Carroll Turpin MA, Pinner A, Thakur P, Sekaran TSG, Siddaiah H, Rivas J, Yates A, Huang GJ, Senthil A, Khurmi N, Miller JL, Stark CW, Urman RD, Kaye AD. Pharmacogenomics of Pain Management: The Impact of Specific Biological Polymorphisms on Drugs and Metabolism. Curr Oncol Rep 2020; 22:18. [PMID: 32030524 DOI: 10.1007/s11912-020-0865-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
PURPOSE OF REVIEW Pain is multifactorial and complex, often with a genetic component. Pharmacogenomics is a relative new field, which allows for the development of a truly unique and personalized therapeutic approach in the treatment of pain. RECENT FINDINGS Until recently, drug mechanisms in humans were determined by testing that drug in a population and calculating response averages. However, some patients will inevitably fall outside of those averages, and it is nearly impossible to predict who those outliers might be. Pharmacogenetics considers a patient's unique genetic information and allows for anticipation of that individual's response to medication. Pharmacogenomic testing is steadily making progress in the management of pain by being able to identify individual differences in the perception of pain and susceptibility and sensitivity to drugs based on genetic markers. This has a huge potential to increase efficacy and reduce the incidence of iatrogenic drug dependence and addiction. The streamlining of relevant polymorphisms of genes encoding receptors, transporters, and drug-metabolizing enzymes influencing the pain phenotype can be an important guide to develop safe new strategies and approaches to personalized pain management. Additionally, some challenges still prevail and preclude adoption of pharmacogenomic testing universally. These include lack of knowledge about pharmacogenomic testing, inadequate standardization of the process of data handling, questionable benefits about the clinical and financial aspects of pharmacogenomic testing-guided therapy, discrepancies in clinical evidence supporting these tests, and doubtful reimbursement of the tests by health insurance agencies.
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Affiliation(s)
- Elyse M Cornett
- Department of Anesthesiology, LSU Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA.
| | - Michelle A Carroll Turpin
- Department of Biomedical Sciences, College of Medicine, University of Houston, Health 2 Building, Room 8037, Houston, TX, USA
| | - Allison Pinner
- Ochsner LSU Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA
| | - Pankaj Thakur
- Department of Anesthesiology, Ochsner LSU Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA
| | | | - Harish Siddaiah
- Department of Anesthesiology, Ochsner LSU Health Shreveport, 1501 Kings Highway, Shreveport, LA, 71103, USA
| | - Jasmine Rivas
- Department of Family Medicine, ECU Vidant Medical Center, 101 Heart Drive, Greenville, NC, 27834, USA
| | - Anna Yates
- LSU Health Shreveport School of Medicine, 1501 Kings Highway, Shreveport, LA, 71103, USA
| | - G Jason Huang
- Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Anitha Senthil
- Department of Anesthesiology, Lahey Hospital & Medical Center, 41Mall Road, Burlington, MA, 01805, USA
| | - Narjeet Khurmi
- Department of Anesthesiology & Perioperative Medicine, Mayo Clinic Arizona, 5777 East Mayo Boulevard, Phoenix, AZ, 85054, USA
| | - Jenna L Miller
- LSU Health Sciences Center New Orleans, 1901 Perdido Street, New Orleans, LA, 70112, USA
| | - Cain W Stark
- Medical College of Wisconsin, 8701 West Watertown Plank Road, Wauwatosa, WI, 53226, USA
| | - Richard D Urman
- Department of Anesthesiology, Perioperative and Pain Medicine, Harvard Medical School, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA
| | - Alan David Kaye
- Department of Anesthesiology and Pharmacology, Toxicology, and Neurosciences, Louisiana State University School of Medicine, 1501 Kings Hwy, Shreveport, LA, 71103, USA
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Applying Pharmacogenomics to Antifungal Selection and Dosing: Are We There Yet? CURRENT FUNGAL INFECTION REPORTS 2020; 14:63-75. [PMID: 32256938 DOI: 10.1007/s12281-020-00371-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
Purpose of Review This review summarizes recent literature for applying pharmacogenomics to antifungal selection and dosing, providing an approach to implementing antifungal pharmacogenomics in clinical practice. Recent Findings The Clinical Pharmacogenetics Implementation Consortium published guidelines on CYP2C19 and voriconazole, with recommendations to use alternative antifungals or adjust voriconazole dose with close therapeutic drug monitoring (TDM). Recent studies demonstrate an association between CYP2C19 phenotype and voriconazole levels, clinical outcomes, and adverse events. Additionally, CYP2C19-guided preemptive dose adjustment demonstrated benefit in two prospective studies for prophylaxis. Pharmacokinetic-pharmacodynamic modeling studies have generated proposed voriconazole treatment doses based on CYP2C19 phenotypes, with further validation studies needed. Summary Sufficient evidence is available for implementing CYP2C19-guided voriconazole selection and dosing among select patients at risk for invasive fungal infections. The institution needs appropriate infrastructure for pharmacogenomic testing, integration of results in the clinical decision process, with TDM confirmation of goal trough achievement, to integrate antifungal pharmacogenomics into routine clinical care.
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Herr TM, Peterson JF, Rasmussen LV, Caraballo PJ, Peissig PL, Starren JB. Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE Network. J Am Med Inform Assoc 2020; 26:143-148. [PMID: 30590574 DOI: 10.1093/jamia/ocy156] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2018] [Accepted: 11/05/2018] [Indexed: 11/12/2022] Open
Abstract
To better understand the real-world effects of pharmacogenomic (PGx) alerts, this study aimed to characterize alert design within the eMERGE Network, and to establish a method for sharing PGx alert response data for aggregate analysis. Seven eMERGE sites submitted design details and established an alert logging data dictionary. Six sites participated in a pilot study, sharing alert response data from their electronic health record systems. PGx alert design varied, with some consensus around the use of active, post-test alerts to convey Clinical Pharmacogenetics Implementation Consortium recommendations. Sites successfully shared response data, with wide variation in acceptance and follow rates. Results reflect the lack of standardization in PGx alert design. Standards and/or larger studies will be necessary to fully understand PGx impact. This study demonstrated a method for sharing PGx alert response data and established that variation in system design is a significant barrier for multi-site analyses.
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Affiliation(s)
- Timothy M Herr
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Luke V Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Pedro J Caraballo
- Department of Medicine and Center for Translational Informatics and Knowledge Management, Mayo Clinic, Rochester, Minnesota, USA
| | - Peggy L Peissig
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - Justin B Starren
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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40
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Nofziger C, Turner AJ, Sangkuhl K, Whirl-Carrillo M, Agúndez JAG, Black JL, Dunnenberger HM, Ruano G, Kennedy MA, Phillips MS, Hachad H, Klein TE, Gaedigk A. PharmVar GeneFocus: CYP2D6. Clin Pharmacol Ther 2020; 107:154-170. [PMID: 31544239 PMCID: PMC6925641 DOI: 10.1002/cpt.1643] [Citation(s) in RCA: 141] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Accepted: 08/29/2019] [Indexed: 01/13/2023]
Abstract
The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).
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Affiliation(s)
| | - Amy J. Turner
- Department of Pediatrics, Section of Genomic Pediatrics and Children’s Research Institute, The Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- RPRD Diagnostics LLC, Wauwatosa, Wisconsin, USA
| | - Katrin Sangkuhl
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | | | - José A. G. Agúndez
- University Institute of Molecular Pathology Biomarkers, UEx, Cáceres; ARADyAL Instituto de Salud Carlos III. Spain
| | - John L. Black
- Personalized Genomics Laboratory, Division of Laboratory Genetics and Genomics, Mayo Clinic laboratories, Mayo Clinic, Rochester MN (200 1st Street SW, Rochester MN 55902)
| | - Henry M. Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanton, IL, USA
| | - Gualberto Ruano
- Institute of Living at Hartford Hospital, Genomas Laboratory of Personalized Health, Hartford, Connecticut (67 Jefferson Street, Hartford, Connecticut 06106)
| | - Martin A. Kennedy
- Department of Pathology and Biomedical Science, University Otago, Christchurch, New Zealand
| | - Michael S. Phillips
- Sequence Bioinformatics Inc., 139 Water Street, 2 Floor, St. John’s NL, A1C 1B2, Canada
| | | | - Teri E. Klein
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - Andrea Gaedigk
- Division of Clinical Pharmacology, Toxicology & Therapeutic Innovation, Children’s Mercy Kansas City, Kansas City and School of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA
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Aronson S, Babb L, Ames D, Gibbs RA, Venner E, Connelly JJ, Marsolo K, Weng C, Williams MS, Hartzler AL, Liang WH, Ralston JD, Devine EB, Murphy S, Chute CG, Caraballo PJ, Kullo IJ, Freimuth RR, Rasmussen LV, Wehbe FH, Peterson JF, Robinson JR, Wiley K, Overby Taylor C. Empowering genomic medicine by establishing critical sequencing result data flows: the eMERGE example. J Am Med Inform Assoc 2019; 25:1375-1381. [PMID: 29860405 DOI: 10.1093/jamia/ocy051] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Accepted: 04/18/2018] [Indexed: 11/14/2022] Open
Abstract
The eMERGE Network is establishing methods for electronic transmittal of patient genetic test results from laboratories to healthcare providers across organizational boundaries. We surveyed the capabilities and needs of different network participants, established a common transfer format, and implemented transfer mechanisms based on this format. The interfaces we created are examples of the connectivity that must be instantiated before electronic genetic and genomic clinical decision support can be effectively built at the point of care. This work serves as a case example for both standards bodies and other organizations working to build the infrastructure required to provide better electronic clinical decision support for clinicians.
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Affiliation(s)
- Samuel Aronson
- Research Information Science and Computing, Partners HealthCare, Boston, Massachusetts, USA.,Partners Personalized Medicine, Partners HealthCare, Boston Massachusetts, USA
| | - Lawrence Babb
- Mitogen-GeneInsight, Sunquest Information Systems, Boston, Massachusetts, USA
| | - Darren Ames
- DNAnexus, Inc., Mountain View, California, USA
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Eric Venner
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - John J Connelly
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Keith Marsolo
- Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA.,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University, New York, New York, USA
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA
| | - Andrea L Hartzler
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.,Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA
| | - Wayne H Liang
- Informatics Institute, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Department of Pediatrics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - James D Ralston
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington, USA.,Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA
| | - Emily Beth Devine
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA
| | - Shawn Murphy
- Research Information Science and Computing, Partners HealthCare, Boston, Massachusetts, USA
| | | | | | - Iftikhar J Kullo
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - Robert R Freimuth
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Luke V Rasmussen
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, Illinois, USA
| | - Firas H Wehbe
- Department of Preventive Medicine, Division of Health and Biomedical Informatics, Northwestern University, Chicago, Illinois, USA
| | - Josh F Peterson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jamie R Robinson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Ken Wiley
- National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Casey Overby Taylor
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania, USA.,Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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Barin-Le Guellec C, Picard N, Alarcan H, Barreau M, Becquemont L, Quaranta S, Boyer JC, Loriot MA. [Pharmacogenetics for patient care in France: A discipline that evolves!]. Therapie 2019; 75:459-470. [PMID: 31767126 DOI: 10.1016/j.therap.2019.09.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Revised: 08/12/2019] [Accepted: 09/24/2019] [Indexed: 12/19/2022]
Abstract
Pharmacogenetics, which concepts are known for a long time, is entering a new period at least as far as its practical applications for patients are concerned. In recent years there have been more and more initiatives to promote widespread dissemination, and health authorities are increasingly incorporating these concepts into drug labels. In France, the national network of pharmacogenetics (RNPGx) works to promote these activities, both with health actors (biologists, clinicians) and health authorities. This article reviews the current situation in France and the milestones of the year 2018. It highlights recent advances in this field, in terms of currently recommended analyses, sharing of information or technological developments, and the prospects for future developments in the near future from targeted pharmacogenetics to eventually preemptive approaches.
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Affiliation(s)
- Chantal Barin-Le Guellec
- Inserm U1248, laboratoire de biochimie et biologie moléculaire, université de Tours, CHU de tours, 2, boulevard Tonnellé, 37044 Tours cedex, France.
| | - Nicolas Picard
- Inserm U1248, service de pharmacologie et toxicologie, université de Limoges, CHU de Limoges, 87042 Limoges, France
| | - Hugo Alarcan
- Inserm U1248, laboratoire de biochimie et biologie moléculaire, université de Tours, CHU de tours, 2, boulevard Tonnellé, 37044 Tours cedex, France
| | - Melody Barreau
- Inserm U1107, Service de pharmacologie, université d'Auvergne, CHU de Clermont-Ferrand, 63001 Clermont-Ferrand, France
| | - Laurent Becquemont
- CESP/Inserm U1018, Centre de recherche clinique, hôpital Bicêtre, université Paris Sud, 94275 Le Kremlin-Bicêtre, France
| | - Sylvie Quaranta
- Laboratoire de pharmacocinétique et toxicologie, CHU Timone, 13005 Marseille, France
| | | | - Marie-Anne Loriot
- Inserm U1144, service de biochimie, hôpital européen Georges-Pompidou, université Paris Descartes, 75015 Paris, France
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Giri J, Moyer AM, Bielinski SJ, Caraballo PJ. Concepts Driving Pharmacogenomics Implementation Into Everyday Healthcare. Pharmgenomics Pers Med 2019; 12:305-318. [PMID: 31802928 PMCID: PMC6826176 DOI: 10.2147/pgpm.s193185] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 10/07/2019] [Indexed: 12/13/2022] Open
Abstract
Pharmacogenomics (PGx) is often promoted as the domain of precision medicine with the greatest potential to readily impact everyday healthcare. Rapid advances in PGx knowledge derived from extensive basic and clinical research along with decreasing costs of laboratory testing have led to an increased interest in PGx and expectations of imminent clinical translation with substantial clinical impact. However, the implementation of PGx into clinical workflows is neither simple nor straightforward, and comprehensive processes and multidisciplinary collaboration are required. Several national and international institutions have pioneered models for implementing clinical PGx, and these initial models have led to a better understanding of unresolved challenges. In this review, we have categorized and explored the most relevant of these challenges to highlight potential gaps and present possible solutions. We describe the ongoing need for basic and clinical research to drive further developments in evidence-based medicine. Integration into daily clinical workflows introduces new challenges requiring innovative solutions; specifically those related to the electronic health record and embedded clinical decision support. We describe advances in PGx testing and result reporting and describe the critical need for increased standardization in these areas across laboratories. We also explore the complexity of the PGx knowledge required for clinical practice and the need for educational strategies to ensure adequate understanding among members of current and future healthcare teams. Finally, we evaluate knowledge obtained from previous implementation efforts and discuss how to best apply these learnings to future projects. Despite these challenges, the future of precision medicine appears promising due to the rapidity of recent advances in the field and current multidisciplinary efforts to effectively translate PGx to everyday clinical practice.
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Affiliation(s)
- Jyothsna Giri
- Center for Individualized Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ann M Moyer
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Pedro J Caraballo
- Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA
- Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
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Chanfreau-Coffinier C, Hull LE, Lynch JA, DuVall SL, Damrauer SM, Cunningham FE, Voight BF, Matheny ME, Oslin DW, Icardi MS, Tuteja S. Projected Prevalence of Actionable Pharmacogenetic Variants and Level A Drugs Prescribed Among US Veterans Health Administration Pharmacy Users. JAMA Netw Open 2019; 2:e195345. [PMID: 31173123 PMCID: PMC6563578 DOI: 10.1001/jamanetworkopen.2019.5345] [Citation(s) in RCA: 88] [Impact Index Per Article: 17.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
IMPORTANCE Implementation of pharmacogenetic testing to guide drug prescribing has potential to improve drug response and prevent adverse events. Robust data exist for more than 30 gene-drug pairs linking genotype to drug response phenotypes; however, it is unclear which pharmacogenetic tests, if implemented, would provide the greatest utility for a given patient population. OBJECTIVES To project the proportion of veterans in the US Veterans Health Administration (VHA) with actionable pharmacogenetic variants and evaluate how testing might be associated with prescribing decisions. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional study included veterans who used national VHA pharmacy services from October 1, 2011, to September 30, 2017. Data analyses began April 26, 2018, and were completed February 6, 2019. EXPOSURES Receipt of level A drugs based on VHA pharmacy dispensing records. MAIN OUTCOMES AND MEASURES Projected prevalence of actionable pharmacogenetic variants among VHA pharmacy users based on variant frequencies from the 1000 Genomes Project and veteran demographic characteristics; incident number of level A prescriptions, and proportion of new level A drug recipients projected to carry an actionable pharmacogenetic variant. RESULTS During the study, 7 769 359 veterans (mean [SD] age, 58.1 [17.8] years; 7 021 504 [90.4%] men) used VHA pharmacy services. It was projected that 99% of VHA pharmacy users would carry at least 1 actionable pharmacogenetic variant. Among VHA pharmacy users, 4 259 153 (54.8%) received at least 1 level A drug with 1 188 124 (15.3%) receiving 2 drugs, and 912 189 (11.7%) receiving 3 or more drugs. The most common incident prescriptions during the study were tramadol (923 671 new recipients), simvastatin (533 928 new recipients), citalopram (266 952 new recipients), and warfarin (205 177 new recipients). Gene-drug interactions projected to have substantial clinical impacts in the VHA population include the interaction of SLCO1B1 with simvastatin (1 988 956 veterans [25.6%]), CYP2D6 with tramadol (318 544 veterans [4.1%]), and CYP2C9 or VKORC1 with warfarin (7 163 349 veterans [92.2%]). CONCLUSIONS AND RELEVANCE Clinically important pharmacogenetic variants are highly prevalent in the VHA population. Almost all veterans would carry an actionable variant, and more than half of the population had been exposed to a drug affected by these variants. These results suggest that pharmacogenetic testing has the potential to affect pharmacotherapy decisions for commonly prescribed outpatient medications for many veterans.
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Affiliation(s)
- Catherine Chanfreau-Coffinier
- US Department of Veterans Affairs, VA Informatics and Computing Infrastructure, Salt Lake City Health Care System, Salt Lake City, Utah
| | - Leland E. Hull
- Center for Healthcare Organization and Implementation Research, US Department of Veterans Affairs, Boston Healthcare System, Boston, Massachusetts
- US Department of Veterans Affairs, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts
| | - Julie A. Lynch
- US Department of Veterans Affairs, VA Informatics and Computing Infrastructure, Salt Lake City Health Care System, Salt Lake City, Utah
- US Department of Veterans Affairs, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, Massachusetts
- College of Nursing and Health Sciences, University of Massachusetts, Boston
| | - Scott L. DuVall
- US Department of Veterans Affairs, VA Informatics and Computing Infrastructure, Salt Lake City Health Care System, Salt Lake City, Utah
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City
| | - Scott M. Damrauer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Corporal Michael Crescenz Department of Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Francesca E. Cunningham
- US Department of Veterans Affairs Center for Medication Safety, Pharmacy Benefits Management Services, Hines, Illinois
| | | | - Michael E. Matheny
- Geriatrics Research Education and Clinical Care Center, US Department of Veterans Affairs Tennessee Valley Healthcare System, Nashville
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - David W. Oslin
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Corporal Michael Crescenz Department of Veterans Affairs Medical Center, Philadelphia, Pennsylvania
| | - Michael S. Icardi
- US Department of Veterans Affairs Iowa City Healthcare System, Iowa City, Iowa
- US Department of Veterans Affairs National Office of Pathology and Laboratory Medicine, Iowa City, Iowa
- Carver College of Medicine, University of Iowa, Iowa City
| | - Sony Tuteja
- Perelman School of Medicine, University of Pennsylvania, Philadelphia
- Corporal Michael Crescenz Department of Veterans Affairs Medical Center, Philadelphia, Pennsylvania
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Ohno-Machado L, Kim J, Gabriel RA, Kuo GM, Hogarth MA. Genomics and electronic health record systems. Hum Mol Genet 2019; 27:R48-R55. [PMID: 29741693 DOI: 10.1093/hmg/ddy104] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 03/19/2018] [Indexed: 01/27/2023] Open
Abstract
Several reviews and case reports have described how information derived from the analysis of genomes are currently included in electronic health records (EHRs) for the purposes of supporting clinical decisions. Since the introduction of this new type of information in EHRs is relatively new (for instance, the widespread adoption of EHRs in the United States is just about a decade old), it is not surprising that a myriad of approaches has been attempted, with various degrees of success. EHR systems undergo much customization to fit the needs of health systems; these approaches have been varied and not always generalizable. The intent of this article is to present a high-level view of these approaches, emphasizing the functionality that they are trying to achieve, and not to advocate for specific solutions, which may become obsolete soon after this review is published. We start by broadly defining the end goal of including genomics in EHRs for healthcare and then explaining the various sources of information that need to be linked to arrive at a clinically actionable genomics analysis using a pharmacogenomics example. In addition, we include discussions on open issues and a vision for the next generation systems that integrate whole genome sequencing and EHRs in a seamless fashion.
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Affiliation(s)
- Lucila Ohno-Machado
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
| | - Jihoon Kim
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
| | - Rodney A Gabriel
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA.,Department of Anesthesiology, University of California San Diego, La Jolla, CA, USA
| | - Grace M Kuo
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Michael A Hogarth
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
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Hersh CP. Pharmacogenomics of chronic obstructive pulmonary disease. Expert Rev Respir Med 2019; 13:459-470. [PMID: 30925849 PMCID: PMC6482089 DOI: 10.1080/17476348.2019.1601559] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 03/27/2019] [Indexed: 02/08/2023]
Abstract
INTRODUCTION Chronic obstructive pulmonary disease (COPD) is a heterogeneous condition, which presents the opportunity for precision therapy based on genetics or other biomarkers. Areas covered: Alpha-1 antitrypsin deficiency, a genetic form of emphysema, provides an example of this precision approach to diagnosis and therapy. To date, research in COPD pharmacogenomics has been limited by small sample sizes, lack of accessible target tissue, failure to consider COPD subtypes, and different outcomes relevant for various medications. There have been several published genome-wide association studies and other omics studies in COPD pharmacogenomics; however, clinical implementation remains far away. There is a growing evidence base for precision prescription of inhaled corticosteroids in COPD, based on clinical phenotypes and blood biomarkers, but not yet based on pharmacogenomics. Expert opinion: At this time, there is insufficient evidence for clinical implementation of COPD pharmacogenomics. Additional genome-wide studies will be required to discover predictors of drug response and to identify genomic biomarkers of COPD subtypes, which could be targeted with subtype-directed therapies.
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Affiliation(s)
- Craig P Hersh
- a Channing Division of Network Medicine and Division of Pulmonary and Critical Care Medicine , Brigham and Women's Hospital, Harvard Medical School , Boston , MA , USA
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Venkatakrishnan K, Rostami‐Hodjegan A. Come Dance With Me: Transformative Changes in the Science and Practice of Drug–Drug Interactions. Clin Pharmacol Ther 2019; 105:1272-1278. [DOI: 10.1002/cpt.1433] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 03/15/2019] [Indexed: 01/04/2023]
Affiliation(s)
| | - Amin Rostami‐Hodjegan
- Centre for Applied Pharmacokinetic ResearchUniversity of Manchester Manchester UK
- Simcyp DivisionCertara UK Limited Sheffield UK
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Dressler LG, Bell GC, Abernathy PM, Ruch K, Denslow S. Implementing pharmacogenetic testing in rural primary care practices: a pilot feasibility study. Pharmacogenomics 2019; 20:433-446. [PMID: 30983513 DOI: 10.2217/pgs-2018-0200] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Aim: Assess feasibility and perspectives of pharmacogenetic testing/PGx in rural, primary care physician (PCP) practices when PCPs are trained to interpret/apply results and testing costs are covered. Methods: Participants included PCPs who agreed to training, surveys and interviews and eligible patients who agreed to surveys and testing. 51 patients from three practices participated. Results: Prestudy, no PCP had ever ordered a PGx test. Test results demonstrated gene variations in 30% of patients, related to current medications, with PCPs reporting changes to drug management. Poststudy, test cost was still a concern, but now PCPs reported practical barriers, including the utilization of PGx results over time. PCPs and patients had favorable responses to testing. Summary: PGx testing is feasible in rural PCP practices.
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Affiliation(s)
- Lynn G Dressler
- Mission Health Personalized Medicine & Pharmacogenomics Program; currently Independent Consultant, LGDconsulting 512, Fairview, NC 28730, USA
| | - Gillian C Bell
- Mission Health Personalized Medicine & Pharmacogenomics Program, Asheville, NC 28801, USA
| | - Pearl M Abernathy
- Mission Health Personalized Medicine & Pharmacogenomics Program, Asheville, NC 28801, USA
| | - Karl Ruch
- Mission Health Personalized Medicine & Pharmacogenomics Program; currently OneOME, Minneapolis, MN,55405, USA
| | - Sheri Denslow
- Mission Health, Mission Research Institute, Asheville, NC 28801, USA
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FARMAPRICE: A Pharmacogenetic Clinical Decision Support System for Precise and Cost-Effective Therapy. Genes (Basel) 2019; 10:genes10040276. [PMID: 30987397 PMCID: PMC6523070 DOI: 10.3390/genes10040276] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/26/2019] [Accepted: 04/01/2019] [Indexed: 01/02/2023] Open
Abstract
Pharmacogenetic (PGx) guidelines for the precise dosing and selection of drugs remain poorly implemented in current clinical practice. Among the barriers to the implementation process is the lack of clinical decision support system (CDSS) tools to aid health providers in managing PGx information in the clinical context. The present study aimed to describe the first Italian endeavor to develop a PGx CDSS, called FARMAPRICE. FARMAPRICE prototype was conceived for integration of patient molecular data into the clinical prescription process in the Italian Centro di Riferimento Oncologico (CRO)-Aviano Hospital. It was developed through a coordinated partnership between two high-tech companies active in the computerization of the Italian healthcare system. Introducing FARMAPRICE into the clinical setting can aid physicians in prescribing the most efficacious and cost-effective pharmacological therapy available.
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50
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Chang A, Nelson R, Brixner D. Advancing pharmacy practice by reducing gaps in pharmacogenetic education. Am J Health Syst Pharm 2019; 76:320-326. [PMID: 30753288 DOI: 10.1093/ajhp/zxy066] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Affiliation(s)
- Annie Chang
- University of California, San Francisco School of Pharmacy, San Francisco, CA
| | - Ryan Nelson
- Department of Individualized Cancer Management, Moffitt Cancer Center, ?Tampa, FL
| | - Diana Brixner
- Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, UT.,Program in Personalized Healthcare, University of Utah, Salt Lake City, UT
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