1
|
Shugg T, Tillman EM, Breman AM, Hodge JC, McDonald CA, Ly RC, Rowe EJ, Osei W, Smith TB, Schwartz PH, Callaghan JT, Pratt VM, Lynch S, Eadon MT, Skaar TC. Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned. Clin Pharmacol Ther 2024. [PMID: 39169556 DOI: 10.1002/cpt.3402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/25/2024] [Indexed: 08/23/2024]
Abstract
In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.
Collapse
Affiliation(s)
- Tyler Shugg
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Emma M Tillman
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Amy M Breman
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jennelle C Hodge
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Christine A McDonald
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Reynold C Ly
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Elizabeth J Rowe
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Wilberforce Osei
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Tayler B Smith
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Peter H Schwartz
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - John T Callaghan
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Victoria M Pratt
- Division of Diagnostic Genomics, Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Sheryl Lynch
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael T Eadon
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Division of Nephrology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Todd C Skaar
- Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| |
Collapse
|
2
|
Simon ST, Lin M, Trinkley KE, Aleong R, Rafaels N, Crooks KR, Reiter MJ, Gignoux CR, Rosenberg MA. A polygenic risk score for the QT interval is an independent predictor of drug-induced QT prolongation. PLoS One 2024; 19:e0303261. [PMID: 38885227 PMCID: PMC11182491 DOI: 10.1371/journal.pone.0303261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 04/23/2024] [Indexed: 06/20/2024] Open
Abstract
Drug-induced QT prolongation (diLQTS), and subsequent risk of torsade de pointes, is a major concern with use of many medications, including for non-cardiac conditions. The possibility that genetic risk, in the form of polygenic risk scores (PGS), could be integrated into prediction of risk of diLQTS has great potential, although it is unknown how genetic risk is related to clinical risk factors as might be applied in clinical decision-making. In this study, we examined the PGS for QT interval in 2500 subjects exposed to a known QT-prolonging drug on prolongation of the QT interval over 500ms on subsequent ECG using electronic health record data. We found that the normalized QT PGS was higher in cases than controls (0.212±0.954 vs. -0.0270±1.003, P = 0.0002), with an unadjusted odds ratio of 1.34 (95%CI 1.17-1.53, P<0.001) for association with diLQTS. When included with age and clinical predictors of QT prolongation, we found that the PGS for QT interval provided independent risk prediction for diLQTS, in which the interaction for high-risk diagnosis or with certain high-risk medications (amiodarone, sotalol, and dofetilide) was not significant, indicating that genetic risk did not modify the effect of other risk factors on risk of diLQTS. We found that a high-risk cutoff (QT PGS ≥ 2 standard deviations above mean), but not a low-risk cutoff, was associated with risk of diLQTS after adjustment for clinical factors, and provided one method of integration based on the decision-tree framework. In conclusion, we found that PGS for QT interval is an independent predictor of diLQTS, but that in contrast to existing theories about repolarization reserve as a mechanism of increasing risk, the effect is independent of other clinical risk factors. More work is needed for external validation in clinical decision-making, as well as defining the mechanism through which genes that increase QT interval are associated with risk of diLQTS.
Collapse
Affiliation(s)
- Steven T. Simon
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Meng Lin
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Katy E. Trinkley
- Department of Clinical Pharmacy, School of Pharmacy, University of Colorado, Aurora, CO, United States of America
| | - Ryan Aleong
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Kristy R. Crooks
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Michael J. Reiter
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Christopher R. Gignoux
- Colorado Center for Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Michael A. Rosenberg
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, United States of America
| |
Collapse
|
3
|
Aquilante CL, Trinkley KE, Lee YM, Crooks KR, Hearst EC, Heckman SM, Hess KW, Kudron EL, Martin JL, Swartz CT, Kao DP. Implementation of clopidogrel pharmacogenetic clinical decision support for a preemptive return of results program. Am J Health Syst Pharm 2024; 81:555-562. [PMID: 38253063 DOI: 10.1093/ajhp/zxae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Indexed: 01/24/2024] Open
Abstract
PURPOSE To describe our experiences implementing and iterating CYP2C19 genotype-guided clopidogrel pharmacogenetic clinical decision support (CDS) tools over time in the setting of a large health system-wide, preemptive pharmacogenomics program. SUMMARY Clopidogrel-treated patients who are genetically predicted cytochrome P450 isozyme 2C19 (CYP2C19) intermediate or poor metabolizers have an increased risk of atherothrombotic events, some of which can be life-threatening. The Clinical Pharmacogenetics Implementation Consortium provides guidance for the use of clopidogrel based on CYP2C19 genotype in patients with cardiovascular and cerebrovascular diseases. Our multidisciplinary team implemented an automated, interruptive alert that fires when clopidogrel is ordered or refilled for biobank participants with structured CYP2C19 intermediate or poor metabolizer genomic indicators in the electronic health record. The implementation began with a narrow cardiovascular indication and setting and was then scaled in 4 primary dimensions: (1) clinical indication; (2) availability across health-system locations; (3) care venue (e.g., inpatient vs outpatient); and (4) provider groups (eg, cardiology and neurology). We iterated our approach over time based on evolving clinical evidence and proactive strategies to optimize CDS maintenance and sustainability. A key facilitator of expansion was socialization of the broader pharmacogenomics initiative among our academic medical center community, accompanied by clinician acceptance of pharmacogenetic alerts in practice. CONCLUSION A multidisciplinary collaboration is recommended to facilitate the use of CYP2C19 genotype-guided antiplatelet therapy in patients with cardiovascular and cerebrovascular diseases. Evolving clopidogrel pharmacogenetic evidence necessitates thoughtful iteration of implementation efforts and strategies to optimize long-term maintenance and sustainability.
Collapse
Affiliation(s)
- Christina L Aquilante
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Katy E Trinkley
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Family Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Yee Ming Lee
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kristy R Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Emily C Hearst
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- UCHealth, Aurora, CO, USA
| | | | | | - Elizabeth L Kudron
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Biomedical Informatics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - James L Martin
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Pharmaceutical Sciences, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - David P Kao
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
- Division of Cardiology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| |
Collapse
|
4
|
Sperber NR, Roberts MC, Gonzales S, Bendz LM, Cragun D, Haga SB, Wu RR, Omeogu C, Kaufman B, Petry NJ, Ramsey LB, Uber R. Pharmacogenetic testing in primary care could bolster depression treatment: A value proposition. Clin Transl Sci 2024; 17:e13837. [PMID: 38898561 PMCID: PMC11186746 DOI: 10.1111/cts.13837] [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: 02/12/2024] [Revised: 04/23/2024] [Accepted: 05/07/2024] [Indexed: 06/21/2024] Open
Abstract
Pharmacogenetic testing could reduce the time to identify a safe and effective medication for depression; however, it is underutilized in practice. Major depression constitutes the most common mental disorder in the US, and while antidepressant therapy can help, the current trial -and error approach can require patients to endure multiple medication trials before finding one that is effective. Tailoring the fit of pharmacogenetic testing with prescribers' needs across a variety of settings could help to establish a generalizable value proposition to improve likelihood of adoption. We conducted a study to explore the value proposition for health systems using pharmacogenetic testing for mental health medications through prescribers' real-world experiences using implementation science concepts and systematic interviews with prescribers and administrators from four health care systems. To identify a value proposition, we organized the themes according to the Triple Aim framework, a leading framework for health care policy which asserts that high-value care should focus on three key metrics: (1) better health care quality and (2) population-level outcomes with (3) reduced per capita costs. Primary care providers whom we interviewed said that they value pharmacogenetic testing because it would provide more information about medications that they can prescribe, expanding their ability to identify medications that best-fit patients and reducing their reliance on referrals to specialists; they said that this capacity would help meet patients' needs for access to mental health care through primary care. At the same time, prescribers expressed differing views about how pharmacogenetic testing can help with quality of care and whether their views about out-of-pocket cost would prevent them from offering it. Thus, implementation should focus on integrating pharmacogenetic testing into primary care and using strategies to support prescribers' interactions with patients.
Collapse
Affiliation(s)
- Nina R. Sperber
- Duke UniversityDurhamNorth CarolinaUSA
- Durham VA Health Care SystemDurhamNCUnited States
| | - Megan C. Roberts
- University of North Carolina – Chapel HillChapel HillNorth CarolinaUSA
| | | | | | | | | | - R. Ryanne Wu
- Duke UniversityDurhamNorth CarolinaUSA
- 23andMeSouth San FranciscoUSA
| | | | - Brystana Kaufman
- Duke UniversityDurhamNorth CarolinaUSA
- Durham VA Health Care SystemDurhamNCUnited States
| | - Natasha J. Petry
- North Dakota State University/Sanford Health ImageneticsFargoNorth DakotaUSA
| | | | | |
Collapse
|
5
|
Johnson D, Del Fiol G, Kawamoto K, Romagnoli KM, Sanders N, Isaacson G, Jenkins E, Williams MS. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc 2024; 31:1183-1194. [PMID: 38558013 PMCID: PMC11031215 DOI: 10.1093/jamia/ocae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVES Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.
Collapse
Affiliation(s)
- Darren Johnson
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Katrina M Romagnoli
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Nathan Sanders
- School of Medicine, Geisinger Health Systems, Danville, PA 17822, United States
| | - Grace Isaacson
- Family Medicine, Penn Highlands Healthcare, DuBois, PA 16830, United States
| | - Elden Jenkins
- School of Medicine, Noorda College of Osteopathic Medicine, Provo, UT 84606, United States
| | - Marc S Williams
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| |
Collapse
|
6
|
Hashimi SR, Babatunde O, Alrajeh K, Dixon RJ, Okpeku A, Price ET. Pharmacogenomics in Clinical Practice for Older People. Sr Care Pharm 2024; 39:132-136. [PMID: 38528338 DOI: 10.4140/tcp.n.2024.132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Older people are over-represented among individuals that experience adverse drug reactions (ADR) and adverse drug events (ADE). Furthermore, older people are over-represented among individuals that visit emergency departments and are hospitalized because of ADRs. Moreover, older people are overrepresented among those who suffer ADEs while hospitalized. Finally, older people are among those most likely to have an anaphylactic response to prescription medications. Therefore, older people are prime candidates for efforts aimed at optimizing pharmacotherapeutic outcomes. Pharmacogenomics is an approach of using genetic data to optimize pharmacotherapeutic outcomes. Over the last two decades, pharmacogenomics grew from research initiatives into the current environment of pharmacogenomics implementation. Specifically, implementing pharmacogenomics into clinical settings or within health care systems has proven beneficial in optimizing pharmacotherapeutic outcomes. Therefore, pharmacists focused on optimizing pharmacotherapeutic outcomes for older people should be aware of the approaches to and resources available for implementing pharmacogenomics. KEY WORDS: Drug labeling biomarkers, Genes, Older adults, Pharmacogenomics.
Collapse
Affiliation(s)
- Syeda R Hashimi
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Olajumoke Babatunde
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Khalifa Alrajeh
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Richard J Dixon
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Aimalohi Okpeku
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| | - Elvin T Price
- 1 Virginia Commonwealth University, School of Pharmacy, Department of Pharmacotherapy and Outcomes Science
| |
Collapse
|
7
|
Kanegusuku ALG, Chan CW, O'Donnell PH, Yeo KTJ. Implementation of pharmacogenomics testing for precision medicine. Crit Rev Clin Lab Sci 2024; 61:89-106. [PMID: 37776898 DOI: 10.1080/10408363.2023.2255279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 08/31/2023] [Indexed: 10/02/2023]
Abstract
Great strides have been made in the past decade to lower barriers to clinical pharmacogenomics implementation. Nevertheless, PGx consultation prior to prescribing therapeutics is not yet mainstream. This review addresses the current climate surrounding PGx implementation, focusing primarily on strategies for implementation at academic institutions, particularly at The University of Chicago, and provides an up-to-date guide of resources supporting the development of PGx programs. Remaining challenges and recent strategies for overcoming these challenges to implementation are discussed.
Collapse
Affiliation(s)
| | - Clarence W Chan
- Departments of Pathology, The University of Chicago, Chicago, IL, USA
| | - Peter H O'Donnell
- Department of Medicine, The University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, USA
| | - Kiang-Teck J Yeo
- Departments of Pathology, The University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, USA
| |
Collapse
|
8
|
Wiley LK, Shortt JA, Roberts ER, Lowery J, Kudron E, Lin M, Mayer D, Wilson M, Brunetti TM, Chavan S, Phang TL, Pozdeyev N, Lesny J, Wicks SJ, Moore ET, Morgenstern JL, Roff AN, Shalowitz EL, Stewart A, Williams C, Edelmann MN, Hull M, Patton JT, Axell L, Ku L, Lee YM, Jirikowic J, Tanaka A, Todd E, White S, Peterson B, Hearst E, Zane R, Greene CS, Mathias R, Coors M, Taylor M, Ghosh D, Kahn MG, Brooks IM, Aquilante CL, Kao D, Rafaels N, Crooks KR, Hess S, Barnes KC, Gignoux CR. Building a vertically integrated genomic learning health system: The biobank at the Colorado Center for Personalized Medicine. Am J Hum Genet 2024; 111:11-23. [PMID: 38181729 PMCID: PMC10806731 DOI: 10.1016/j.ajhg.2023.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/30/2023] [Accepted: 12/01/2023] [Indexed: 01/07/2024] Open
Abstract
Precision medicine initiatives across the globe have led to a revolution of repositories linking large-scale genomic data with electronic health records, enabling genomic analyses across the entire phenome. Many of these initiatives focus solely on research insights, leading to limited direct benefit to patients. We describe the biobank at the Colorado Center for Personalized Medicine (CCPM Biobank) that was jointly developed by the University of Colorado Anschutz Medical Campus and UCHealth to serve as a unique, dual-purpose research and clinical resource accelerating personalized medicine. This living resource currently has more than 200,000 participants with ongoing recruitment. We highlight the clinical, laboratory, regulatory, and HIPAA-compliant informatics infrastructure along with our stakeholder engagement, consent, recontact, and participant engagement strategies. We characterize aspects of genetic and geographic diversity unique to the Rocky Mountain region, the primary catchment area for CCPM Biobank participants. We leverage linked health and demographic information of the CCPM Biobank participant population to demonstrate the utility of the CCPM Biobank to replicate complex trait associations in the first 33,674 genotyped individuals across multiple disease domains. Finally, we describe our current efforts toward return of clinical genetic test results, including high-impact pathogenic variants and pharmacogenetic information, and our broader goals as the CCPM Biobank continues to grow. Bringing clinical and research interests together fosters unique clinical and translational questions that can be addressed from the large EHR-linked CCPM Biobank resource within a HIPAA- and CLIA-certified environment.
Collapse
Affiliation(s)
- Laura K Wiley
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jonathan A Shortt
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Emily R Roberts
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jan Lowery
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Community and Behavioral Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Elizabeth Kudron
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - David Mayer
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Melissa Wilson
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tonya M Brunetti
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Sameer Chavan
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tzu L Phang
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nikita Pozdeyev
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Joseph Lesny
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Stephen J Wicks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Ethan T Moore
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Joshua L Morgenstern
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Alanna N Roff
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Elise L Shalowitz
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adrian Stewart
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Cole Williams
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Michelle N Edelmann
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Madelyne Hull
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - J Tacker Patton
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Lisen Axell
- CU Cancer Center, Hereditary Cancer Clinic, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Lisa Ku
- CU Cancer Center, Hereditary Cancer Clinic, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Yee Ming Lee
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | | | - Emily Todd
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; UCHealth, Aurora, CO 80045, USA
| | | | - Brett Peterson
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Richard Zane
- UCHealth, Aurora, CO 80045, USA; University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Casey S Greene
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Rasika Mathias
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Marilyn Coors
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Matthew Taylor
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Division of Cardiology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO 80045, USA
| | - Michael G Kahn
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Ian M Brooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christina L Aquilante
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - David Kao
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Division of Cardiology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; CARE Innovation Center, UCHealth, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy R Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Pathology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Kathleen C Barnes
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA; Department of Biomedical Informatics, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
| |
Collapse
|
9
|
Li LJ, Legeay S, Gagnon AL, Frigon MP, Tessier L, Tremblay K. Moving towards the implementation of pharmacogenetic testing in Quebec. Front Genet 2024; 14:1295963. [PMID: 38234998 PMCID: PMC10791884 DOI: 10.3389/fgene.2023.1295963] [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: 09/17/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024] Open
Abstract
Clinical implementation of pharmacogenetics (PGx) into routine care will elevate the current paradigm of treatment decisions. However, while PGx tests are increasingly becoming reliable and affordable, several barriers have limited their widespread usage in Canada. Globally, over ninety successful PGx implementors can serve as models. The purpose of this paper is to outline the PGx implementation barriers documented in Quebec (Canada) to suggest efficient solutions based on existing PGx clinics and propose an adapted clinical implementation model. We conclude that the province of Quebec is ready to implement PGx.
Collapse
Affiliation(s)
- Ling Jing Li
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Medicine Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
| | - Samuel Legeay
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Medicine Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
- University Angers, [CHU Angers], Inserm, CNRS, MINT, Angers, France
| | - Ann-Lorie Gagnon
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
| | - Marie-Pier Frigon
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pediatrics Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Laurence Tessier
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pharmacology-Physiology Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
| | - Karine Tremblay
- Centre Intégré Universitaire de Santé et de Services Sociaux Du Saguenay-Lac-Saint-Jean (Chicoutimi University Hospital), Research Center, Saguenay, QC, Canada
- Pharmacology-Physiology Department, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Saguenay, QC, Canada
- Centre de Recherche Du Centre Hospitalier Universitaire de Sherbrooke (CR-CHUS), Sherbrooke, QC, Canada
| |
Collapse
|
10
|
Moxham R, Tjokrowidjaja A, Devery S, Smyth R, McLean A, Roberts DM, Wu KHC. Clinical utilities and end-user experience of pharmacogenomics: 39 mo of clinical implementation experience in an Australian hospital setting. World J Med Genet 2023; 11:39-50. [DOI: 10.5496/wjmg.v11.i4.39] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 11/06/2023] [Accepted: 11/30/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND Pharmacogenomics (PG) testing is under-utilised in Australia. Our research provides Australia-specific data on the perspectives of patients who have had PG testing and those of the clinicians involved in their care, with the aim to inform wider adoption of PG into routine clinical practice.
AIM To investigate the frequency of actionable drug gene interactions and assess the perceived utility of PG among patients and clinicians.
METHODS We conducted a retrospective audit of PG undertaken by 100 patients at an Australian public hospital genetics service from 2018 to 2021. Via electronic surveys we compared and contrasted the experience, understanding and usage of results between these patients and their clinicians.
RESULTS Of 100 patients who had PG, 84% were taking prescription medications, of which 67% were taking medications with actionable drug-gene interactions. Twenty-five out of 81 invited patients and 17 out of 89 invited clinicians completed the surveys. Sixty-eight percent of patients understood their PG results and 48% had medications changed following testing. Paired patient-clinician surveys showed patient-perceived utility and experience was positive, contrasting their clinicians’ hesitancy on PG adoption who identified insufficient education/training, lack of clinical support, test turnaround time and cost as barriers to adoption.
CONCLUSION Our dichotomous findings between the perspectives of our patient and clinician cohorts suggest the uptake of PG is likely to be driven by patients and clinicians need to be prepared to provide information and guidance to their patients.
Collapse
Affiliation(s)
- Rosalind Moxham
- Clinical Genomics, St Vincent's Hospital, NSW, Sydney 2010, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, NSW, Sydney 2031, Australia
| | - Andrew Tjokrowidjaja
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, NSW, Sydney 2031, Australia
| | - Sophie Devery
- Clinical Genomics, St Vincent's Hospital, NSW, Sydney 2010, Australia
| | - Renee Smyth
- Clinical Genomics, St Vincent's Hospital, NSW, Sydney 2010, Australia
| | - Alison McLean
- Clinical Genomics, St Vincent's Hospital, NSW, Sydney 2010, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, NSW, Sydney 2031, Australia
| | - Darren M Roberts
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, NSW, Sydney 2031, Australia
- Clinical Pharmacology, Drug Health Services, Royal Prince Alfred Hospital, NSW, Sydney 2050, Australia
| | - Kathy H C Wu
- Clinical Genomics, St Vincent's Hospital, NSW, Sydney 2010, Australia
- School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, NSW, Sydney 2031, Australia
- School of Medicine, University of Notre Dame Australia, NSW, Sydney 2010, Australia
- Discipline of Genetic Medicine, University of Sydney, NSW, Sydney 2006, Australia
| |
Collapse
|
11
|
Rodriguez Llorian E, Kopac N, Waliji LA, Borle K, Dragojlovic N, Elliott AM, Lynd LD. A Rapid Review on the Value of Biobanks Containing Genetic Information. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2023; 26:1286-1295. [PMID: 36921900 DOI: 10.1016/j.jval.2023.02.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Revised: 01/20/2023] [Accepted: 02/24/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVES Increasing access to health data through biobanks containing genetic information has the potential to expand the knowledge base and thereby improve screening, diagnosis, and treatment options for many diseases. Nevertheless, although privacy concerns and risks surrounding genetic data sharing are well documented, direct evidence in favor of the hypothesized benefits of data integration is scarce, which complicates decision making in this area. Therefore, the objective of this study is to summarize the available evidence on the research and clinical impacts of biobanks containing genetic information, so as to better understand how to quantify the value of expanding genomic data access. METHODS Using a rapid review methodology, we performed a search of MEDLINE/PubMed and Embase databases; and websites of biobanks and genomic initiatives published from 2010 to 2022. We classified findings into 11 indicators including outputs (a direct product of the biobank activities) and outcomes (changes in scientific and clinical capacity). RESULTS Of 8479 abstracts and 101 gray literature sources were reviewed, 96 records were included. Although most records did not report key indicators systematically, the available evidence concentrated on research indicators such as publications and gene-disorder association discoveries (63% of studies), followed by research infrastructure (26%), and clinical indicators (11%) such as supporting the diagnosis of individual patients. CONCLUSIONS Existing evidence on the benefits of biobanks is skewed toward easily quantifiable research outputs. Measuring a comprehensive set of outputs and outcomes inspired by value frameworks is necessary to generate better evidence on the benefits of genomic data sharing.
Collapse
Affiliation(s)
- Elisabet Rodriguez Llorian
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada.
| | - Nicola Kopac
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Louloua Ashikhusein Waliji
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Kennedy Borle
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Nick Dragojlovic
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Alison M Elliott
- Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Larry D Lynd
- Collaboration for Outcomes Research and Evaluation (CORE), Faculty of Pharmaceutical Sciences, The University of British Columbia, Vancouver, British Columbia, Canada; Centre for Health Evaluation and Outcome Sciences (CHÉOS), St. Paul's Hospital, Vancouver, BC, Canada
| |
Collapse
|
12
|
McDermott JH, Sharma V, Keen J, Newman WG, Pirmohamed M. The Implementation of Pharmacogenetics in the United Kingdom. Handb Exp Pharmacol 2023; 280:3-32. [PMID: 37306816 DOI: 10.1007/164_2023_658] [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: 06/13/2023]
Abstract
There is considerable inter-individual variability in the effectiveness and safety of pharmaceutical interventions. This phenomenon can be attributed to a multitude of factors; however, it is widely acknowledged that common genetic variation affecting drug absorption or metabolism play a substantial contributory role. This is a concept known as pharmacogenetics. Understanding how common genetic variants influence responses to medications, and using this knowledge to inform prescribing practice, could yield significant advantages for both patients and healthcare systems. Some health services around the world have introduced pharmacogenetics into routine practice, whereas others are less advanced along the implementation pathway. This chapter introduces the field of pharmacogenetics, the existing body of evidence, and discusses barriers to implementation. The chapter will specifically focus on efforts to introduce pharmacogenetics in the NHS, highlighting key challenges related to scale, informatics, and education.
Collapse
Affiliation(s)
- John H McDermott
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Videha Sharma
- Division of Informatics, Imaging and Data Science, Centre for Health Informatics, The University of Manchester, Manchester, UK
| | - Jessica Keen
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
| | - William G Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, University of Liverpool, Liverpool, UK.
- Liverpool University Hospital Foundation NHS Trust, Liverpool, UK.
| |
Collapse
|
13
|
Pasternak AL, Ward K, Irwin M, Okerberg C, Hayes D, Fritsche L, Zoellner S, Virzi J, Choe HM, Ellingrod V. Identifying the prevalence of clinically actionable drug-gene interactions in a health system biorepository to guide pharmacogenetics implementation services. Clin Transl Sci 2022; 16:292-304. [PMID: 36510710 PMCID: PMC9926071 DOI: 10.1111/cts.13449] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 10/14/2022] [Accepted: 10/24/2022] [Indexed: 12/15/2022] Open
Abstract
Understanding patterns of drug-gene interactions (DGIs) is important for advancing the clinical implementation of pharmacogenetics (PGx) into routine practice. Prior studies have estimated the prevalence of DGIs, but few have confirmed DGIs in patients with known genotypes and prescriptions, nor have they evaluated clinician characteristics associated with DGI-prescribing. This retrospective chart review assessed prevalence of DGI, defined as a medication prescription in a patient with a PGx phenotype that has a clinical practice guideline recommendation to adjust therapy or monitor drug response, for patients enrolled in a research genetic biorepository linked to electronic health records (EHRs). The prevalence of prescriptions for medications with pharmacogenetic (PGx) guidelines, proportion of prescriptions with DGI, location of DGI prescription, and clinical service of the prescriber were evaluated descriptively. Seventy-five percent (57,058/75,337) of patients had a prescription for a medication with a PGx guideline. Up to 60% (n = 26,067/43,647) of patients had at least one DGI when considering recommendations to adjust or monitor therapy based on genotype. The majority (61%) of DGIs occurred in outpatient prescriptions. Proton pump inhibitors were the most common DGI medication for 11 of 12 clinical services. Almost 25% of patients (n = 10,706/43,647) had more than one unique DGI, and, among this group of patients, 61% had a DGI with more than one gene. These findings can inform future clinical implementation by identifying key stakeholders for initial DGI prescriptions, helping to inform workflows. The high prevalence of multigene interactions identified also support the use of panel PGx testing as an implementation strategy.
Collapse
Affiliation(s)
- Amy L. Pasternak
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA,Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Kristen Ward
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA,Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Madison Irwin
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA,Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Carl Okerberg
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - David Hayes
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
| | - Lars Fritsche
- Department of BiostatisticsUniversity of Michigan School of Public HealthAnn ArborMichiganUSA
| | - Sebastian Zoellner
- Department of BiostatisticsUniversity of Michigan School of Public HealthAnn ArborMichiganUSA
| | - Jessica Virzi
- Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Hae Mi Choe
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA,Michigan MedicineUniversity of Michigan HealthAnn ArborMichiganUSA
| | - Vicki Ellingrod
- Department of Clinical PharmacyUniversity of Michigan College of PharmacyAnn ArborMichiganUSA
| |
Collapse
|
14
|
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.
Collapse
|
15
|
Fricke-Galindo I, Falfán-Valencia R. Current pharmacogenomic recommendations in chronic respiratory diseases: Is there a biomarker ready for clinical implementation? Expert Rev Respir Med 2022; 16:1145-1152. [PMID: 36416606 DOI: 10.1080/17476348.2022.2149496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
INTRODUCTION The study of genetic variants in response to different drugs has predominated in fields of medicine such as oncology and infectious diseases. In chronic respiratory diseases, the available pharmacogenomic information is scarce but not less relevant. AREAS COVERED We searched the pharmacogenomic recommendations for respiratory diseases in the Table of Pharmacogenomic Biomarkers in Drug Labeling (U.S. Food and Drug Administration), the Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. The main pharmacogenomics recommendation in this field is to assess CFTR variants for using ivacaftor and its combination. The drugs' labels for arformoterol, indacaterol, and umeclidinium indicate a lack of influence of genetic variants in the pharmacokinetics of these drugs. Further studies should evaluate the contribution of CYP2D6 and CYP2C19 variants for formoterol. In addition, there are reports of potential pharmacogenetic variants in the treatment with acetylcysteine (TOLLIP rs3750920) and captopril (ACE rs1799752). The genetic variations for warfarin also are presented in PharmGKB and CPIC for patients with pulmonary hypertension. EXPERT OPINION The pharmacogenomics recommendations for lung diseases are limited. The clinical implementation of pharmacogenomics in treating respiratory diseases will contribute to the quality of life of patients with chronic respiratory diseases.
Collapse
Affiliation(s)
- Ingrid Fricke-Galindo
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, 14080, Mexico City, Mexico
| | - Ramcés Falfán-Valencia
- HLA Laboratory, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, 14080, Mexico City, Mexico
| |
Collapse
|
16
|
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.
Collapse
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
| |
Collapse
|
17
|
Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
Collapse
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; , , , ,
| |
Collapse
|
18
|
O'Sullivan JW, Raghavan S, Marquez-Luna C, Luzum JA, Damrauer SM, Ashley EA, O'Donnell CJ, Willer CJ, Natarajan P. Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association. Circulation 2022; 146:e93-e118. [PMID: 35862132 PMCID: PMC9847481 DOI: 10.1161/cir.0000000000001077] [Citation(s) in RCA: 86] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.
Collapse
|
19
|
McDermott JH, Wright S, Sharma V, Newman WG, Payne K, Wilson P. Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review. Front Med (Lausanne) 2022; 9:945352. [PMID: 36059837 PMCID: PMC9433561 DOI: 10.3389/fmed.2022.945352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/29/2022] [Indexed: 12/11/2022] Open
Abstract
Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.
Collapse
Affiliation(s)
- John H. McDermott
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
- *Correspondence: John H. McDermott,
| | - Stuart Wright
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Videha Sharma
- Division of Informatics, Centre for Health Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - William G. Newman
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
| | - Katherine Payne
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Paul Wilson
- Division of Population Health, Centre for Primary Care and Health Services Research, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| |
Collapse
|
20
|
Selig DJ, Livezey JR, Chin GC, DeLuca JP, Guillory Ii WO, Kress AT, Oliver TO, Por ED. Prescription Patterns and Relationship to Pharmacogenomics Testing in the Military Health System. Mil Med 2021; 187:9-17. [PMID: 34967405 DOI: 10.1093/milmed/usab481] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/21/2021] [Accepted: 12/03/2021] [Indexed: 11/12/2022] Open
Abstract
INTRODUCTION Clinical utilization of pharmacogenomics (PGx) testing is highly institutionally dependent, and little information is known about provider practices of PGx testing in the Military Health System (MHS). In this study, we aimed to characterize Clinical Pharmacogenetics Implementation Consortium (CPIC) actionable prescription (Rx) patterns and their temporal relationship with PGx testing in the MHS. METHODS Using data from the Military Health System Management Analysis and Reporting Tool (M2) database, this retrospective cohort study included all patients receiving at least one PGx test and at least one CPIC actionable Rx from January 2015 to August 2020 (845 patients, 1,471 PGx, 7,725 index CPIC actionable Rxs). Rx patterns and temporal relationships with PGx testing were characterized via descriptive statistics. Binomial regression was used to determine which patient and provider characteristics were associated with a patient receiving a PGx test within 30 days of an index Rx. RESULTS Patients had a median of 9 index CPIC actionable Rx's (range 1-26). Pain medications were most commonly prescribed (N = 794, 94% patients with at least 1 Rx). However, pain medication had the lowest Rx-PGx match rate (40%) compared to an average of 62% Rx-PGx match rate for all CPIC drugs. Antidepressants were also commonly prescribed (N = 668, 79.1% patients with at least 1 Rx), and antidepressants had the highest Rx-PGx match rate of 86.7%. A minority of providers (20%, N = 249) ordered the majority of PGx tests (86.1%, N = 1,266) and only 8.3% of PGx tests (N = 398) matched to a CPIC actionable drug within 30 days of the test (defined by Rxs ordered within 30 days before or after the PGx test). However, approximately 39.8% of patients (N = 317) had at least one drug match to a PGx test within 30 days. The largest predictor of whether a patient received a PGx test within 30 days of any index Rx was whether or not a specific psychiatry provider ordered the PGx test (odds ratio; OR 3.7, 95% CI 2.13-6.54, P < 0.001). Neither the CPIC level of evidence nor FDA PGx actionable or informative labels had a significant effect on PGx test timing. CONCLUSIONS PGx testing was generally limited to high Rx-drug users and was found to be an under-utilized resource. PGx testing did not typically follow CPIC guidelines. Implementing PGx testing protocols, simplifying PGx test-ordering by incorporating at minimum CYP2D6, CYP2C19, and CYP2C9 into PGx-testing panels, and unifying providers' PGx knowledgebase in the MHS are feasible and would improve the clinical utilization of PGx tests in the MHS.
Collapse
Affiliation(s)
- Daniel J Selig
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Jeffrey R Livezey
- Clinical Pharmacology Department, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Geoffrey C Chin
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Jesse P DeLuca
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Walter O Guillory Ii
- The Internal Medicine Department, Walter Reed National Military Medical Center, Bethesda, MD 20814, USA
| | - Adrian T Kress
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| | - Thomas O Oliver
- Clinical Pharmacology Department, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Elaine D Por
- Experimental Therapeutics Department, Walter Reed Army Institute of Research, Silver Spring, MD 20910, USA
| |
Collapse
|
21
|
J. Ost K, W. Anderson D, W. Cadotte D. Delivering Precision Medicine to Patients with Spinal Cord Disorders; Insights into Applications of Bioinformatics and Machine Learning from Studies of Degenerative Cervical Myelopathy. ARTIF INTELL 2021. [DOI: 10.5772/intechopen.98713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
With the common adoption of electronic health records and new technologies capable of producing an unprecedented scale of data, a shift must occur in how we practice medicine in order to utilize these resources. We are entering an era in which the capacity of even the most clever human doctor simply is insufficient. As such, realizing “personalized” or “precision” medicine requires new methods that can leverage the massive amounts of data now available. Machine learning techniques provide one important toolkit in this venture, as they are fundamentally designed to deal with (and, in fact, benefit from) massive datasets. The clinical applications for such machine learning systems are still in their infancy, however, and the field of medicine presents a unique set of design considerations. In this chapter, we will walk through how we selected and adjusted the “Progressive Learning framework” to account for these considerations in the case of Degenerative Cervical Myeolopathy. We additionally compare a model designed with these techniques to similar static models run in “perfect world” scenarios (free of the clinical issues address), and we use simulated clinical data acquisition scenarios to demonstrate the advantages of our machine learning approach in providing personalized diagnoses.
Collapse
|
22
|
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.
Collapse
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
| |
Collapse
|
23
|
Zubiaur P, Mejía-Abril G, Navares-Gómez M, Villapalos-García G, Soria-Chacartegui P, Saiz-Rodríguez M, Ochoa D, Abad-Santos F. PriME-PGx: La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics. J Clin Med 2021; 10:jcm10173772. [PMID: 34501219 PMCID: PMC8432257 DOI: 10.3390/jcm10173772] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 12/18/2022] Open
Abstract
The implementation of clinical pharmacogenetics in daily practice is limited for various reasons. Today, however, it is a discipline in full expansion. Accordingly, in the recent times, several initiatives promoted its implementation, mainly in the United States but also in Europe. In this document, the genotyping results since the establishment of our Pharmacogenetics Unit in 2006 are described, as well as the historical implementation process that was carried out since then. Finally, this progress justified the constitution of La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx), promoted by the Clinical Pharmacology Department of Hospital Universitario de La Princesa (Madrid, Spain). Here, we present the initiative along with the two first ongoing projects: the PROFILE project, which promotes modernization of pharmacogenetic reporting (i.e., from classic gene-drug pair reporting to complete pharmacogenetic reporting or the creation of pharmacogenetic profiles specific to the Hospital’s departments) and the GENOTRIAL project, which promotes the communication of relevant pharmacogenetic findings to any healthy volunteer participating in any bioequivalence clinical trial at the Clinical Trials Unit of Hospital Universitario de La Princesa (UECHUP).
Collapse
Affiliation(s)
- Pablo Zubiaur
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
| | - Gina Mejía-Abril
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Marcos Navares-Gómez
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Gonzalo Villapalos-García
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Paula Soria-Chacartegui
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Miriam Saiz-Rodríguez
- Research Unit, Fundación Burgos por la Investigación de la Salud (FBIS), Hospital Universitario de Burgos, 09006 Burgos, Spain;
| | - Dolores Ochoa
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28200 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
| |
Collapse
|
24
|
Interactions between cardiology and oncology drugs in precision cardio-oncology. Clin Sci (Lond) 2021; 135:1333-1351. [PMID: 34076246 DOI: 10.1042/cs20200309] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 04/26/2021] [Accepted: 05/10/2021] [Indexed: 12/13/2022]
Abstract
Recent advances in treatment have transformed the management of cancer. Despite these advances, cardiovascular disease remains a leading cause of death in cancer survivors. Cardio-oncology has recently evolved as a subspecialty to prevent, diagnose, and manage cardiovascular side effects of antineoplastic therapy. An emphasis on optimal management of comorbidities and close attention to drug interactions are important in cardio-oncologic care. With interdisciplinary collaboration among oncologists, cardiologists, and pharmacists, there is potential to prevent and reduce drug-related toxicities of treatments. The cytochrome P450 (CYP450) family of enzymes and the P-glycoprotein (P-g) transporter play a crucial role in drug metabolism and drug resistance. Here we discuss the role of CYP450 and P-g in drug interactions in the field of cardio-oncology, provide an overview of the cardiotoxicity of a spectrum of cancer agents, highlight the role of precision medicine, and encourage a multidisciplinary treatment approach for patients with cancer.
Collapse
|
25
|
Tillman EM, Beavers CJ, Afanasjeva J, Momary KM, Strnad KG, Yerramilli A, Williams AM, Smith BA, Florczykowski B, Fahmy M. Current and future state of clinical pharmacist‐led precision medicine initiatives. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2021. [DOI: 10.1002/jac5.1447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Monica Fahmy
- American College of Clinical Pharmacy Lenexa Kansas USA
| |
Collapse
|
26
|
Luczak T, Brown SJ, Armbruster D, Hundertmark M, Brown J, Stenehjem D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 2021; 22:345-364. [PMID: 33829852 DOI: 10.2217/pgs-2020-0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.
Collapse
Affiliation(s)
- Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, MN 55455, USA
| | - Danielle Armbruster
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Megan Hundertmark
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Jacob Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| |
Collapse
|
27
|
Liko I, Lee YM, Stutzman DL, Blackmer AB, Deininger KM, Reynolds AM, Aquilante CL. Providers' perspectives on the clinical utility of pharmacogenomic testing in pediatric patients. Pharmacogenomics 2021; 22:263-274. [PMID: 33657875 DOI: 10.2217/pgs-2020-0112] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: To assess providers' knowledge, attitudes, perceptions, and experiences related to pharmacogenomic (PGx) testing in pediatric patients. Materials & methods: An electronic survey was sent to multidisciplinary healthcare providers at a pediatric hospital. Results: Of 261 respondents, 71.3% were slightly or not at all familiar with PGx, despite 50.2% reporting prior PGx education or training. Most providers, apart from psychiatry, perceived PGx to be at least moderately useful to inform clinical decisions. However, only 26.4% of providers had recent PGx testing experience. Unfamiliarity with PGx and uncertainty about the clinical value of testing were common perceived challenges. Conclusion: Low PGx familiarity among pediatric providers suggests additional education and electronic resources are needed for PGx examples in which data support testing in children.
Collapse
Affiliation(s)
- Ina Liko
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Yee Ming Lee
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Danielle L Stutzman
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Pharmacy, Children's Hospital Colorado, Aurora, CO 80045, USA.,Pediatric Mental Health Institute, Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Allison B Blackmer
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Pharmacy, Children's Hospital Colorado, Aurora, CO 80045, USA.,Special Care Clinic, Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Kimberly M Deininger
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Ann M Reynolds
- Special Care Clinic, Children's Hospital Colorado, Aurora, CO 80045, USA.,Department of Pediatrics, University of Colorado School of Medicine & Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Christina L Aquilante
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| |
Collapse
|
28
|
Shah SN, Gammal RS, Amato MG, Alobaidly M, Reyes DD, Hasan S, Seger DL, Krier JB, Bates DW. Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events. Drug Saf 2021; 44:601-607. [PMID: 33620701 DOI: 10.1007/s40264-021-01050-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2021] [Indexed: 12/20/2022]
Abstract
INTRODUCTION Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy. OBJECTIVE We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing. METHODS Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs. RESULTS Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction. CONCLUSION Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.
Collapse
Affiliation(s)
- Sonam N Shah
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA. .,Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA.
| | - Roseann S Gammal
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA.,Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Mary G Amato
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA.,Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Maryam Alobaidly
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Dariel Delos Reyes
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Sarah Hasan
- Department of Pharmacy Practice, MCPHS University School of Pharmacy, Boston, MA, USA
| | - Diane L Seger
- Clinical Quality Analysis, Partners Healthcare, Somerville, MA, USA
| | - Joel B Krier
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - David W Bates
- Department of Internal Medicine, Brigham and Women's Hospital, 41 Avenue of Louis Pasteur, Office 103, Boston, MA, 02115, USA.,Clinical Quality Analysis, Partners Healthcare, Somerville, MA, USA.,Harvard Medical School, Boston, MA, USA
| |
Collapse
|
29
|
Jones S. Welcome to the 22nd volume of Pharmacogenomics. Pharmacogenomics 2021; 22:123-124. [PMID: 33619995 DOI: 10.2217/pgs-2021-0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Sarah Jones
- Commissioning Editor, Future Medicine, 2 Unitec House, Albert Place, London N3 1QB, UK
| |
Collapse
|
30
|
Stevenson JM, Alexander GC, Palamuttam N, Mehta HB. Projected Utility of Pharmacogenomic Testing Among Individuals Hospitalized With COVID-19: A Retrospective Multicenter Study in the United States. Clin Transl Sci 2021; 14:153-162. [PMID: 33085221 PMCID: PMC7877860 DOI: 10.1111/cts.12919] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Accepted: 10/07/2020] [Indexed: 12/24/2022] Open
Abstract
Many academic institutions are collecting blood samples from patients seeking treatment for coronavirus disease 2019 (COVID-19) to build research biorepositories. It may be feasible to extract pharmacogenomic (PGx) information from biorepositories for clinical use. We sought to characterize the potential value of multigene PGx testing among individuals hospitalized with COVID-19 in the United States. We performed a cross-sectional analysis of electronic health records from consecutive individuals hospitalized with COVID-19 at a large, urban academic health system. We characterized medication orders, focusing on medications with actionable PGx guidance related to 14 commonly assayed genes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, DPYD, G6PD, HLA-A, HLA-B, IFNL3, NUDT15, SLCO1B1, TPMT, UGT1A1, and VKORC1). A simulation analysis combined medication data with population phenotype frequencies to estimate how many treatment modifications would be enabled if multigene PGx results were available. Sixty-four unique medications with PGx guidance were ordered at least once in the cohort (n = 1,852, mean age 60.1 years). Nearly nine in 10 individuals (89.7%) had at least one order for a medication with PGx guidance and 427 patients (23.1%) had orders for 4 or more actionable medications. Using a simulation, we estimated that 17 treatment modifications per 100 patients would be enabled if PGx results were available. The genes CYP2D6 and CYP2C19 were responsible for the majority of treatment modifications, and the medications most often affected were ondansetron, oxycodone, and clopidogrel. PGx results would be relevant for nearly all individuals hospitalized with COVID-19 and would provide the opportunity to improve clinical care.
Collapse
Affiliation(s)
- James M. Stevenson
- Division of Clinical PharmacologyJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - G. Caleb Alexander
- Center for Drug Safety and EffectivenessJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Division of General Internal MedicineJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Natasha Palamuttam
- Division of Health Sciences InformaticsJohns Hopkins University School of MedicineBaltimoreMarylandUSA
| | - Hemalkumar B. Mehta
- Center for Drug Safety and EffectivenessJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| |
Collapse
|
31
|
Technologies for Pharmacogenomics: A Review. Genes (Basel) 2020; 11:genes11121456. [PMID: 33291630 PMCID: PMC7761897 DOI: 10.3390/genes11121456] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/30/2020] [Accepted: 12/02/2020] [Indexed: 12/11/2022] Open
Abstract
The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels-in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.
Collapse
|
32
|
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.
Collapse
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
| |
Collapse
|
33
|
B. Tata E, A. Ambele M, S. Pepper M. Barriers to Implementing Clinical Pharmacogenetics Testing in Sub-Saharan Africa. A Critical Review. Pharmaceutics 2020; 12:pharmaceutics12090809. [PMID: 32858798 PMCID: PMC7560181 DOI: 10.3390/pharmaceutics12090809] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 08/19/2020] [Accepted: 08/22/2020] [Indexed: 12/14/2022] Open
Abstract
Clinical research in high-income countries is increasingly demonstrating the cost- effectiveness of clinical pharmacogenetic (PGx) testing in reducing the incidence of adverse drug reactions and improving overall patient care. Medications are prescribed based on an individual’s genotype (pharmacogenes), which underlies a specific phenotypic drug response. The advent of cost-effective high-throughput genotyping techniques coupled with the existence of Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines for pharmacogenetic “actionable variants” have increased the clinical applicability of PGx testing. The implementation of clinical PGx testing in sub-Saharan African (SSA) countries can significantly improve health care delivery, considering the high incidence of communicable diseases, the increasing incidence of non-communicable diseases, and the high degree of genetic diversity in these populations. However, the implementation of PGx testing has been sluggish in SSA, prompting this review, the aim of which is to document the existing barriers. These include under-resourced clinical care logistics, a paucity of pharmacogenetics clinical trials, scientific and technical barriers to genotyping pharmacogene variants, and socio-cultural as well as ethical issues regarding health-care stakeholders, among other barriers. Investing in large-scale SSA PGx research and governance, establishing biobanks/bio-databases coupled with clinical electronic health systems, and encouraging the uptake of PGx knowledge by health-care stakeholders, will ensure the successful implementation of pharmacogenetically guided treatment in SSA.
Collapse
Affiliation(s)
- Emiliene B. Tata
- Institute for Cellular and Molecular Medicine, Department of Immunology, and South African Medical Research Council Extramural Unit for Stem Cell Research & Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria 0084, South Africa; (E.B.T.); (M.A.A.)
| | - Melvin A. Ambele
- Institute for Cellular and Molecular Medicine, Department of Immunology, and South African Medical Research Council Extramural Unit for Stem Cell Research & Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria 0084, South Africa; (E.B.T.); (M.A.A.)
- Department of Oral Pathology and Oral Biology, Faculty of Health Sciences, School of Dentistry, University of Pretoria, PO BOX 1266, Pretoria 0001, South Africa
| | - Michael S. Pepper
- Institute for Cellular and Molecular Medicine, Department of Immunology, and South African Medical Research Council Extramural Unit for Stem Cell Research & Therapy, Faculty of Health Sciences, University of Pretoria, Pretoria 0084, South Africa; (E.B.T.); (M.A.A.)
- Correspondence: ; Tel.: +27-12-319-2190
| |
Collapse
|
34
|
Osman I, Cotzia P, Moran U, Donnelly D, Arguelles-Grande C, Mendoza S, Moreira A. The urgency of utilizing COVID-19 biospecimens for research in the heart of the global pandemic. J Transl Med 2020; 18:219. [PMID: 32487093 PMCID: PMC7266426 DOI: 10.1186/s12967-020-02388-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 05/22/2020] [Indexed: 02/04/2023] Open
Abstract
The outbreak of the novel coronavirus disease 2019 (COVID-19) and consequent social distancing practices have disrupted essential clinical research functions worldwide. Ironically, this coincides with an immediate need for research to comprehend the biology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the pathology of COVID-19. As the global crisis has already led to over 15,000 deaths out of 175,000 confirmed cases in New York City and Nassau County, NY alone, it is increasingly urgent to collect patient biospecimens linked to active clinical follow up. However, building a COVID-19 biorepository amidst the active pandemic is a complex and delicate task. To help facilitate rapid, robust, and regulated research on this novel virus, we report on the successful model implemented by New York University Langone Health (NYULH) within days of outbreak in the most challenging hot spot of infection globally. Using an amended institutional biobanking protocol, these efforts led to accrual of 11,120 patients presenting for SARS-CoV-2 testing, 4267 (38.4%) of whom tested positive for COVID-19. The recently reported genomic characterization of SARS-CoV-2 in the New York City Region, which is a crucial development in tracing sources of infection and asymptomatic spread of the novel virus, is the first outcome of this effort. While this growing resource actively supports studies of the New York outbreak in real time, a worldwide effort is necessary to build a collective arsenal of research tools to deal with the global crisis now, and to exploit the virus's biology for translational innovation that outlasts humanity's current dilemma.
Collapse
Affiliation(s)
- Iman Osman
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA.
| | - Paolo Cotzia
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| | - Una Moran
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| | - Douglas Donnelly
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| | - Carolina Arguelles-Grande
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| | - Sandra Mendoza
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| | - Andre Moreira
- The New York University Langone Health (NYULH) Center of Biospecimen Research and Development, Office of Science and Research, NYU Grossman School of Medicine, 522 First Avenue, SML405, New York, NY, 10016, USA
| |
Collapse
|