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Chen T, O'Donnell PH, Middlestadt M, Ruhnke GW, Danahey K, van Wijk XMR, Choksi A, Knoebel R, Hartman S, Yeo KTJ, Friedman PN, Ratain MJ, Nutescu EA, O'Leary KJ, Perera MA, Meltzer DO. Implementation of pharmacogenomics into inpatient general medicine. Pharmacogenet Genomics 2023; 33:19-23. [PMID: 36729768 DOI: 10.1097/fpc.0000000000000487] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Pharmacogenomics is a crucial piece of personalized medicine. Preemptive pharmacogenomic testing is only used sparsely in the inpatient setting and there are few models to date for fostering the adoption of pharmacogenomic treatment in the inpatient setting. We created a multi-institutional project in Chicago to enable the translation of pharmacogenomics into inpatient practice. We are reporting our implementation process and barriers we encountered with solutions. This study, 'Implementation of Point-of-Care Pharmacogenomic Decision Support Accounting for Minority Disparities', sought to implement pharmacogenomics into inpatient practice at three sites: The University of Chicago, Northwestern Memorial Hospital, and the University of Illinois at Chicago. This study involved enrolling African American adult patients for preemptive genotyping across a panel of actionable germline variants predicting drug response or toxicity risk. We report our approach to implementation and the barriers we encountered engaging hospitalists and general medical providers in the inpatient pharmacogenomic intervention. Our strategies included: a streamlined delivery system for pharmacogenomic information, attendance at hospital medicine section meetings, use of physician and pharmacist champions, focus on hospitalists' care and optimizing system function to fit their workflow, hand-offs, and dealing with hospitalists turnover. Our work provides insights into strategies for the initial engagement of inpatient general medicine providers that we hope will benefit other institutions seeking to implement pharmacogenomics in the inpatient setting.
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Affiliation(s)
- Thomas Chen
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Peter H O'Donnell
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Merisa Middlestadt
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois, USA
| | - Gregory W Ruhnke
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois, USA
| | | | - Anish Choksi
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | - Randall Knoebel
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | - Seth Hartman
- Department of Pharmacy, The University of Chicago, Chicago, Illinois, USA
| | | | - Paula N Friedman
- Department of Pharmacology, Northwestern University, Chicago, Illinois, USA
| | - Mark J Ratain
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Edith A Nutescu
- Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Kevin J O'Leary
- Department of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Minoli A Perera
- Department of Pharmacology, Northwestern University, Chicago, Illinois, USA
| | - David O Meltzer
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
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2
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Truong TM, Apfelbaum JL, Danahey K, Schierer E, Ludwig J, George D, House L, Karrison T, Shahul S, Anitescu M, Choksi A, Hartman S, Knoebel RW, van Wijk XM, Yeo KTJ, Meltzer D, Ratain MJ, O’Donnell PH. Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial. Anesth Analg 2022; 135:929-940. [PMID: 35213469 PMCID: PMC9402808 DOI: 10.1213/ane.0000000000005951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.
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Affiliation(s)
- Tien M. Truong
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Jeffrey L. Apfelbaum
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Emily Schierer
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Jenna Ludwig
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - David George
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Larry House
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Theodore Karrison
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Sajid Shahul
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Magdalena Anitescu
- Department of Anesthesia and Critical Care, University of Chicago, Chicago, IL, USA
| | - Anish Choksi
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Seth Hartman
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Randall W. Knoebel
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pharmacy, University of Chicago, Chicago, IL, USA
| | - Xander M.R. van Wijk
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - Kiang-Teck J. Yeo
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Department of Pathology, University of Chicago, Chicago, IL, USA
| | - David Meltzer
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Mark J. Ratain
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
| | - Peter H. O’Donnell
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, IL, USA
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3
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Appraisal and development of evidence-based clinical decision support to enable perioperative pharmacogenomic application. THE PHARMACOGENOMICS JOURNAL 2021; 21:691-711. [PMID: 34376788 PMCID: PMC9267777 DOI: 10.1038/s41397-021-00248-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/23/2021] [Revised: 06/06/2021] [Accepted: 06/16/2021] [Indexed: 02/07/2023]
Abstract
Variable responses to medications complicates perioperative care. As a potential solution, we evaluated and synthesized pharmacogenomic evidence that may inform anesthesia and pain prescribing to identify clinically actionable drug/gene pairs. Clinical decision-support (CDS) summaries were developed and were evaluated using Appraisal of Guidelines for Research and Evaluation (AGREE) II. We found that 93/180 (51%) of commonly-used perioperative medications had some published pharmacogenomic information, with 18 having actionable evidence: celecoxib/diclofenac/flurbiprofen/ibuprofen/piroxicam/CYP2C9, codeine/oxycodone/tramadol CYP2D6, desflurane/enflurane/halothane/isoflurane/sevoflurane/succinylcholine/RYR1/CACNA1S, diazepam/CYP2C19, phenytoin/CYP2C9, succinylcholine/mivacurium/BCHE, and morphine/OPRM1. Novel CDS summaries were developed for these 18 medications. AGREE II mean ± standard deviation scores were high for Scope and Purpose (95.0 ± 2.8), Rigor of Development (93.2 ± 2.8), Clarity of Presentation (87.3 ± 3.0), and Applicability (86.5 ± 3.7) (maximum score = 100). Overall mean guideline quality score was 6.7 ± 0.2 (maximum score = 7). All summaries were recommended for clinical implementation. A critical mass of pharmacogenomic evidence exists for select medications commonly used in the perioperative setting, warranting prospective examination for clinical utility.
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4
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Pharmacogenetics of Direct Oral Anticoagulants: A Systematic Review. J Pers Med 2021; 11:jpm11010037. [PMID: 33440670 PMCID: PMC7826504 DOI: 10.3390/jpm11010037] [Citation(s) in RCA: 50] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 12/30/2020] [Accepted: 01/07/2021] [Indexed: 12/11/2022] Open
Abstract
Dabigatran, rivaroxaban, apixaban, edoxaban, and betrixaban are direct oral anticoagulants (DOACs). Their inter-individual variability in pharmacodynamics and pharmacokinetics (transport and metabolism) is high, and could result from genetic polymorphisms. As recommended by the French Network of Pharmacogenetics (RNPGx), the management of some treatments in cardiovascular diseases (as antiplatelet agents, oral vitamin K antagonists, and statins) can rely on genetic testing in order to improve healthcare by reducing therapeutic resistance or toxicity. This paper is a review of association studies between single nucleotide polymorphisms (SNPs) and systemic exposure variation of DOACs. Most of the results presented here have a lot to do with some SNPs of CES1 (rs2244613, rs8192935, and rs71647871) and ABCB1 (rs1128503, rs2032582, rs1045642, and rs4148738) genes, and dabigatran, rivaroxaban, and apixaban. Regarding edoxaban and betrixaban, as well as SNPs in the CYP3A4 and CYP3A5 genes, literature is scarce, and further studies are needed.
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5
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Christian C, Borden BA, Danahey K, Yeo KTJ, van Wijk XM, Ratain MJ, O’Donnell PH. Pharmacogenomic-Based Decision Support to Predict Adherence to Medications. Clin Pharmacol Ther 2020; 108:368-376. [PMID: 32236960 PMCID: PMC7363565 DOI: 10.1002/cpt.1838] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 03/13/2020] [Indexed: 02/03/2023]
Abstract
Poor adherence is associated with worse disease outcomes. Pharmacogenomics provides a possible intervention to address adherence. We hypothesized that pharmacogenomic-informed care could increase adherence. Patients in a prospective case-control study underwent preemptive pharmacogenomic genotyping with results available for provider use at the point of care; controls (not genotyped) were treated by the same providers. Over 6,000 e-prescriptions for 39 medications with actionable pharmacogenomic information were analyzed. Composite adherence, measured by modified proportion of days covered (mPDC), was compared between cases/controls and genomically concordant vs. genomically higher-risk medications. Overall, 536 patients were included. No difference in mean mPDC was observed due to availability of pharmacogenomic guidance. However, case patients prescribed high-risk pharmacogenomic medications were more than twice as likely to have low mPDC for these medications compared with genomically concordant prescriptions (odds ratio = 2.4 (1.03-5.74), P < 0.05). This study is the first to show that composite pharmacogenomic information predicts adherence.
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Affiliation(s)
- Carlton Christian
- The University of Chicago, Pritzker School of Medicine, Chicago, IL, USA
| | - Brittany A. Borden
- The University of Chicago Center for Personalized Therapeutics, Chicago, IL, USA
| | - Keith Danahey
- The University of Chicago Center for Personalized Therapeutics, Chicago, IL, USA
- The University of Chicago Center for Research Informatics, Chicago, IL, USA
| | - Kiang-Teck J. Yeo
- The University of Chicago Center for Personalized Therapeutics, Chicago, IL, USA
- The University of Chicago Department of Pathology, Chicago, IL, USA
- UChicago Advanced Technology Clinical Laboratory, Chicago, IL, USA
- The University of Chicago Committee on Clinical Pharmacology and Pharmacogenomics, Chicago, IL, USA
| | - Xander M.R. van Wijk
- The University of Chicago Department of Pathology, Chicago, IL, USA
- UChicago Advanced Technology Clinical Laboratory, Chicago, IL, USA
| | - Mark J. Ratain
- The University of Chicago Center for Personalized Therapeutics, Chicago, IL, USA
- The University of Chicago Committee on Clinical Pharmacology and Pharmacogenomics, Chicago, IL, USA
- The University of Chicago Department of Medicine, Chicago, IL, USA
| | - Peter H. O’Donnell
- The University of Chicago Center for Personalized Therapeutics, Chicago, IL, USA
- The University of Chicago Committee on Clinical Pharmacology and Pharmacogenomics, Chicago, IL, USA
- The University of Chicago Department of Medicine, Chicago, IL, USA
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6
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Kaye AD, Koress CM, Novitch MB, Jung JW, Urits I, Viswanath O, Renschler JS, Alpaugh ES, Cornett EM. Pharmacogenomics, concepts for the future of perioperative medicine and pain management: A review. Best Pract Res Clin Anaesthesiol 2020; 34:651-662. [PMID: 33004174 DOI: 10.1016/j.bpa.2020.07.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 07/15/2020] [Indexed: 02/07/2023]
Abstract
Pharmacogenomics is the study of how genetic differences between individuals affect pharmacokinetics and pharmacodynamics. These differences are apparent to clinicians when taking into account the wide range of responses to medications given in clinical practice. A review of literature involving pharmacogenomics and pain management was performed. The implementation of preoperative pharmacogenomics will allow us to better care for our patients by delivering personalized, safer medicine. This review describes the current state of pharmacogenomics as it relates to many aspects of clinical practice and how clinicians can use these tools to improve patient outcomes.
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Affiliation(s)
- Alan D Kaye
- Louisiana State University Health Shreveport, Department of Anesthesiology, Shreveport, LA, USA.
| | - Cody M Koress
- Tulane University School of Medicine, Department of Internal Medicine, New Orleans, LA, USA.
| | - Matthew B Novitch
- University of Washington, Department of Anesthesiology, Seattle, WA, USA; Mount Sinai Medical Center, Department of Anesthesiology, Miami Beach, FL, USA.
| | - Jai Won Jung
- Georgetown University School of Medicine, Washington, DC, USA.
| | - Ivan Urits
- Beth Israel Deaconess Medical Center, Department of Anesthesia, Critical Care, and Pain Medicine, Harvard Medical School, Boston, MA, USA.
| | - Omar Viswanath
- Louisiana State University Health Shreveport, Department of Anesthesiology, Shreveport, LA, USA; Valley Pain Consultants - Envision Physician Services, Phoenix, AZ, USA; Creighton University School of Medicine, Department of Anesthesiology, Omaha, NE, USA; University of Arizona College of Medicine-Phoenix, Department of Anesthesiology Phoenix, AZ, USA.
| | | | - Edward S Alpaugh
- Louisiana State University Health Sciences Center, Department of Anesthesiology, Orleans, LA, USA.
| | - Elyse M Cornett
- Louisiana State University Health Shreveport, Department of Anesthesiology, Shreveport, LA, USA.
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7
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Veenstra DL, Mandelblatt J, Neumann P, Basu A, Peterson JF, Ramsey SD. Health Economics Tools and Precision Medicine: Opportunities and Challenges. Forum Health Econ Policy 2020; 23:fhep-2019-0013. [PMID: 32134729 DOI: 10.1515/fhep-2019-0013] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Precision medicine - individualizing care for patients and addressing variations in treatment response - is likely to be important in improving the nation's health in a cost-effective manner. Despite this promise, widespread use of precision medicine, specifically genomic markers, in clinical care has been limited in practice to date. Lack of evidence, clear evidence thresholds, and reimbursement have been cited as major barriers. Health economics frameworks and tools can elucidate the effects of legal, regulatory, and reimbursement policies on the use of precision medicine while guiding research investments to enhance the appropriate use of precision medicine. Despite the capacity of economics to enhance the clinical and human impact of precision medicine, application of health economics to precision medicine has been limited - in part because precision medicine is a relatively new field - but also because precision medicine is complex, both in terms of its applications and implications throughout medicine and the healthcare system. The goals of this review are several-fold: (1) provide an overview of precision medicine and key policy challenges for the field; (2) explain the potential utility of economics methods in addressing these challenges; (3) describe recent research activities; and (4) summarize opportunities for cross-disciplinary research.
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8
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Abstract
The use of pharmacogenetic information is becoming mainstream with insurance companies and others starting to pay for widescale implementation of this new technology starting with patients who have anxiety and depression. It has been introduced in response to the unpredictability of medication, the high number of adverse drug events, and lack of drug effectiveness. Greater than one-third of patients are identified as having one or more pharmacogenetic variants. Each pharmacogenetic variant may affect the metabolism of several medications used in primary care, in addition to the antidepressant and anti-anxiolytic medications. Pharmacogenetic information is evolving with major international working groups providing continuous updates. It is challenging to incorporate this new information along with all the other variables needed to identify safe and effective drug options within a normal consultation. Medication decision support software is one solution that can help address this.
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Affiliation(s)
- Martin Dawes
- Department of Family Practice, The University of British Columbia, Vancouver, British Columbia, Canada
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9
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Loganathan L, Gopinath K, Sankaranarayanan VM, Kukreti R, Rajendran K, Lee JK, Muthusamy K. Computational and Pharmacogenomic Insights on Hypertension Treatment: Rational Drug Design and Optimization Strategies. Curr Drug Targets 2019; 21:18-33. [DOI: 10.2174/1389450120666190808101356] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 07/15/2019] [Accepted: 07/16/2019] [Indexed: 02/07/2023]
Abstract
Background::
Hypertension is a prevalent cardiovascular complication caused by genetic
and nongenetic factors. Blood pressure (BP) management is difficult because most patients become
resistant to monotherapy soon after treatment initiation. Although many antihypertensive drugs are
available, some patients do not respond to multiple drugs. Identification of personalized antihypertensive
treatments is a key for better BP management.
Objective::
This review aimed to elucidate aspects of rational drug design and other methods to develop
better hypertension management.
Results::
Among hypertension-related signaling mechanisms, the renin-angiotensin-aldosterone system
is the leading genetic target for hypertension treatment. Identifying a single drug that acts on multiple
targets is an emerging strategy for hypertension treatment, and could be achieved by discovering new
drug targets with less mutated and highly conserved regions. Extending pharmacogenomics research
to include patients with hypertension receiving multiple antihypertensive drugs could help identify the
genetic markers of hypertension. However, available evidence on the role of pharmacogenomics in
hypertension is limited and primarily focused on candidate genes. Studies on hypertension pharmacogenomics
aim to identify the genetic causes of response variations to antihypertensive drugs. Genetic
association studies have identified single nucleotide polymorphisms affecting drug responses. To understand
how genetic traits alter drug responses, computational screening of mutagenesis can be utilized
to observe drug response variations at the protein level, which can help identify new inhibitors
and drug targets to manage hypertension.
Conclusions::
Rational drug design facilitates the discovery and design of potent inhibitors. However,
further research and clinical validation are required before novel inhibitors can be clinically used as
antihypertensive therapies.
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Affiliation(s)
| | - Krishnasamy Gopinath
- Department of Chemical Engineering, Konkuk University, 1 Hwayang-Dong, Gwangjin-Gu, Seoul, Korea
| | | | - Ritushree Kukreti
- Genomics and Molecular Medicine Unit, Institute of Genomics and Integrative Biology, Council of Scientific and Industrial Research, New Delhi, India
| | - Kannan Rajendran
- Department of General Medicine, Saveetha Medical College and Hospital, Chennai, Tamil Nadu, India
| | - Jung-Kul Lee
- Department of Chemical Engineering, Konkuk University, 1 Hwayang-Dong, Gwangjin-Gu, Seoul, Korea
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Krasi G, Precone V, Paolacci S, Stuppia L, Nodari S, Romeo F, Perrone M, Bushati V, Dautaj A, Bertelli M. Genetics and pharmacogenetics in the diagnosis and therapy of cardiovascular diseases. ACTA BIO-MEDICA : ATENEI PARMENSIS 2019; 90:7-19. [PMID: 31577248 PMCID: PMC7233637 DOI: 10.23750/abm.v90i10-s.8748] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 08/05/2019] [Indexed: 12/20/2022]
Abstract
Cardiovascular diseases are the main cause of death worldwide. The ability to accurately define individual susceptibility to these disorders is therefore of strategic importance. Linkage analysis and genome-wide association studies have been useful for the identification of genes related to cardiovascular diseases. The identification of variants predisposing to cardiovascular diseases contributes to the risk profile and the possibility of tailored preventive or therapeutic strategies. Molecular genetics and pharmacogenetics are playing an increasingly important role in the correct clinical management of patients. For instance, genetic testing can identify variants that influence how patients metabolize medications, making it possible to prescribe personalized, safer and more efficient treatments, reducing medical costs and improving clinical outcomes. In the near future we can expect a great increment in information and genetic testing, which should be acknowledged as a true branch of diagnostics in cardiology, like hemodynamics and electrophysiology. In this review we summarize the genetics and pharmacogenetics of the main cardiovascular diseases, showing the role played by genetic information in the identification of cardiovascular risk factors and in the diagnosis and therapy of these conditions. (www.actabiomedica.it)
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11
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Jhun EH, Apfelbaum JL, Dickerson DM, Shahul S, Knoebel R, Danahey K, Ratain MJ, O’Donnell PH. Pharmacogenomic considerations for medications in the perioperative setting. Pharmacogenomics 2019; 20:813-827. [PMID: 31411557 PMCID: PMC6949515 DOI: 10.2217/pgs-2019-0040] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Accepted: 05/08/2019] [Indexed: 11/21/2022] Open
Abstract
Several high-profile examples of adverse outcomes from medications used in the perioperative setting are well known (e.g., malignant hyperthermia, prolonged apnea, respiratory depression, inadequate analgesia), leading to an increased understanding of genetic susceptibilities underlying these risks. Pharmacogenomic information is increasingly being utilized in certain areas of medicine. Despite this, routine preoperative genetic screening to inform medication risk is not yet standard practice. In this review, we assess the current readiness of pharmacogenomic information for clinical consideration for several common perioperative medications, including description of key pharmacogenes, pharmacokinetic implications and potential clinical outcomes. The goal is to highlight medications for which emerging or considerable pharmacogenomic information exists and identify areas for future potential research.
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Affiliation(s)
- Ellie H Jhun
- Committee on Clinical Pharmacology & Pharmacogenomics, University of Chicago, Chicago, IL, 60637, USA
- Current affiliation: Department of Pharmacogenetics, Base10 Genetics, Chicago, IL 60603, USA
| | - Jeffrey L Apfelbaum
- Department of Anesthesia & Critical Care, University of Chicago, Chicago, IL 60637, USA
| | - David M Dickerson
- Department of Anesthesia & Critical Care, University of Chicago, Chicago, IL 60637, USA
- Current affiliation: Northshore University Health System, Evanston, IL 60201, USA
| | - Sajid Shahul
- Department of Anesthesia & Critical Care, University of Chicago, Chicago, IL 60637, USA
| | - Randall Knoebel
- Department of Pharmacy, University of Chicago Medicine, Chicago, IL 60637, USA
| | - Keith Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL 60637, USA
- Center for Research Informatics, University of Chicago, Chicago, IL 60637, USA
| | - Mark J Ratain
- Committee on Clinical Pharmacology & Pharmacogenomics, University of Chicago, Chicago, IL, 60637, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Peter H O’Donnell
- Committee on Clinical Pharmacology & Pharmacogenomics, University of Chicago, Chicago, IL, 60637, USA
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL 60637, USA
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
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12
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Friedman PN, Shaazuddin M, Gong L, Grossman RL, Harralson AF, Klein TE, Lee NH, Miller DC, Nutescu EA, O'Brien TJ, O'Donnell PH, O'Leary KJ, Tuck M, Meltzer DO, Perera MA. The ACCOuNT Consortium: A Model for the Discovery, Translation, and Implementation of Precision Medicine in African Americans. Clin Transl Sci 2019; 12:209-217. [PMID: 30592548 PMCID: PMC6510376 DOI: 10.1111/cts.12608] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 11/26/2018] [Indexed: 01/06/2023] Open
Abstract
The majority of pharmacogenomic (PGx) studies have been conducted on European ancestry populations, thereby excluding minority populations and impeding the discovery and translation of African American–specific genetic variation into precision medicine. Without accounting for variants found in African Americans, clinical recommendations based solely on genetic biomarkers found in European populations could result in misclassification of drug response in African American patients. To address these challenges, we formed the Transdisciplinary Collaborative Center (TCC), African American Cardiovascular Pharmacogenetic Consortium (ACCOuNT), to discover novel genetic variants in African Americans related to clinically actionable cardiovascular phenotypes and to incorporate African American–specific sequence variations into clinical recommendations at the point of care. The TCC consists of two research projects focused on discovery and translation of genetic findings and four cores that support the projects. In addition, the largest repository of PGx information on African Americans is being established as well as lasting infrastructure that can be utilized to spur continued research in this understudied population.
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Affiliation(s)
- Paula N Friedman
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Mohammed Shaazuddin
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Li Gong
- Department of Biomedical Data Science, Stanford University, Stanford, California, USA
| | - Robert L Grossman
- Department of Medicine and Computer Science, Center for Data Intensive Science, The University of Chicago, Chicago, Illinois, USA
| | - Arthur F Harralson
- Department of Pharmacogenomics, Shenandoah University, Inova Center for Personalized Health, Fairfax, Virginia, USA.,Department of Pharmacology and Physiology, The George Washington University, School of Medicine and Health Sciences, Washington, DC, USA
| | - Teri E Klein
- Department of Biomedical Data Science and Department of Medicine, Stanford University, Stanford, California, USA
| | - Norman H Lee
- Department of Pharmacology and Physiology, The George Washington University, School of Medicine and Health Sciences, Washington, DC, USA
| | - Doriane C Miller
- Department of Medicine, The University of Chicago, Chicago, Illinois, USA
| | - Edith A Nutescu
- Department of Pharmacy Systems, Outcomes, and Policy and Personalized Medicine Program, University of Illinois, College of Pharmacy, Chicago, Illinois, USA
| | - Travis J O'Brien
- Department of Pharmacology and Physiology, The George Washington University, School of Medicine and Health Sciences, Washington, DC, USA
| | - Peter H O'Donnell
- Department of Medicine, Center for Personalized Therapeutics, Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, Illinois, USA
| | - Kevin J O'Leary
- Division of Hospital Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Matthew Tuck
- Washington DC VA Medical Center, Washington, DC and The George Washington University, Washington, DC, USA
| | - David O Meltzer
- Department of Medicine, Center for Health and the Social Sciences, The University of Chicago, Chicago, Illinois, USA
| | - Minoli A Perera
- Department of Pharmacology, Center for Pharmacogenomics, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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13
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Kaye AD, Mahakian T, Kaye AJ, Pham AA, Hart BM, Gennuso S, Cornett EM, Gabriel RA, Urman RD. Pharmacogenomics, precision medicine, and implications for anesthesia care. Best Pract Res Clin Anaesthesiol 2018; 32:61-81. [DOI: 10.1016/j.bpa.2018.07.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2018] [Accepted: 07/30/2018] [Indexed: 01/28/2023]
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14
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Billings J, Racsa PN, Bordenave K, Long CL, Ellis JJ. The impact of real-world cardiovascular-related pharmacogenetic testing in an insured population. Int J Clin Pract 2018; 72:e13088. [PMID: 29767472 DOI: 10.1111/ijcp.13088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Accepted: 03/20/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Pharmacogenomics is intended to help clinicians provide the right drug to the right patient at an appropriate dose. However, limited evidence of clinical utility has slowed uptake of pharmacogenomic testing (PGT). OBJECTIVE To evaluate the impact of real-world cardiovascular (CV)-related PGT on clinical outcomes, healthcare resource utilisation (HCRU) and cost in a large, heterogeneous population. METHODS Individuals with Medicare Advantage Prescription Drug, Medicaid, or commercial coverage between 1/1/2011 and 9/30/2015 and ≥1 atherosclerotic CV-related diagnosis were identified. Those with ≥1 claim for CV-related PGT were included in the test group (index date = 1st PGT claim) and matched 1:2 to controls without PGT. Individuals aged <22 or ≥90 years old on the index date, with <12 months continuous enrollment before and after the index date, or without an ASCVD-related diagnosis in the 12-month pre-index period were excluded. The primary outcome was occurrence of a major CV event during the 12-month post-index period. RESULTS After adjustment, the PGT group was significantly more likely to experience ischaemic stroke, pulmonary embolism, deep vein thrombosis or a composite event compared with controls. Adjusting for baseline characteristics, HCRU was significantly higher for the test group across all measured outcomes except all-cause and ASCVD-related inpatient admissions. Median all-cause and ASCVD-related healthcare costs were significantly higher for the test group. CONCLUSIONS Real world PGT in a large population did not improve outcomes. Tailoring medication therapy to each patient holds great promise for providing quality care but a deeper understanding of how widespread utilisation of PGT might impact objective health outcomes is needed.
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Affiliation(s)
| | - Patrick N Racsa
- Comprehensive Health Insights, Humana Inc., Louisville, KY, USA
| | | | - Charron L Long
- Research and Publications, Humana Inc., Louisville, KY, USA
| | - Jeffrey J Ellis
- Comprehensive Health Insights, Humana Inc., Louisville, KY, USA
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15
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Wellmann R, Borden BA, Danahey K, Nanda R, Polite BN, Stadler WM, Ratain MJ, O'Donnell PH. Analyzing the clinical actionability of germline pharmacogenomic findings in oncology. Cancer 2018; 124:3052-3065. [PMID: 29742281 DOI: 10.1002/cncr.31382] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 03/07/2018] [Accepted: 03/09/2018] [Indexed: 01/19/2023]
Abstract
BACKGROUND Germline and tumor pharmacogenomics impact drug responses, but germline markers less commonly guide oncology prescribing. The authors hypothesized that a critical number of clinically actionable germline pharmacogenomic associations exist, representing clinical implementation opportunities. METHODS In total, 125 oncology drugs were analyzed for positive germline pharmacogenomic associations in journals with impact factors ≥5. Studies were assessed for design and genotyping quality, clinically relevant outcomes, statistical rigor, and evidence of drug-gene effects. Associations from studies of high methodologic quality were deemed potentially clinically actionable, and translational summaries were written as point-of-care clinical decision support (CDS) tools and formally evaluated using the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument. RESULTS The authors identified germline pharmacogenomic results for 56 of 125 oncology drugs (45%) across 173 publications. Actionable associations were detected for 12 drugs, including 6 that had germline pharmacogenomic information within US Food and Drug Administration labels or published guidelines (capecitabine/fluorouracil/dihydropyrimidine dehydrogenase [DPYD], irinotecan/uridine diphosphate glucuronosyltransferase family 1 member A1 [UGT1A1], mercaptopurine/thioguanine/thiopurine S-methyltransferase [TPMT], tamoxifen/cytochrome P450 [CYP] family 2 subfamily D member 6 [CYP2D6]), and 6 others were novel (asparaginase/nuclear factor of activated T-cells 2 [NFATC2]/human leukocyte antigen D-related β1 [HLA-DRB1], cisplatin/acylphosphatase 2 [ACYP2], doxorubicin/adenosine triphosphate-binding cassette subfamily C member 2/Rac family small guanosine triphosphatase 2/neutrophil cytosolic factor 4 [ABCC2/RAC2/NCF4], lapatinib/human leukocyte antigen DQ α1 [HLA-DQA1], sunitinib/cytochrome P450 family 3 subfamily A member 5 [CYP3A5], vincristine/centrosomal protein 72 [CEP72]). By using AGREE II, the developed CDS summaries had high mean ± standard deviation scores (maximum score, 100) for scope and purpose (92.7 ± 5.1) and rigour of development (87.6 ± 7.4) and moderate yet robust scores for clarity of presentation (58.6 ± 25.1) and applicability (55.9 ± 24.6). The overall mean guideline quality score was 5.2 ± 1.0 (maximum score, 7). Germline pharmacogenomic CDS summaries for these 12 drugs were recommended for implementation. CONCLUSIONS Several oncology drugs have actionable germline pharmacogenomic information, justifying their delivery through institutional pharmacogenomic implementations to determine clinical utility. Cancer 2018;124:3052-65. © 2018 American Cancer Society.
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Affiliation(s)
- Rebecca Wellmann
- Pritzker School of Medicine, The University of Chicago, Chicago, Illinois
| | - Brittany A Borden
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Center for Research Informatics, The University of Chicago, Chicago, Illinois
| | - Rita Nanda
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Department of Medicine, The University of Chicago, Chicago, Illinois
| | - Blase N Polite
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Department of Medicine, The University of Chicago, Chicago, Illinois
| | - Walter M Stadler
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Department of Medicine, The University of Chicago, Chicago, Illinois
| | - Mark J Ratain
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Department of Medicine, The University of Chicago, Chicago, Illinois.,Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, Illinois
| | - Peter H O'Donnell
- Center for Personalized Therapeutics, The University of Chicago, Chicago, Illinois.,Department of Medicine, The University of Chicago, Chicago, Illinois.,Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, Illinois
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16
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Haga SB. Integrating pharmacogenetic testing into primary care. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2017; 2:327-336. [PMID: 31853504 DOI: 10.1080/23808993.2017.1398046] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction Pharmacogenetic (PGx) testing has greatly expanded due to enhanced understanding of the role of genes in drug response and advances in DNA-based testing technology development. As many primary care visits result in a prescription, the use of PGx testing may be particularly beneficial in this setting. However, integration of PGx testing may be limited as no uniform approach to delivery of tests has been established and providers are ill-prepared to integrate PGx testing into routine care. Areas covered In this paper, the readiness of primary care practitioners are reviewed as well as strategies to address these barriers based on published research and ongoing activities on education and implementation of PGx testing. Expert Commentary Widespread integration of PGx testing will warrant continued education and point-of-care decisional support. Primary care providers may also benefit from consultation services or team-based care with laboratory medicine specialists, pharmacists, and genetic counselors.
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Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA,
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17
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O’Donnell PH, Wadhwa N, Danahey K, Borden BA, Lee SM, Hall JP, Klammer C, Hussain S, Siegler M, Sorrentino MJ, Davis AM, Sacro YA, Nanda R, Polonsky TS, Koyner JL, Burnet DL, Lipstreuer K, Rubin DT, Mulcahy C, Strek ME, Harper W, Cifu AS, Polite B, Patrick-Miller L, Yeo KTJ, Leung EKY, Volchenboum SL, Altman RB, Olopade OI, Stadler WM, Meltzer DO, Ratain MJ. Pharmacogenomics-Based Point-of-Care Clinical Decision Support Significantly Alters Drug Prescribing. Clin Pharmacol Ther 2017; 102:859-869. [PMID: 28398598 PMCID: PMC5636653 DOI: 10.1002/cpt.709] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2017] [Revised: 03/31/2017] [Accepted: 04/05/2017] [Indexed: 12/22/2022]
Abstract
Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green = genomically favorable, yellow = genomic caution, red = high risk. The influence of pharmacogenomic alerts on prescribing behaviors was the primary endpoint. In all, 2,279 outpatient encounters were analyzed. Independent of other potential prescribing mediators, medications with high pharmacogenomic risk were changed significantly more often than prescription drugs lacking pharmacogenomic information (odds ratio (OR) = 26.2 (9.0-75.3), P < 0.0001). Medications with cautionary pharmacogenomic information were also changed more frequently (OR = 2.4 (1.7-3.5), P < 0.0001). No pharmacogenomically high-risk medications were prescribed during the entire study when physicians consulted the CDS tool. Pharmacogenomic information improved prescribing in patterns aimed at reducing patient risk, demonstrating that enhanced prescription decision-making is achievable through clinical integration of genomic medicine.
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Affiliation(s)
- Peter H. O’Donnell
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
| | - Nisha Wadhwa
- Pritzker School of Medicine, The University of Chicago, Chicago, IL, U.S.A
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Center for Research Informatics, The University of Chicago, Chicago, IL, U.S.A
| | - Brittany A. Borden
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Sang Mee Lee
- Department of Health Sciences, The University of Chicago, Chicago, IL, U.S.A
| | - Julianne P. Hall
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Catherine Klammer
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Sheena Hussain
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Mark Siegler
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
- MacLean Center for Clinical Medical Ethics, The University of Chicago, Chicago, IL, U.S.A
| | - Matthew J. Sorrentino
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Andrew M. Davis
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Yasmin A. Sacro
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Rita Nanda
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Tamar S. Polonsky
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Jay L. Koyner
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Deborah L. Burnet
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Kristen Lipstreuer
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - David T. Rubin
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Cathleen Mulcahy
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Mary E. Strek
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
| | - William Harper
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Adam S. Cifu
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Blase Polite
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - Linda Patrick-Miller
- Center for Clinical Cancer Genetics, The University of Chicago, Chicago, IL, U.S.A
| | - Kiang-Teck J. Yeo
- Department of Pathology, The University of Chicago, Chicago, IL, U.S.A
| | | | | | - Russ B. Altman
- Departments of Bioengineering, Genetics, and Medicine, Stanford University, Palo Alto, CA, U.S.A
| | | | - Walter M. Stadler
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
| | - David O. Meltzer
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Health and the Social Sciences, The University of Chicago, Chicago, IL, U.S.A
| | - Mark J. Ratain
- Department of Medicine, The University of Chicago, Chicago, IL, U.S.A
- Center for Personalized Therapeutics, The University of Chicago, Chicago, IL, U.S.A
- Committee on Clinical Pharmacology and Pharmacogenomics, The University of Chicago, Chicago, IL, U.S.A
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Danahey K, Borden BA, Furner B, Yukman P, Hussain S, Saner D, Volchenboum SL, Ratain MJ, O'Donnell PH. Simplifying the use of pharmacogenomics in clinical practice: Building the genomic prescribing system. J Biomed Inform 2017; 75:110-121. [PMID: 28963061 DOI: 10.1016/j.jbi.2017.09.012] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2016] [Revised: 09/21/2017] [Accepted: 09/25/2017] [Indexed: 11/17/2022]
Abstract
BACKGROUND A barrier to the use of genomic information during prescribing is the limited number of software solutions that combine a user-friendly interface with complex medical data. We built and designed an online, secure, electronic custom interface termed the Genomic Prescribing System (GPS). METHODS Actionable pharmacogenomic (PGx) information was reviewed, collected, and stored in the back-end of GPS to enable creation of customized drug- and variant-specific clinical decision support (CDS) summaries. The database architecture utilized the star schema to store information. Patient raw genomic data underwent transformation via custom-designed algorithms to enable gene and phenotype-level associations. Multiple external data sets (PubMed, The Systematized Nomenclature of Medicine (SNOMED), National Drug File - Reference Terminology (ND-FRT), and a publically-available PGx knowledgebase) were integrated to facilitate the delivery of patient, drug, disease, and genomic information. Institutional security infrastructure was leveraged to securely store patient genomic and clinical data on a HIPAA-compliant server farm. RESULTS As of May 17, 2016, the GPS back-end housed 257 CDS encompassing 112 genetic variants, 42 genes, and 46 PGx-actionable drugs. The GPS user interface presented patient-specific CDS alongside a recognizable traffic light symbol (green/yellow/red), denoting PGx risk for each genomic result. The number of traffic lights per visit increased with the corresponding increase in the number of available PGx-annotated drugs over time. An integrated drug and disease search functionality, links to primary literature sources, and potential alternative PGx drugs were indicated. The system, which was initially used as stand-alone CDS software within our clinical environment, was then integrated with the institutional electronic medical record for enhanced usability. There have been nearly 2000 logins in 43months since inception, with usage exceeding 56 logins per month and system up-times of 99.99%. For all patient-provider visits encompassing >3years of implementation, unique alert click-through rates corresponded to genomic risk: red lights clicked 100%, yellow lights 79%, green lights 43%. CONCLUSIONS Successful deployment of GPS by combining complex data and recognizable iconography led to a tool that enabled point-of-care genomic delivery with high usability. Continued scalability and incorporation of additional clinical elements to be considered alongside PGx information could expand future impact.
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Affiliation(s)
- Keith Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA; Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Brittany A Borden
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Brian Furner
- Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Patrick Yukman
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA; Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Sheena Hussain
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA
| | - Donald Saner
- Center for Research Informatics, University of Chicago, Chicago, IL, USA
| | - Samuel L Volchenboum
- Center for Research Informatics, University of Chicago, Chicago, IL, USA; Department of Pediatrics, University of Chicago, Chicago, IL, USA
| | - Mark J Ratain
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA; Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Peter H O'Donnell
- Center for Personalized Therapeutics, University of Chicago, Chicago, IL, USA; Department of Medicine, University of Chicago, Chicago, IL, USA.
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19
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Dhanda DS, Guzauskas GF, Carlson JJ, Basu A, Veenstra DL. Are Evidence Standards Different for Genomic- vs. Clinical-Based Precision Medicine? A Quantitative Analysis of Individualized Warfarin Therapy. Clin Pharmacol Ther 2017; 102:805-814. [PMID: 28187492 DOI: 10.1002/cpt.663] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2016] [Revised: 01/23/2017] [Accepted: 02/03/2017] [Indexed: 02/06/2023]
Abstract
Evidence requirements for implementation of precision medicine (PM), whether informed by genomic or clinical data, are not well defined. Evidence requirements are driven by uncertainty and its attendant consequences; these aspects can be quantified by a novel technique in health economics: value of information analysis (VOI). We utilized VOI analysis to compare the evidence levels over time for warfarin dosing based on pharmacogenomic vs. amiodarone-warfarin drug-drug interaction information. The primary outcome was the expected value of perfect information (EVPI), which is an estimate of the upper limit of the societal value of conducting future research. Over the past decade, the EVPI for the pharmacogenomic strategy decreased from $1,550 to $140 vs. $1,220 to $280 per patient for the drug-interaction strategy. Evidence levels thus appear to be higher for pharmacogenomic-guided vs. drug-interaction-guided warfarin dosing. Clinical guidelines and reimbursement policies for warfarin PM could be informed by these findings.
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Affiliation(s)
- D S Dhanda
- Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, Washington, USA
| | - G F Guzauskas
- Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, Washington, USA
| | - J J Carlson
- Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, Washington, USA
| | - A Basu
- Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, Washington, USA
| | - D L Veenstra
- Pharmaceutical Outcomes Research and Policy Program, Department of Pharmacy, University of Washington, Seattle, Washington, USA
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20
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Agarwal D, Udoji MA, Trescot A. Genetic Testing for Opioid Pain Management: A Primer. Pain Ther 2017; 6:93-105. [PMID: 28409480 PMCID: PMC5447546 DOI: 10.1007/s40122-017-0069-2] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2017] [Indexed: 01/01/2023] Open
Abstract
Patients see their primary care physicians (PCPs) for a variety of medical conditions, chronic pain being one of the most common. An increased use of prescription medications (especially opioids) has led to an increase in adverse drug reactions and has heightened our awareness of the variability in response to medications. Opioids and other pain adjuvants are widely used, and drug-drug interactions involving these analgesics can be problematic and potentially lethal. Pharmacogenetics has improved our understanding of drug efficacy and response, opened doors to individual tailoring of medical management, and created a series of ethical and economic considerations. Since it is a relatively new field, genetic testing has not been fully integrated into the primary care setting. The purpose of this paper is to review the metabolism of commonly prescribed opioids, discuss the economic and ethical issues, and provide PCPs with an understanding of how to incorporate genetic testing into routine use to improve clinical practice and patient management.
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Affiliation(s)
- Deepti Agarwal
- Department of Anesthesiology, Advocate Illinois Masonic Medical Center, Chicago, IL, USA
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21
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Cabrera M, Finkelstein J. A Use Case to Support Precision Medicine for Frequently Hospitalized Older Adults with Polypharmacy. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE PROCEEDINGS. AMIA JOINT SUMMITS ON TRANSLATIONAL SCIENCE 2016; 2016:16-21. [PMID: 27570642 PMCID: PMC5001756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Polypharmacy in older adults results in multiple negative clinical consequences including increased risk of hospital readmissions. Precision medicine may provide tools to optimize complex medication regimens however its potential in older adults with polypharmacy is unknown. We carried out pharmacogenetic testing in an older adult with multiple chronic conditions and polypharmacy who was concerned about frequent readmissions despite receiving guideline-concordant care and being adherent to medication regimen. The testing identified patients' CYP2D6 rapid metabolizer status. This may have resulted in decreased exposure to Carvedilol which was primary drug for CHF management in this patient. Additional nine drug-drug interactions were identified during personalized drug regimen review. We concluded that, though precision medicine has enormous potential in older adults with polypharmacy, the complexity of pharmacogenetic information requires innovative informatics solutions to support optimal workflows, decision support, and medication optimization and management in order to fully utilize its potential in routine clinical care.
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22
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Dawes M, Aloise MN, Ang JS, Cullis P, Dawes D, Fraser R, Liknaitzky G, Paterson A, Stanley P, Suarez-Gonzalez A, Katzov-Eckert H. Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study. CMAJ Open 2016; 4:E528-E534. [PMID: 27730116 PMCID: PMC5047800 DOI: 10.9778/cmajo.20150070] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Inappropriate prescribing increases patient illness and death owing to adverse drug events. The inclusion of genetic information into primary care medication practices is one solution. Our aim was to assess the ability to obtain and genotype saliva samples and to determine the levels of use of a decision support tool that creates medication options adjusted for patient characteristics, drug-drug interactions and pharmacogenetics. METHODS We conducted a cohort study in 6 primary care settings (5 family practices and 1 pharmacy), enrolling 191 adults with at least 1 of 10 common diseases. Saliva samples were obtained in the physician's office or pharmacy and sent to our laboratory, where DNA was extracted and genotyped and reports were generated. The reports were sent directly to the family physician/pharmacist and linked to an evidence-based prescribing decision support system. The primary outcome was ability to obtain and genotype samples. The secondary outcomes were yield and purity of DNA samples, ability to link results to decision support software and use of the decision support software. RESULTS Genotyping resulted in linking of 189 patients (99%) with pharmacogenetic reports to the decision support program. A total of 96.8% of samples had at least 1 actionable genotype for medications included in the decision support system. The medication support system was used by the physicians and pharmacists 236 times over 3 months. INTERPRETATION Physicians and pharmacists can collect saliva samples of sufficient quantity and quality for DNA extraction, purification and genotyping. A clinical decision support system with integrated data from pharmacogenetic tests may enable personalized prescribing within primary care. Trial registration: ClinicalTrials.gov, NCT02383290.
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Affiliation(s)
- Martin Dawes
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Martin N Aloise
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - J Sidney Ang
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Pieter Cullis
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Diana Dawes
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Robert Fraser
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Gideon Liknaitzky
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Andrea Paterson
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Paul Stanley
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Adriana Suarez-Gonzalez
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
| | - Hagit Katzov-Eckert
- Department of Family Practice (M. Dawes); GenXys Health Care Systems (M. Dawes, Aloise, Ang, Cullis, D. Dawes, Fraser, Liknaitzky, Stanley, Suarez-Gonzalez, Katzov-Eckert); Personalized Medicine Initiative (Cullis, Fraser); Department of Physical Therapy (D. Dawes); Faculty of Pharmaceutical Sciences (Paterson); Clinicare Pharmacists Inc. (Paterson); Department of Botany (Suarez-Gonzalez); Department of Biochemistry and Molecular Biology (Cullis), University of British Columbia, Vancouver, BC
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23
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Abstract
The cardiovascular research and clinical communities are ideally positioned to address the epidemic of noncommunicable causes of death, as well as advance our understanding of human health and disease, through the development and implementation of precision medicine. New tools will be needed for describing the cardiovascular health status of individuals and populations, including 'omic' data, exposome and social determinants of health, the microbiome, behaviours and motivations, patient-generated data, and the array of data in electronic medical records. Cardiovascular specialists can build on their experience and use precision medicine to facilitate discovery science and improve the efficiency of clinical research, with the goal of providing more precise information to improve the health of individuals and populations. Overcoming the barriers to implementing precision medicine will require addressing a range of technical and sociopolitical issues. Health care under precision medicine will become a more integrated, dynamic system, in which patients are no longer a passive entity on whom measurements are made, but instead are central stakeholders who contribute data and participate actively in shared decision-making. Many traditionally defined diseases have common mechanisms; therefore, elimination of a siloed approach to medicine will ultimately pave the path to the creation of a universal precision medicine environment.
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Affiliation(s)
- Elliott M Antman
- Brigham and Women's Hospital, TIMI Study Group, 350 Longwood Avenue, Office Level One, Boston, Massachusetts 02115, USA
| | - Joseph Loscalzo
- Department of Medicine, Brigham and Women's Hospital, 75 Francis Street, Boston, Massachusetts 02115, USA
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24
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Sorrentino MJ, O'Donnell PH. Pharmacogenomics and cardiology: improving treatment with existing drugs. Pharmacogenomics 2016; 16:1223-6. [PMID: 26369612 DOI: 10.2217/pgs.15.110] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Matthew J Sorrentino
- Department of Medicine, Center for Personalized Therapeutics & Committee on Clinical Pharmacology & Pharmacogenomics, The University of Chicago, USA.,The University of Chicago Medicine, 5841 S. Maryland Avenue, Chicago, IL 60637, USA
| | - Peter H O'Donnell
- Department of Medicine, Center for Personalized Therapeutics & Committee on Clinical Pharmacology & Pharmacogenomics, The University of Chicago, USA.,The University of Chicago Medicine, 5841 S. Maryland Avenue, Chicago, IL 60637, USA
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25
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Payne DA, Baluchova K, Peoc'h KH, van Schaik RHN, Chan KCA, Maekawa M, Mamotte C, Russomando G, Rousseau F, Ahmad-Nejad P. Pre-examination factors affecting molecular diagnostic test results and interpretation: A case-based approach. Clin Chim Acta 2016; 467:59-69. [PMID: 27321365 DOI: 10.1016/j.cca.2016.06.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2015] [Revised: 06/13/2016] [Accepted: 06/15/2016] [Indexed: 12/13/2022]
Abstract
BACKGROUND Multiple organizations produce guidance documents that provide opportunities to harmonize quality practices for diagnostic testing. The International Organization for Standardization ISO 15189 standard addresses requirements for quality in management and technical aspects of the clinical laboratory. One technical aspect addresses the complexities of the pre-examination phase prior to diagnostic testing. METHODS The Committee for Molecular Diagnostics of the International Federation for Clinical Chemistry and Laboratory Medicine (also known as, IFCC C-MD) conducted a survey of international molecular laboratories and determined ISO 15189 to be the most referenced guidance document. In this review, the IFCC C-MD provides case-based examples illustrating the value of select pre-examination processes as these processes relate to molecular diagnostic testing. Case-based examples in infectious disease, oncology, inherited disease and pharmacogenomics address the utility of: 1) providing information to patients and users, 2) designing requisition forms, 3) obtaining informed consent and 4) maintaining sample integrity prior to testing. CONCLUSIONS The pre-examination phase requires extensive and consistent communication between the laboratory, the healthcare provider and the end user. The clinical vignettes presented in this paper illustrate the value of applying select ISO 15189 recommendations for general laboratory to the more specialized area of Molecular Diagnostics.
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Affiliation(s)
- Deborah A Payne
- Molecular Services, APP-UniPath LLC, American Pathology Partners-UniPath, 6116 East Warren Ave., Denver, CO, USA.
| | - Katarina Baluchova
- Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin, Biomedical Center Martin, Division of Oncology, Mala Hora 4C, 036 01 Martin, Slovakia; Comenius University in Bratislava, Jessenius Faculty of Medicine in Martin, Department of Molecular Biology, Mala Hora 4C, 036 01 Martin, Slovakia
| | - Katell H Peoc'h
- AP-HP Hôpital Beaujon, Service de Biochimie clinique, Clichy F-92118, France; Université Paris Diderot, UFR de Médecine site Bichat, INSERM UMRs-1149, Paris, France
| | - Ron H N van Schaik
- Department Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - K C Allen Chan
- Department of Chemical Pathology, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
| | - Masato Maekawa
- Department of Laboratory Medicine, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Cyril Mamotte
- School of Biomedical Sciences and CHIRI Biosciences, Curtin University, Perth, Australia
| | - Graciela Russomando
- Molecular Biology and Biotechnology Department, Instituto de Investigaciones en Ciencias de la Salud, Universidad Nacional de Asunción, Paraguay
| | - François Rousseau
- Department of Medical Biology, Direction médicale des services hospitaliers, CHU de Québec - Université Laval, Québec City, Canada; Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Université Laval, Québec City, Canada
| | - Parviz Ahmad-Nejad
- Institute for Medical Laboratory Diagnostics, Centre for Clinical and Translational Research (CCTR), HELIOS Hospital, Heusnerstraße 40, 42283 Wuppertal, Witten/Herdecke University, Germany
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26
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Hussain S, Kenigsberg BB, Danahey K, Lee YM, Galecki PM, Ratain MJ, O'Donnell PH. Disease-drug database for pharmacogenomic-based prescribing. Clin Pharmacol Ther 2016; 100:179-90. [PMID: 26940584 DOI: 10.1002/cpt.364] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2015] [Revised: 02/04/2016] [Accepted: 02/28/2016] [Indexed: 01/04/2023]
Abstract
Providers have expressed a strong desire to have additional clinical decision-support tools to help with interpretation of pharmacogenomic results. We developed and tested a novel disease-drug association tool that enables pharmacogenomic-based prescribing to treat common diseases. First, 324 drugs were mapped to 484 distinct diseases (mean number of drugs treating each disease was 4.9; range 1-37). Then the disease-drug association tool was pharmacogenomically annotated, with an average of 1.8 pharmacogenomically annotated drugs associated/disease. Applying this tool to a prospectively enrolled >1,000 patient cohort from a tertiary medical center showed that 90% of the top ∼20 diseases in this population and ≥93% of patients could appropriately be treated with ≥1 medication with actionable pharmacogenomic information. When combined with clinical patient genotypes, this tool permits delivery of patient-specific pharmacogenomically informed disease treatment recommendations to inform the treatment of many medical conditions of the US population, a key initial step towards implementation of precision medicine.
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Affiliation(s)
- S Hussain
- Center for Personalized Therapeutics, University of Chicago, Chicago, Illinois, USA
| | - B B Kenigsberg
- Internal Medicine Residency Program, University of Chicago Medical Center, Chicago, Illinois, USA
| | - K Danahey
- Center for Personalized Therapeutics, University of Chicago, Chicago, Illinois, USA.,Center for Research Informatics, University of Chicago, Chicago, Illinois, USA
| | - Y M Lee
- Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, Illinois, USA
| | - P M Galecki
- Center for Personalized Therapeutics, University of Chicago, Chicago, Illinois, USA
| | - M J Ratain
- Center for Personalized Therapeutics, University of Chicago, Chicago, Illinois, USA.,Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, Illinois, USA.,Department of Medicine, University of Chicago, Chicago, Illinois, USA
| | - P H O'Donnell
- Center for Personalized Therapeutics, University of Chicago, Chicago, Illinois, USA.,Committee on Clinical Pharmacology and Pharmacogenomics, University of Chicago, Chicago, Illinois, USA.,Department of Medicine, University of Chicago, Chicago, Illinois, USA
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27
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Finkelstein J, Friedman C, Hripcsak G, Cabrera M. Potential utility of precision medicine for older adults with polypharmacy: a case series study. Pharmgenomics Pers Med 2016; 9:31-45. [PMID: 27143951 PMCID: PMC4846041 DOI: 10.2147/pgpm.s101474] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Pharmacogenomic (PGx) testing has been increasingly used to optimize drug regimens; however, its potential in older adults with polypharmacy has not been systematically studied. In this hypothesis-generating study, we employed a case series design to explore potential utility of PGx testing in older adults with polypharmacy and to highlight barriers in implementing this methodology in routine clinical practice. Three patients with concurrent chronic heart and lung disease aged 74, 78, and 83 years and whose medication regimen comprised 26, 17, and 18 drugs, correspondingly, served as cases for this study. PGx testing identified major genetic polymorphisms in the first two cases. The first case was identified as "CYP3A4/CYP3A5 poor metabolizer", which affected metabolism of eleven prescribed drugs. The second case had "CYP2D6 rapid metabolizer" status affecting three prescribed medications, two of which were key drugs for managing this patient's chronic conditions. Both these patients also had VKORC1 allele *A, resulting in higher sensitivity to warfarin. All cases demonstrated a significant number of potential drug-drug interactions. Both patients with significant drug-gene interactions had a history of frequent hospitalizations (six and 23, respectively), whereas the person without impaired cytochrome P450 enzyme activity had only two acute episodes in the last 5 years, although he was older and had multiple comorbidities. Since all patients received guideline-concordant therapy from the same providers and were adherent to their drug regimen, we hypothesized that genetic polymorphism may represent an additional risk factor for higher hospitalization rates in older adults with polypharmacy. However, evidence to support or reject this hypothesis is yet to be established. Studies evaluating clinical impact of PGx testing in older adults with polypharmacy are warranted. For practical implementation of pharmacogenomics in routine clinical care, besides providing convincing evidence of its clinical effectiveness, multiple barriers must be addressed. Introduction of intelligent clinical decision support in electronic medical record systems is required to address complexities of simultaneous drug-gene and drug-drug interactions in older adults with polypharmacy. Physician training, clear clinical pathways, evidence-based guidelines, and patient education materials are necessary for unlocking full potential of pharmacogenomics into routine clinical care of older adults.
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Affiliation(s)
- Joseph Finkelstein
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Carol Friedman
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University, New York, NY, USA
| | - Manuel Cabrera
- Department of Medicine, Columbia University, New York, NY, USA
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28
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O’Donnell PH, Danahey K, Ratain MJ. The Outlier in All of Us: Why Implementing Pharmacogenomics Could Matter for Everyone. Clin Pharmacol Ther 2016; 99:401-4. [PMID: 26756170 PMCID: PMC4830348 DOI: 10.1002/cpt.333] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2015] [Revised: 01/04/2016] [Accepted: 01/05/2016] [Indexed: 01/11/2023]
Abstract
The field of pharmacogenomics originally emerged in the 1950s from observations that a few rare individuals had unexpected, severe reactions to drugs. As recently as just 6 years ago, prominent views on the subject had largely remained unchanged, with authors from the US Food and Drug Administration (FDA) citing the purpose of pharmacogenetics as "tailoring treatment for the outliers." It should not be surprising if this is the prevailing view--the best-studied pharmacogenomic drug examples are indeed just that, genetic explanations of extreme responses or susceptibilities among usually a very small fraction of the human population. Thiopurine methyltransferase (TPMT) deficiency as a cause of severe myelosuppression upon treatment with azathioprine or mercaptopurine is found as a heterozygous trait in only ∼ 10% of patients, and homozygous (deficiency) carriers are even more rare--occurring in fewer than 1 in 300 patients. Malignant hyperthermia resulting from inhaled anesthetics and succinylcholine is believed to have a genetic incidence of only about 1 in 2000 people.
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Affiliation(s)
- Peter H. O’Donnell
- Center for Personalized Therapeutics, The University of Chicago,
Chicago, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, The
University of Chicago, Chicago, USA
- Department of Medicine, The University of Chicago, Chicago,
USA
| | - Keith Danahey
- Center for Personalized Therapeutics, The University of Chicago,
Chicago, USA
- Center for Research Informatics, The University of Chicago, Chicago,
USA
| | - Mark J. Ratain
- Center for Personalized Therapeutics, The University of Chicago,
Chicago, USA
- Committee on Clinical Pharmacology and Pharmacogenomics, The
University of Chicago, Chicago, USA
- Department of Medicine, The University of Chicago, Chicago,
USA
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29
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Pereira NL, Stewart AK. Clinical Implementation of Cardiovascular Pharmacogenomics. Mayo Clin Proc 2015; 90:701-4. [PMID: 26046404 DOI: 10.1016/j.mayocp.2015.04.011] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2015] [Accepted: 04/23/2015] [Indexed: 11/26/2022]
Affiliation(s)
- Naveen L Pereira
- Division of Cardiovascular Diseases, Division of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN.
| | - A Keith Stewart
- Center for Individualized Medicine, Division of Hematology/Oncology, Mayo Clinic, Rochester, MN
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