Feasibility of incorporating genomic knowledge into electronic medical records for pharmacogenomic clinical decision support

Overby, Casey Lynnette; Tarczy‐Hornoch, Peter; Hoath, James; Kalet, Ira J.; Veenstra, David L.

doi:10.1186/1471-2105-11-s9-s10

Cited by 46 publications

(31 citation statements)

References 15 publications

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“…Simultaneously, many have turned to large human and murine datasets by use of a systems approach to compare transcriptional regulation in humans and mice and in some cases, compare them with clinical outcomes. In this era of big data [20][21][22][23][24], relatively recent projects have focused on a comparison of the transcriptional regulation between mouse and humans. For example, the Mouse ENCODE Consortium mapped transcription, DNase I hypersensitivity, transcription-factor binding, chromatin modifications, and replication domains throughout the mouse genome and compared the results with healthy humans [25].…”

Section: Introductionmentioning

confidence: 99%

The future of murine sepsis and trauma research models

Efron

Mohr

Moore

et al. 2015

Journal of Leukocyte Biology

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Recent comparisons of the murine and human transcriptome in health and disease have called into question the appropriateness of the use of murine models for human sepsis and trauma research. More specifically, researchers have debated the suitability of mouse models of severe inflammation that is intended for eventual translation to human patients. This mini-review outlines this recent research, as well as specifically defines the arguments for and against murine models of sepsis and trauma research based on these transcriptional studies. In addition, we review newer advancements in murine models of infection and injury and define what we envision as an evolving but viable future for murine studies of sepsis and trauma. J. Leukoc. Biol. 98: 945-952;

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Section: Introductionmentioning

confidence: 99%

The future of murine sepsis and trauma research models

Efron

Mohr

Moore

et al. 2015

Journal of Leukocyte Biology

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“…2 The use of alerts within the electronic medical record system when selecting a drug is not a successful strategy because such alerts are ignored in 49% to 96% of cases, 24 and alerts are unlikely to be effective within the time constraints of usual family practice. 25 An alternative to alerts is to build a condition-based MDSS, derived from the clinical guidelines for all conditions, that provides options that are safe and effective for a given patient. 15 We built a system that starts with all the possible options for treatment and results in a list of optimal, individualized drug therapy options.…”

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confidence: 99%

Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

et al. 2016

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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. AbstractResearch Research CMAJ OPENCMAJ OPEN, 4(3) E529fective at changing prescribing decisions, 13 whereas information given within a physician's workflow has been found to be effective in reducing inappropriate orders for imaging. 14 A medication decision support system (MDSS) is a health information technology system that is designed to provide health care professionals with clinical decision support with medication decision-making tasks. These systems assess whether a drug is safe and effective for the patient, taking into account other medications, diseases and the patient's physical state. 15 We have developed a patient-centred MDSS that assesses the potential drug-drug, drug-condition, druggene and drug-drug-gene interactions and produces a list of drug options least likely to cause harm and most likely to be effective.We conducted a study to assess the DNA collection processes, investigate a panel of pharmacogenetic tests relevant to primary care patients and assess the use of an MDSS. The value of the MDSS will be assessed once feasibility of all processes has been shown. MethodsOver an 18-month period before the start of the trial, we developed a pharmacogenetic panel, a pharmacogenetic report and an MDSS for use in primary...

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“…At the level of patient care, integration of genotyping order template and/or genotype result into a robust system of electronic medical record (EMR) with popup action alert and order templates for actionable pharmacogenomic tests to be used by physicians will be necessary [113,114]. At the level of research, the health information technology would enable organizational management of all research data and accessibility by the EMR [115][116][117][118].…”

Section: The Multifacet Process Of Clinicalmentioning

confidence: 99%

Scientific Challenges and Implementation Barriers to Translation of Pharmacogenomics in Clinical Practice

Lam¹

2014

Omics in Clinical Practice

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The mapping of the human genome and subsequent advancements in genetic technology had provided clinicians and scientists an understanding of the genetic basis of altered drug pharmacokinetics and pharmacodynamics, as well as some examples of applying genomic data in clinical practice. This has raised the public expectation that predicting patients' responses to drug therapy is now possible in every therapeutic area, and personalized drug therapy would come sooner than later. However, debate continues among most stakeholders involved in drug development and clinical decision-making on whether pharmacogenomic biomarkers should be used in patient assessment, as well as when and in whom to use the biomarker-based diagnostic tests. Currently, most would agree that achieving the goal of personalized therapy remains years, if not decades, away. Realistic application of genomic findings and technologies in clinical practice and drug development require addressing multiple logistics and challenges that go beyond discovery of gene variants and/or completion of prospective controlled clinical trials. The goal of personalized medicine can only be achieved when all stakeholders in the field work together, with willingness to accept occasional paradigm change in their current approach.

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Feasibility of incorporating genomic knowledge into electronic medical records for pharmacogenomic clinical decision support

Cited by 46 publications

References 15 publications

The future of murine sepsis and trauma research models

The future of murine sepsis and trauma research models

Introducing pharmacogenetic testing with clinical decision support into primary care: a feasibility study

Scientific Challenges and Implementation Barriers to Translation of Pharmacogenomics in Clinical Practice

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