Antidepressants are commonly prescribed medications in the United States, and there is increasing interest in individualizing treatment selection for more than 20 US Food and Drug ...Administration-approved treatments for major depressive disorder. Providing greater precision to pharmacotherapeutic recommendations for individual patients beyond the large-scale clinical trials evidence base can potentially reduce adverse effect toxicity profiles and increase response rates and overall effectiveness. It is increasingly recognized that genetic variation may contribute to this differential risk to benefit ratio and thus provides a unique opportunity to develop pharmacogenetic guidelines for psychiatry. Key studies and concepts that review the rationale for cytochrome P450 2D6 (CYP2D6) and cytochrome P450 2C19 (CYP2C19) genetic testing can be delineated by serum levels, adverse events, and clinical outcome measures (eg, antidepressant response). In this article, we report the evidence that contributed to the implementation of pharmacokinetic pharmacogenetic guidelines for antidepressants primarily metabolized by CYP2D6 and CYP2C19.
A number of barriers exist for adoption of pharmacogenomics into practice. Physicians, pharmacists, and nurses report limited knowledge about pharmacogenomics and its use in patient care. Lack of ...pharmacogenomics education curricula as part of professional schools or postgraduate training programs has been reported as a potential cause. Understanding pharmacogenomics is further complicated by a complex and nonstandard lexicon, limited medication guidelines, rapidly changing evidence, and insufficient awareness of test availability and utility.
Abstract Background Limited information is available regarding primary care clinicians’ response to pharmacogenomic Clinical Decision Support (PGx-CDS) alerts integrated in the electronic health ...record. Methods In February 2015, 159 clinicians in the Mayo Clinic primary care practice were sent e-mail surveys to understand their perspectives on the implementation and use of pharmacogenomic testing in their clinical practice. Surveys assessed how the clinicians felt about pharmacogenomics and whether they thought electronic PGx-CDS alerts were useful. Information was abstracted on the number of CDS alerts the clinicians received between October, 2013 and the date their survey was returned. CDS alerts were grouped into two categories: alert recommended caution using the prescription or the alert recommended an alternate prescription. Finally, data were abstracted regarding whether the clinician changed their prescription in response to the alert recommendation. Results The survey response rate was 57% (n=90). Overall, 52% of the clinicians did not expect to use or did not know whether they would use pharmacogenomic information in their future prescribing practices. Additionally, 53% of the clinicians felt that the alerts were confusing, irritating, frustrating, or that it was difficult to find additional information. Finally, only 30% of the clinicians that received a CDS alert changed their prescription to an alternative medication. Conclusions Our results suggest a lack of clinician comfort with integration of pharmacogenomic data into primary care. Further efforts to refine PGx-CDS alerts to make them as useful and user-friendly as possible are needed to improve clinician satisfaction with these new tools.
To examine predictors of understanding preemptive CYP2D6 pharmacogenomics test results and to identify key features required to improve future educational efforts of preemptive pharmacogenomics ...testing.
One thousand ten participants were surveyed after receiving preemptive CYP2D6 pharmacogenomics test results.
Eighty-six percent (n = 869) of patients responded. Of the responders, 98% were white and 55% were female; 57% had 4 years or more of post-secondary education and an average age of 58.9 ± 5.5 years. Twenty-six percent said that they only somewhat understood their results and 7% reported they did not understand them at all. Only education predicted understanding. The most common suggestion for improvement was the use of layperson's terms when reporting results. In addition, responders suggested that results should be personalized by referring to medications that they were currently using. Of those reporting imperfect drug adherence, most (91%) reported they would be more likely to use medication as prescribed if pharmacogenomic information was used to help select the drug or dose.
Despite great efforts to simplify pharmacogenomic results (or because of them), approximately one-third of responders did not understand their results. Future efforts need to provide more examples and tailor results to the individual. Incorporation of pharmacogenomics is likely to improve medication adherence.Genet Med advance online publication 05 January 2017.
Despite potential clinical benefits, implementation of pharmacogenomics (PGx) faces many technical and clinical challenges. These challenges can be overcome with a comprehensive and systematic ...implementation model.
The development and implementation of PGx were organized into eight interdependent components addressing resources, governance, clinical practice, education, testing, knowledge translation, clinical decision support (CDS), and maintenance. Several aspects of implementation were assessed, including adherence to the model, production of PGx-CDS interventions, and access to educational resources.
Between August 2012 and June 2015, 21 specific drug–gene interactions were reviewed and 18 of them were implemented in the electronic medical record as PGx-CDS interventions. There was complete adherence to the model with variable production time (98–392 days) and delay time (0–148 days). The implementation impacted approximately 1,247 unique providers and 3,788 unique patients. A total of 11 educational resources complementary to the drug–gene interactions and 5 modules specific for pharmacists were developed and implemented.
A comprehensive operational model can support PGx implementation in routine prescribing. Institutions can use this model as a roadmap to support similar efforts. However, we also identified challenges that will require major multidisciplinary and multi-institutional efforts to make PGx a universal reality.
Genet Med19 4, 421–429.
Ten organizations within the Electronic Medical Records and Genomics Network developed programs to implement pharmacogenomic sequencing and clinical decision support into clinical settings. ...Recognizing the importance of informed prescribers, a variety of strategies were used to incorporate provider education to support implementation. Education experiences with pharmacogenomics are described within the context of each organization's prior involvement, including the scope and scale of implementation specific to their Electronic Medical Records and Genomics projects. We describe common and distinct education strategies, provide exemplars and share challenges. Lessons learned inform future perspectives. Future pharmacogenomics clinical implementation initiatives need to include funding toward implementing provider education and evaluating outcomes.
Implementing individualized medicine into the medical practice Lazaridis, Konstantinos N; McAllister, Tammy M; Babovic-Vuksanovic, Dusica ...
American journal of medical genetics. Part C, Seminars in medical genetics,
March 2014, Letnik:
166C, Številka:
1
Journal Article
There is increasing recognition that genomic medicine as part of individualized medicine has a defined role in patient care. Rapid advances in technology and decreasing cost combine to bring genomic ...medicine closer to the clinical practice. There is also growing evidence that genomic-based medicine can advance patient outcomes, tailor therapy and decrease side effects. However the challenges to integrate genomics into the workflow involved in patient care remain vast, stalling assimilation of genomic medicine into mainstream medical practice. In this review we describe the approach taken by one institution to further individualize medicine by offering, executing and interpreting whole exome sequencing on a clinical basis through an enterprise-wide, standalone individualized medicine clinic. We present our experience designing and executing such an individualized medicine clinic, sharing lessons learned and describing early implementation outcomes.
To report the design and implementation of the Right Drug, Right Dose, Right Time-Using Genomic Data to Individualize Treatment protocol that was developed to test the concept that prescribers can ...deliver genome-guided therapy at the point of care by using preemptive pharmacogenomics (PGx) data and clinical decision support (CDS) integrated into the electronic medical record (EMR).
We used a multivariate prediction model to identify patients with a high risk of initiating statin therapy within 3 years. The model was used to target a study cohort most likely to benefit from preemptive PGx testing among the Mayo Clinic Biobank participants, with a recruitment goal of 1000 patients. We used a Cox proportional hazards model with variables selected through the Lasso shrinkage method. An operational CDS model was adapted to implement PGx rules within the EMR.
The prediction model included age, sex, race, and 6 chronic diseases categorized by the Clinical Classifications Software for International Classification of Diseases, Ninth Revision codes (dyslipidemia, diabetes, peripheral atherosclerosis, disease of the blood-forming organs, coronary atherosclerosis and other heart diseases, and hypertension). Of the 2000 Biobank participants invited, 1013 (51%) provided blood samples, 256 (13%) declined participation, 555 (28%) did not respond, and 176 (9%) consented but did not provide a blood sample within the recruitment window (October 4, 2012, through March 20, 2013). Preemptive PGx testing included CYP2D6 genotyping and targeted sequencing of 84 PGx genes. Synchronous real-time CDS was integrated into the EMR and flagged potential patient-specific drug-gene interactions and provided therapeutic guidance.
This translational project provides an opportunity to begin to evaluate the impact of preemptive sequencing and EMR-driven genome-guided therapy. These interventions will improve understanding and implementation of genomic data in clinical practice.
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