Linda Jo Bone Jeng

An openly available online tool for implementing the ACMG/AMP standards and guidelines for the interpretation of sequence variants.

An openly available online tool for implementing the ACMG/AMP standards and guidelines for the interpretation of sequence variants

The IGNITE Pharmacogenetics Working Group: An Opportunity for Building Evidence with Pharmacogenetic Implementation in a Real‐World Setting

Genotype is increasingly recognized as an important factor influencing the likelihood for drug effectiveness or risk for adverse events. Genetic information is now included in US Food and Drug Administration-approved labeling for over 130 drugs, and in some cases, the information is in the form of a boxed warning given the potentially serious implications of genotype on drug response. Based on the growing body of evidence supporting genetic contributions to drug response, the Clinical Pharmacogenetics Implementation Consortium (CPIC) was formed to provide consensus guidelines on interpretation and translation of genotype results into actionable prescribing decisions.1 Guidelines have been published for 18 drugs or drug classes as of late 2016. The Precision Medicine Initiative is expected to further drive discoveries in genomic medicine and their translation to patient care.2 In 2013, the National Institutes of Health (NIH)-funded Implementing GeNomics In praTticE (IGNITE) network was established to support the development and investigation of genomic medicine practice models to enhance its implementation into routine clinical practice.3 One of the challenges hindering genomic implementation is the limited data on the outcomes and cost-effectiveness of genotype-guided drug therapy. The IGNITE network, consisting of institutions funded in the network and affiliate members, includes a number of institutions that have implemented pharmacogenetic testing to assist with prescribing

Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry.

To characterize the extent and impact of ancestry-related biases in precision genomic medicine, we use 642 whole-genome sequences from the Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) project to evaluate typical filters and databases. We find significant correlations between estimated African ancestry proportions and the number of variants per individual in all variant classification sets but one. The source of these correlations is highlighted in more detail by looking at the interaction between filtering criteria and the ClinVar and Human Gene Mutation databases. ClinVars correlation, representing African ancestry-related bias, has changed over time amidst monthly updates, with the most extreme switch happening between March and April of 2014 (r=0.733 to r=−0.683). We identify 68 SNPs as the major drivers of this change in correlation. As long as ancestry-related bias when using these clinical databases is minimally recognized, the genetics community will face challenges with implementation, interpretation and cost-effectiveness when treating minority populations.

Educational innovations in clinical pharmacogenomics

Genetic and genomic discovery is revolutionizing medicine at an extraordinary pace, leading to a better understanding of disease and improved treatments for patients. This advanced pace of discovery presents an urgency to expand medical school curricula to include genetic and genomic testing (including pharmacogenomics), and integration of genomic medicine into clinical practice. Consequently, organizations and healthcare authorities have charged medical schools with training future physicians to be competent in their knowledge of genomic implementation.

Multisite Investigation of Strategies for the Implementation of CYP2C19 Genotype‐Guided Antiplatelet Therapy

CYP2C19 genotype‐guided antiplatelet therapy following percutaneous coronary intervention is increasingly implemented in clinical practice. However, challenges such as selecting a testing platform, communicating test results, building clinical decision support processes, providing patient and provider education, and integrating methods to support the translation of emerging evidence to clinical practice are barriers to broad adoption. In this report, we compare and contrast implementation strategies of 12 early adopters, describing solutions to common problems and initial performance metrics for each program. Key differences between programs included the test result turnaround time and timing of therapy changes, which are both related to the CYP2C19 testing model and platform used. Sites reported the need for new informatics infrastructure, expert clinicians such as pharmacists to interpret results, physician champions, and ongoing education. Consensus lessons learned are presented to provide a path forward for those seeking to implement similar clinical pharmacogenomics programs within their institutions.

User-centered design of multi-gene sequencing panel reports for clinicians

The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects.