On February 25th, one year after the announcement of the Precision Medicine Initiative (PMI), the White House hosted the Precision Medicine Summit. A White House press release described how various public and private groups will be taking steps to advance the goals of the PMI. As part of the PMI Stanford will launch a consultative pharmacogenetics practice for physicians to refer patients with unusual drug responses. Dr. Russ Altman, Co-Principal Investigator (Co-PI) of PharmGKB will lead the pharmacogenetics consultative practice. The consultative practice will evaluate genetic variants in patients with unusual drug responses and will use Clinical Pharmacogenetics Implementation Consortium (CPIC) dosing guidelines to focus attention on gene-drug pairs with the best evidence for actionability. In addition, Stanford University will also make the genomic data of 77 individuals of Iranian descent publicly available. The genomes of those 77 individuals were sequenced as part of the Iranian Genome Project, for which Dr. Altman is also the PI. Dr. Roxana Daneshjou, a former student in Dr. Altman’s lab is the lead researcher for the project. Although Dr. Daneshjou is leading the data analysis for the project, Dr. Altman explained “we wanted to get the data out into the public as soon as possible, so (we) have taken the slightly unusual measure of making the data available before we get our paper out… we want people to use it.” A major goal of the PMI is to “open up data and technology tools to invite citizen participation, unleash new discoveries, and bring together diverse collaborators to share their unique skills.”
Sunday, February 28, 2016
Wednesday, February 24, 2016
EPIC Integrates Genelex's Pharmacogenomics Decision Support System into Electronic Health Records
On
Feb 23rd, Pharmagenomics (PGx) testing company Genelex announced enhanced connection with
Epic, the most widely used electronic
health record (EHR) system in US. With this new connectivity, healthcare
systems and providers using Epic EHRs will be able to use Genelex's YouScript
Precision Prescribing software to better identify patients who are at greater
risk of adverse drug events based on pharmacogenetic information. In a GenomeWebnews article, Genelex CEO Kristine Ashcraft said “It's an indicator of
market adoption and market demand for pharmacogenetic information”.
Translating
pharmacogenomics knowledge into clinical practice has not been an easy task.
Barriers that prevent the widespread use of PGx diagnostics include the lack of
incentives for health care systems to conduct tests as well as lack of clear
clinical guidelines for translating genetic variations into actionable
recommendations. Additionally, computational tools for clinical decision
support (CDS) will need to be developed and integrated in the EHR to prompt and
guide clinicians on how to use genetic information when prescribing drugs. CPIC was formed in 2009 as a
collaborative project between PharmGKB and the Pharmacogenomics ResearchNetwork to address some of the challenges in clinical implementation. Its goal
was to create guidelines to aid clinicians on how genetic test results should
be translated into specific prescribing actions. CPIC guidelines are
simultaneously published and maintained on PharmGKB website, in both plain text
as well as computable form for easy integration into clinical decision support
tools. Many of the CPIC guidelines have been endorsed by professional societies
such as The American Society of Health-System Pharmacists (ASHP). CPIC have
also established informatics subgroup to support the adoption of the CPIC guidelines by developing tools
to combine clinical information from the EHR with the information from the CPIC
guidelines and use them for clinical decision support. Preemptive pharmacogenomic testing programs using EHRs and
decision support tools have been deployed at several academic medical centers,
eg. St. Jude, Vanderbilt University and University of Florida.
Read
the GenomeWeb article:
Read
the press release from Genelex:
More
information about CPIC and CPIC informatics working group:
https://cpicpgx.org/informatics/
Wednesday, February 10, 2016
A Study of the Transcriptomic Variation Affecting Pharmacogenes
In an effort to capture differences in the expression of pharmacogenes between individuals and between tissue types and to characterize novel pharmacogene splice variants, researchers conducted a transcriptomic analysis of 389 pharmacologically important genes in liver, kidney (cortex), heart (left ventricle), and adipose tissue from 139 individuals as well as 45 lymphoblastoid cell lines (LCLs). Tissue samples came from various Pharmacogenomics Reseach Network (PGRN) groups. The list of pharmacogenes was compiled from several sources, including PharmGKB. The results were recently published in The Pharmacogenomics Journal.
The study, “Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines”, reports that many pharmacogenes were highly expressed in liver or kidney when compared to other tissues, although some were consistently expressed at high or low levels in all tissue types, and that many pharmacogenes showed variable expressed when comparing between individuals and tissue types. The authors suspect that some differences in expression between individuals may reflect environmental and health differences between people. Expression of most pharmacogenes was almost always lower in LCLs when compared to the other tissue types that were examined. Finally, the authors report the discovery of several novel pharmacogene splicing events and splice variant differences between tissue types.
These findings suggest that variable expression of pharmacogenes between tissue types and individuals as well as differences in alternative splicing patterns could contribute to the observed variation in drug dosing, response, and toxicities.
The study, “Transcriptomic variation of pharmacogenes in multiple human tissues and lymphoblastoid cell lines”, reports that many pharmacogenes were highly expressed in liver or kidney when compared to other tissues, although some were consistently expressed at high or low levels in all tissue types, and that many pharmacogenes showed variable expressed when comparing between individuals and tissue types. The authors suspect that some differences in expression between individuals may reflect environmental and health differences between people. Expression of most pharmacogenes was almost always lower in LCLs when compared to the other tissue types that were examined. Finally, the authors report the discovery of several novel pharmacogene splicing events and splice variant differences between tissue types.
These findings suggest that variable expression of pharmacogenes between tissue types and individuals as well as differences in alternative splicing patterns could contribute to the observed variation in drug dosing, response, and toxicities.
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