Reading and interpreting a genotype profile from a QR code.

<p>Reading and interpreting a genotype profile from a QR code.</p

Excerpt of the OWL 2 ontology used for inferring matching polymorphisms and CDS rules from patient genotypes.

<p>Excerpt of the OWL 2 ontology used for inferring matching polymorphisms and CDS rules from patient genotypes.</p

MSC system modules and their interactions.

<p>MSC system modules and their interactions.</p

Interface to generate a QR code from a genetic profile in 23andMe or VCF format.

<p>For files in 23andMe format, the strand orientation of the genetic information can be chosen.</p

Interface for manual entry of genetic traits.

<p>Interface for manual entry of genetic traits.</p

Processing a patient's genetic profile and obtaining the corresponding anonymous QR code.

<p>Processing a patient's genetic profile and obtaining the corresponding anonymous QR code.</p

Example of simple pharmacogenomics-based treatment recommendations generated from a QR code.

<p>The current user interface displays basic recommendations, but future versions of the interface will also allow displaying further information – such as underlying mechanisms and evidence – when required.</p

Incidence of Exposure of Patients in the United States to Multiple Drugs for Which Pharmacogenomic Guidelines Are Available

<div><p>Pre-emptive pharmacogenomic (PGx) testing of a panel of genes may be easier to implement and more cost-effective than reactive pharmacogenomic testing if a sufficient number of medications are covered by a single test and future medication exposure can be anticipated. We analysed the incidence of exposure of individual patients in the United States to multiple drugs for which pharmacogenomic guidelines are available (PGx drugs) within a selected four-year period (2009–2012) in order to identify and quantify the incidence of pharmacotherapy in a nation-wide patient population that could be impacted by pre-emptive PGx testing based on currently available clinical guidelines. In total, 73 024 095 patient records from private insurance, Medicare Supplemental and Medicaid were included. Patients enrolled in Medicare Supplemental age > = 65 or Medicaid age 40–64 had the highest incidence of PGx drug use, with approximately half of the patients receiving at least one PGx drug during the 4 year period and one fourth to one third of patients receiving two or more PGx drugs. These data suggest that exposure to multiple PGx drugs is common and that it may be beneficial to implement wide-scale pre-emptive genomic testing. Future work should therefore concentrate on investigating the cost-effectiveness of multiplexed pre-emptive testing strategies.</p></div

Classification of potential clinical effects observed in patients with risk phenotypes, based on DPWG guidelines.

<p>Classification of potential clinical effects observed in patients with risk phenotypes, based on DPWG guidelines.</p

Distribution of incident use within four-year time window among therapeutic areas.

<p>Distribution of incident use within four-year time window among therapeutic areas.</p