The 1200 patients project: creating a new medical model system for clinical implementation of pharmacogenomics

Abstract

The paradigm of individualized drug therapy based on genetics is an ideal that is now potentially possible. However, translation of pharmacogenomics into practice has encountered barriers such as limited availability and the high cost of genetic testing, the delays involved, disagreements about interpretation of results, and even lack of understanding about pharmacogenomics in general. We describe our institutional pharmacogenomics-implementation project, "The 1200 Patients Project," a model designed to overcome these barriers and facilitate the availability of pharmacogenomic information for personalized prescribing.

Figures

Figure 1. “The 1200 Patients Project” Model for Realizing Pharmacogenomic Implementation

Our study attempts to address and overcome the common barriers to more routine use of pharmacogenomic information in clinical practice. PGx = pharmacogenomic.

Figure 2. The genomic prescribing system of “The 1200 Patients Project” used for instantaneous delivery of pharmacogenomic results and virtual consultation when considering clinical implementation

All of a patient’s genetic results impacting current medications are summarized and made available to the provider each time the provider logs-in (top panel). The GPS provides not raw genotypes but rather a patient-specific interpretation of the complex genomic data for that drug, distilled into a summary the provider can read in 30 seconds or less (bottom panel). Each of these clinical pharmacogenomic drug summaries characterizes the nature of the drug-variant association(s) for that patient, the clinical impact of the variant on drug disposition, response, or toxicity, and a brief description of the studies which led to these associations. Providers have the opportunity to view the source publications supporting each drug-variant pair through direct link-outs to PubMed. In this way, the provider can choose (based on interest, familiarity with the subject, and time constraints) the level of detail they desire about each drug-variant summary. A dynamic feature of the GPS is that it allows the physician to query their patient’s preemptively-tested results to determine if any results impact other drugs that they might be considering prescribing. For example, if a provider wants to search whether their patient has a genotype impacting potential use of ‘simvastatin’, the drug’s name can be entered, and the patient-specific “30 second clinical summary” results for simvastatin are produced (bottom panel). Diseases can also be searched if a provider wants to compare pharmacogenomic information about multiple drugs that may treat a given disease. Providers can therefore use the GPS to consider pharmacogenomic information while they are considering prescribing any drug or as they are considering treating any condition. Additionally, each time providers log-in they are alerted if there is new pharmacogenomic information relevant to their patients since the last log-in. Note: the displayed patient name in the top panel has been fictionalized.