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The PMI (Precision Medicine Initiative) is an initiative funded by the NIH (National Institutes of Health), announced in early 2015 by President Barack Obama in his State of the Union address and later from the White House. Francis Collins, the director of the NIH and a key player in the human genome project, and others, have had a vision of precision medicine for at least a few years, but the technology (both informatics and genomic testing) have finally reached a point where such medicine is feasible for many patients, with funding of course. The overall goal of the initiative is to enroll (i.e., consent) over 1 million Americans into a cohort (or interconnected cohorts) for whom data will be collected, such as genetic data, for studying and delivering precision medicine. Funding will be available to recruit and study patients for this initiative starting in the fiscal year 2016 [1].


  • Precision, or personalized, medicine: although these terms are often used interchangeably, in this initiative they are referring to the general definition of delivering tailored care to each patient using data specific to each patient, i.e., "...taking individual variability into account."[2] Genomic is probably the most often thought of type of data used for this purpose, although similar types of data such as metabolomics, and other types of data such as data gathered from a patient's mobile device, for example environmental exposure data based on where a patient lives, works, and visits, could certainly also be used to deliver more precise medical care.
  • Genomic data definitions:
    • Phenotype and genotype: a phenotype is a disease or trait that arises in an individual due to a combination of his/her genotype(s), and environment. A genotype is the part of an individual's genetic profile that at least in part determines a given phenotype.
    • Pharmacogenomics is the use of genotypes to predict the right dose of the right drug at the right time for each patient. It takes advantage of the fact that many genes encode for proteins in metabolic pathways that determine how a drug will be metabolized by a given individual depending on their genetic profile, and also that some genes can make us susceptible, in other ways as well, to various possible adverse effects of drugs. Further information is available on a couple other pages on this wiki: Bioinformatics linkage of heterogeneous clinical and genomic information in support of personalized medicine and Pharmacogenomics
  • Metabolomics is similar to pharmacogenomics but has broader applications such as tailored nutrition
  • eHealth is the use of internet and similar information technologies to deliver health care. There is an EHealth Initiative which is collaborating with the PMI.

Informatics needs

Informatics will be needed in multiple areas of precision medicine, not limited to the following:

  • CDS (Clinican Decision Support): as delivering tailored care involves taking into account a plethora of data on an individual, some of which, such as genetic data, is very complex, the use of CDS is critical for delivering precision medicine. A good example is the amount of information needed from multiple sources, including both the EHR and genetics, to determine a precise optimal starting dose of warfarin - see the form to fill out on Elsewhere on this wiki is a review of these thus far: Clinical decision support or genetically guided personalized medicine: a systematic review and also a description of how this is used in pharmacogenomics: Development and use of active clinical decision support for preemptive pharmacogenomics
  • Returning of genomic results into the EHR will include multiple informatics solutions:
    • AGSs (ancillary genomics systems), which are being developed as a way to cope with the large volume of genomic data being generated, which cannot simply be pushed into the EHR as a single "lab," or even as an order panel of labs, result(s). These AGSs can store the huge volume of genomic data, and will need to connect with the EHR to deliver only those results that are actionable, in a format that clinicians can understand, into the appropriate place in the EHR depending on the type of action (such as pharmacogenomic results into a medication section vs. risk of a certain disease into a problem list perhaps). In addition, these results will need to be updated in the EHR by an AGS as knowledge on specific genotypes evolves (the understanding of phenotypic implications of a given genotype are continually evolving with continued research).
    • Updating of EHR systems to appropriately accommodate genomic test results, which will no longer be single test results, and eventually may include the entire genome of each patient. Vendors such as Epic are already working to create appropriate places within the EHR to store and appropriately display this information, but as this information will only continue to grow, developing informatics solutions will be an ongoing process.
    • Terminology expansion, both standard and interface terminologies need to be updated to convey precision medicine. Interface terminology providers such as IMO (Intelligent Medical Objects) are working to provide proper terms to convey such results (such as conveying "risk of" a disease vs. "already has" a disease), while standards development organizations are working to update standards such as SNOMED-CT.
  • eHealth, and mhealth (mobile health), informatics: Although these are slightly different areas, both will need to be used in precision medicine for gathering data for care, such as from apps on mobile devices, and also delivering care, such as telemedicine over the internet.
  • Research - multiple informatics solutions will be needed to manage the research cohort, from enrollment of patients, to managing data including protecting the privacy of that data, to delivering of results to the patients.

Potential impact

  • On clinical care: this initiative will likely change the way clinical care is delivered, as with precision medicine, quality can be improved as adverse drug events can be avoided, and more.
  • On research: this initiative should accelerate ongoing research such as that being done by existing collaborations such as eMERGE, CSER, and CPIC.


  2. Francis S. Collins, M.D., Ph.D., and Harold Varmus, M.D., A New Initiative on Precision Medicine, N Engl J Med 2015; 372:793-795, February 26, 2015. DOI: 10.1056/NEJMp1500523

External links

Submitted by Jennifer Allen Pacheco