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Technical hurdles to the wide-spread use of genetic data in humans are disappearing. The cost of sequencing an entire human genome is sinking to around $1,000. Commercial companies are offering genetic tests for their clients’ personal use.

Given that changes such as these are occurring, you could easily imagine that you will, one day soon, arrive at your doctor’s office carrying a thumb drive containing your entire genomic sequence. What then? Will your doctor simply download your genomic information, run a computer program, and generate a report about your chances of developing a disease or experiencing an adverse reaction to a particular medication?

Unfortunately, that day is still far off. But patients are already availing themselves of genetic testing services, and bringing their test results to their doctors’ offices. The doctors, however, may be unprepared.

As a practical matter, personalized medicine will be realized through intermediaries that can help clinicians work in accordance with the latest genomic knowledge. One such intermediary is the Clinical Pharmacogenetics Implementation Consortium (CPIC), an organization working to streamline the process of translating genetic test results into gene-based prescription recommendations.

“The goal of the CPIC is to facilitate the process to apply pharmacogenetics to clinical practice by developing guidelines for clinicians,

” states Kelly E. Caudle, Pharm.D., Ph.D., CPIC coordinator, St. Jude Children’s Research Hospital. “We do not tell clinicians if genetics testing should be ordered, but rather what to do with the information when it is available.” The CPIC strives to provide clear, concise information for providers, explaining how genetic data applies to their patients.

A genetic test is unlike a blood glucose test, which is merely a snapshot of a dynamic situation,” Dr. Caudle continues. “Genetic results follow a patient for a lifetime.” Hence, genetic information needs to be entered into a patient’s electronic health record (EHR) in a time-independent way. When a physician orders a drug for a patient 15 years after the genetic test was added, an alert needs to inform the clinician about the results of genetics testing in relation to the treatment.

According to Dr. Caudle, the CPIC not only provides gene-based clinical recommendations, it also supports EHR mechanisms. Such mechanisms can, for example, facilitate the ordering of a pharmacogenomics panel in advance of clinical need (preemptive genotyping) or in response to a specific drug indication.

In addition to being able to add to the knowledge base of genetic information in humans, the CPIC also strives to maintain the ability to integrate with several EHR forms. Different medical groups often have different applications that they use to access EHRs. The ability of CPIC information to integrate with all EHR types is essential for information to flow freely.

CPIC guidelines enable the translation of genetic laboratory test results into actionable prescribing decisions for specific drugs,” declares Robert R. Freimuth, Ph.D., assistant professor of biomedical informatics at the Mayo Clinic and co-chair of the CPIC Informatics Working Group. “A key assumption underlying CPIC guidelines is that as clinical genomic testing becomes more common, clinicians will have those results available but may face uncertainty about how to use those results to inform their choice of treatment.

One theme that has emerged is the need for standardization within pharmacogenetics,” maintains Dr. Freimuth. “How is clinical genomic data represented? We need to be able to exchange genomic information within and between systems and institutions using specific data standards.

“Next, we need to define the language we use. If different words are used, the interpretation of results can become variable. We need common definitions provided by terminology standards.

Additionally, standard models are essential to describe how genomic data and clinical decisions are linked to one another. Knowledge must be captured and structured so that computers and people can read it. Genotype to interpreted phenotype tables must be standardized—these tables are really at the core to understanding and communicating information.

“Finally, messaging standards provide the means to exchange data between systems and deliver it to physicians. The first three types of standards (data, terminology, and models) ensure that the information is clearly represented; the messaging standards provide the means for information to be exchanged between computer systems and communicated to clinicians. Together, all four types of standards are necessary to ensure information is clearly communicated and interpreted.

 

 

Vennila is one of BioTecNika's Online Editors. When she is not posting news articles and jobs on the website, she can be found gardening or running off to far flung places for the next adventure, armed with a good book and mosquito repellant. Stalk her on her social networks to see what she does next.