Systems-guided support to enable personalized medicine

Oct. 22, 2015

It is a time of exciting developments in laboratory medicine. Advances in genomics and molecular diagnostics continue to improve our understanding of diseases and effective therapies, while innovations in Big Data and information technology are helping to advance genetic science and personalized medicine into clinical practice.

The federal government’s Precision Medicine Initiative will launch in 2016 to further evaluate genetic causes of disease and find new drugs that target mutations. The $215 million initiative will identify new approaches for the diagnosis and treatment of diseases, potentially saving billions of dollars and significantly improving health outcomes.

Labs will play a central role in these and other value-based healthcare initiatives by helping to ensure the appropriate ordering of genetic tests and the interpretation of genomic results that lead to the best evidence-based therapies.

Pharmacogenomics in practice

One of the fastest-growing areas in molecular diagnostics is genetically guided therapy management, also known as pharmacogenomics (PGx), which analyzes unique genetic information and other risk factors to help predict how an individual will respond to a specific drug therapy.

A common use of PGx testing is to identify variations in CYP genes that are most responsible for metabolizing drugs to determine if an individual will have a response to a given medication. There are about 60 CYP genes in humans, with approximately 10 genes playing the largest role in 70 to 80 percent of drug metabolism.The number of polymorphisms in these 10 genes may correlate to thousands of different gene variations important to drug use and efficacy. While this is a mind-boggling amount of data, the good news is that since many commonly prescribed drugs are impacted by just a few genes, the PGx results of a single test may be valuable across many diagnostic and therapeutic episodes in a patient’s lifetime.

PGx testing is also important for identifying gene variations that cause adverse drug reactions (ADRs). The Food and Drug Administration reports that there are more than two million avoidable ADRs per year in the United States, costing in excess of $136 billion. Use of PGx testing to identify genetic variations that increase the likelihood of a patient having an adverse reaction to a specific medication, or identifying related variables impacting the anticipated response for the medication, will help to significantly improve the risk of ADRs and result in considerable cost savings to the healthcare system.

Complex data exceeds cognitive abilities

Although PGx testing offers significant therapeutic value, the growing volume of available genetic diagnostic tests and the raw data they generate make it virtually impossible for physicians to stay current. The biggest challenge is the difficulty in analyzing and interpreting the complex and vast amount of genomic and molecular data involved in PGx testing, and integrating it into clinical decision-making.

Most clinical information systems and electronic medical record systems today cannot effectively manage or transform genetic test data into actionable guidance for use in medical practice because of their inability to interpret the data in the appropriate clinical context or store and display the information as structured data.

The unfortunate result is that diagnostics are often improperly utilized and resultant therapeutics are inaccurately ordered. Studies show physicians order the wrong test in 30 percent of cases and subsequently order the wrong therapy based on those test results in 30 percent of cases.2

Decision support for personalized medicine

Laboratories and diagnostic service providers are well-positioned to help transform this complex data into clinical guidance using knowledge-based information technology to help clinicians order genetic tests, interpret test results, and make the most effective therapeutic decisions.

As more complicated, multi-genic predictors of therapeutic response are identified, clinicians will increasingly be required to rely on decision-support tools in order to implement new testing protocols in clinical practice, as the consistent interpretation of PGx test results will remain extremely challenging.3

There is a specific need for systems that can help clinicians interpret and integrate PGx test results into practice by matching test results to a knowledge base of evidence for clinical genetics. Clinical decision-support systems designed for this purpose can provide the information and reporting capabilities necessary to guide effective clinical decision making, including understanding unique patient risk factors, which drugs are relevant, what genes affect those drugs, and which tests ensure the highest impact at the lowest cost.1

As PGx testing gains increased utility and application in the clinical environment, laboratories must be equipped to expand their laboratory information and revenue cycle management systems to store, process, and manage the volume of unique data generated by PGx tests and ensure that the systems can handle the required integration, workflow management, reporting, compliance, and reimbursement issues that will emerge. Because molecular and genomics data is dynamic and ever-changing, these systems must be highly adaptable and continually updated.

Testing a patient’s genetic code may someday be routine to help guide treatment decisions from cradle to grave. By leveraging technology to help capture, interpret, and share PGx data, diagnostic service providers and labs can better support the clinical decision-making necessary to transform patient care through personalized medicine.


  1. Terry M. A lab leader’s guide to pharmacogenomic testing (PGx): cloud-based software reporting of PGx for hospitals, health systems and clinical laboratories. DARK Daily Laboratory and Pathology News. 3-23.
  2. Zhi M Ding EL, Theisen-Toupal J, Whelan J, Arnaout R. The landscape of inappropriate laboratory testing: a 15-year meta-analysis. PLOS ONE 8(11):e78962. doi:10.1371/journal.pone.0078962.
  3. Crews KR, Hicks JK, Pui C-H, Relling MV, Evans WE. Pharmacogenomics and individualized medicine: translating science into practice. Clin Pharmacol Ther. 2012;92(4): 467–475.
Lâle White, MBA, serves as CEO for San Diego-based XIFIN, Inc., developers of a health economics optimization platform used to streamline diagnostic and business decision-making.
Don Rule, MBA, serves as CEO for Seattle-based Translational Software, Inc., which provides end-to-end solutions and a powerful PGx portal and knowledge base to support clinicians adopting personalized medicine.