Sitting in my first, and only, pharmacogenomics course — learning how genes affect a person's response to drugs — during pharmacy school, I was taken aback by the potential implication and power of personalizing a patient’s medication regimen based on their genetic makeup. I wondered why we weren’t testing every single patient and prescribing medications personalized to them. During my fourth-year clinical rotations, I often suggested performing pharmacogenomics testing for select patients, but the recommendations fell by the wayside, and I was unable to see the use of pharmacogenomics come to fruition in clinical practice.
Even in higher-risk situations, such as the use of Plavix, where the prescribing label warns to consider use of alternative platelet inhibitors in patients identified as being CYP2C19-poor metabolizers, it was only a consideration and not a hard requirement. When probed, my clinician preceptors would often ubiquitously respond that testing took too much time to perform, or something to the tune of, “Who’s going to pay for that?” or “If I had the information available now, I would consider using it.” Those who advocate for routine and preemptive pharmacogenomic testing and believe in its clinical utility, such as myself, are often seen as overly optimistic clinicians who don’t quite understand the intricacies and barriers of the health care system. However, pharmacogenomic testing’s benefits show it is worth implementing, even if it means working around barriers.
Why is pharmacogenomics testing worth the effort? Well, it can help our patients and us more than we think. Data from the Vanderbilt Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) program, which was created to implement preemptive panel-based pharmacogenomic testing into clinical practice, reported that of the ~10,000 studies, 91% individuals in the study had actionable variants. These actionable variants were specific to five pre-defined drug-gene interactions: clopidogrel (CYP2C19), simvastatin (SLCO1B1), warfarin (CYP2C9 and VKORC1), thiopurines (TPMT), and tacrolimus (CYP3A5). Of the 91% of patients with actionable genotypes, 40% of them had evidence of exposure to the specific medication related to that genotype, highlighting numerous cases where clinical outcomes could be optimized or improved. Furthermore, what is unique about the PREDICT model is the use of preemptive screening for a panel of drug-gene interactions compared to “reactive” single-gene screening that is often triggered by new medication exposure. Authors estimated that more than 5,000 genetic tests were avoided using a panel-based screening method, compared to a single-gene testing model. These five drug-gene pairs are integrated into the EMR system, further optimizing usage by clinicians.
It is true that the implementation of pharmacogenomics is more intricate, nuanced, and complicated in clinical practice. The barriers to implementation have been extensively reviewed in the literature, but the most common are concerns about cost and reimbursement, lack of clinician education around pharmacogenomic data, and challenges around incorporating it into current infrastructure.
Cost, reimbursement, insurance, and access are always taken into consideration with any therapy or clinical product/service, and pharmacogenomics is no different. Despite the existence of access challenges with pharmacogenomic testing, it’s important to understand that with the rapid advancement of genomic technology, the cost of testing has significantly decreased and will continue to decrease in the future. As more data emerges around the efficacy and cost-saving and health care resource-saving potential of pharmacogenomics, health plans and insurers will be more inclined to provide adequate coverage for tests. Furthermore, panel-based screening, as discussed earlier with the PREDICT model from Vanderbilt, is comparable in cost to single-gene assays. Preemptively screening for a range of drug-gene interactions is an incentive to overcome some of the cost/reimbursement challenges.
It is important to note that there is some commercial and Medicare-associated coverage for pharmacogenomic testing, but the reimbursement landscape is not without challenges and coverage often varies based on criteria defined by insurers. Understandably, these criteria are often based on gene-drug interactions that are graded a level A or B on the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines or listed in the FDA table of known gene-drug interactions. Recently, a specific Medicare Administrative Contractor – private insurers awarded specific geographical regions to cover Medicare A and B claims – approved a local coverage determination for pharmacogenomic coverage for their specific geographical region. These types of initiatives are promising and moving in the right direction for more future coverage of pharmacogenomic testing. Also, in an effort to further expand access, many pharmacogenomic testing companies provide a tiered cost program based on reported financial income. Although the reimbursement and cost landscape is in its infancy, with more data around potential savings for indirect and direct cost-savings of implementing pharmacogenomic testing, health plans and insurers will be likely to follow suit with more coverage.
Overcoming lack of education is a simpler step, with clinicians familiarizing themselves with pharmacogenomic testing, specifically clinically actionable recommendations when faced with pharmacogenomic variants of significance. I believe that in order to catalyze the adoption of pharmacogenomics, clinicians must take the onus upon themselves to learn about pharmacogenomics through continuing education efforts, certification programs, or additional training. I believe that when a clinician sees the potential of pharmacogenomics, it will be hard not to be excited, or at least hopeful, for a future of more personalized prescribing and disease management. There has been much research in the past 10 years around the utility of pharmacogenomics. The potential pharmacogenomic data has in helping clinicians — as well as patients — optimize their care, improve efficacy, and reduce direct and indirect health care costs is meaningful.
So how do we begin to navigate the barriers? First, educated clinicians can advocate for their institutions to invest in more training and even infrastructure to have this pharmacogenomic data integrated into their local EMR systems. Second, besides clinicians advocating for these changes in their institutions, an important point to discuss is the integration of this data into current clinical workflow. Although various guidelines exist, providing actionable information around pharmacogenomic variants, high-risk medications continue to be prescribed to patients whose relevant genotypes are unknown. At one hospital, 48% of pediatric patients received at least one high-risk drug in a one-year period. In addition to the Vanderbilt program, an example of another program optimizing clinic workflow is an initiative in Europe using preemptive genotyping of a panel of pharmacogenomic markers. The goal is to provide actionable data embedded into the EMR system without disruption of clinical workflow. Although the study is in Europe, the prospect of these types of integrations in the U.S. is promising and is already occurring in several locations, such as Mayo Clinic, Vanderbilt University Medical Center, Mount Sinai Medical Center, St. Jude Children's Research Hospital, and the University of Florida and Shands Hospital. These types of initiatives will allow easier implementation and provide clinicians with point-of-care data and recommendations. It is also important to note that many pharmacogenomic companies also provide clinical decision support services for clinicians to utilize to help overcome some of these barriers with workflow and decision-making.
Undoubtedly, there are challenges that exist in our health care system, but it is hard to imagine a future without routine clinical integration. With the advancement of technology in this sector, along with the growing database of literature highlighting cost-effectiveness and clinical efficacy, we as health care professionals must be prudent in educating ourselves, our patients, and our employers to advocate for the future of a more personalized approach to health care and disease management.
What is your opinion on pharmacogenomics? Share your thoughts in the comments.
Dalga Surofchy, PharmD, APh, is an Advanced Practicing Pharmacist currently working as a Clinical Manager of Medical Affairs at a boutique pharmaceutical consulting group. He also teaches as an adjunct faculty at UC San Diego. He holds a Bachelor’s degree in Biology from UC Berkeley and a Doctor of Pharmacy degree from UC San Francisco. His interests are in precision/personalized medicine, preventative medicine, health equity, education, and market/patient access. His previous roles include a mix of outpatient and clinical pharmacy. Outside of work, he enjoys playing basketball, surfing, rock-climbing, skiing, and spending outdoor time with his family. He reports no conflicts of interest for this piece.