top of page

Pharmacogenomics & Personalized Medicine Management: Opportunities & Challenges

Sept 10, 2020

ORION by VieCure

Volume 1, Issue 4

A presentation by Jai Patel, PharmD, BCOP, CPP, Chair, Cancer
Pharmacology and Pharmacogenomics, Levine Cancer Institute

Pharmacogenomics Optimizes Medication Management

A discussion on using pharmacogenomics to determine how an individual’s genes affects her orhis responses to specific drugs was led by Dr. Jai Patel, Chair of Cancer Pharmacology and Pharmacogenomics at the Levine Cancer Institute in Charlotte, NC, at a recent meeting of VieCure’s Clinical Advisory Council. Dr. Patel reinforced the importance of pharmacogenomic testing broadly, but especially in oncology, the challenges clinics currently face to implement this relatively new testing, and benefits when choosing and managing a patient’s therapy.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) has published over 50 drug-gene guidelines based on the latest available evidence that focus on actionable results based on pharmacogenomic testing. The FDA has also published a Table of Pharmacogenetic Associations, which includes roughly 50 drug-gene associations for which the data support therapeutic management recommendations. The CPIC guidelines and FDA tables somewhat overlap, but also have major differences. Pharmacogenetic experts have called for data harmonization, greater clarity, and interagency collaboration. He also highlighted several challenges, described in detail in this issue, that practices face when trying to implement this testing including data integration in most clinical decision support systems, data harmonization, lack of confirmatory randomized controlled trials/evidence, patient education, reimbursement/cost and clinician education.

Given the prevalence of genes that interact with drugs in the general population, Dr. Patel argued for the urgency of widespread use of pharmacogenomic testing.

Clinical Challenges in the Adoption of Pharmacogenomics

Data Integration & Clinical Decision Support System

  • There are computer-based algorithm clinical decision support systems that support providers in prescribing drugs at the point-of-care

  • These tools are essential for scaling and adopting a pharmacogenomic program

  • These systems are sometimes integrated within the EMR or are a separate parallel application

  • Data integration allows for preemptive testing prior to drug prescribing rather than reactive testing after a patient has experienced an adverse event or failed therapy

  • Need to balance meaningful alerts to the user, those with high levels of evidence vs. too many alerts that can cause “alert fatigue”

Data Harmonization

  • There is limited understanding in the community regarding the pharmacogenomic evidence and thus understanding and harmonizing the required data has been a major challenge

  • There are several sources of peer-reviewed and industry-accepted sources such as the Food and Drug Administration (FDA) and Clinical Pharmacogenetics Implementation Consortium (CPIC), which need to be made more accessible by community providers

  • The FDA must provide greater clarity on what is deemed "high-level evidence," and has recently been more active within the pharmacogenomics space, increasing the attention drawn to the importance of testing

  • There are several differences between CPIC and FDA data making it difficult to make decisions based on clinical evidence

  • Dr. Patel is currently evaluating these sources and he encourages the different agencies to work together to help harmonize clinical evidence

Lack of Conformity Randomized Controlled Trials / Evidence

  • Randomized controlled trials have been the gold standard for evaluating new interventions; however, there is a theory that a lower threshold of evidence should exist for pharmacogenomics similar to drug-drug interactions

  • The vast majority of drug interactions are not necessarily confirmed by clinical trial, but are accepted in clinical practice because there is a scientific possibility

  • In situations where genomic variants alter drug exposure, and we know that drug exposure correlates with response or drug toxicity, that is clinically relevant

Clinician Education

  • Education needs to be provided across all disciplines and levels of the clinic

  • Studies have sown that providers believe that pharmacogenomics is clinically relevant, but that they do not feel educated enough to integrate genomic data into routine practice

  • Pharmacists typically feel the most comfortable with this information

Reimbursement / Cost

  • Fortunately testing, including multi-gene testing, is becoming less expensive and more accessible

  • More clinical evidence has resulted in better payer coverage

Patient Education

Urgently need better patient education to facilitate testing uptake and discussion of treatment options

bottom of page