PG4KDS: a model for the clinical implementation of pre-emptive pharmacogenetics

Abstract

Pharmacogenetics is frequently cited as an area for initial focus of the clinical implementation of genomics. Through the PG4KDS protocol, St. Jude Children's Research Hospital pre-emptively genotypes patients for 230 genes using the Affymetrix Drug Metabolizing Enzymes and Transporters (DMET) Plus array supplemented with a CYP2D6 copy number assay. The PG4KDS protocol provides a rational, stepwise process for implementing gene/drug pairs, organizing data, and obtaining consent from patients and families. Through August 2013, 1,559 patients have been enrolled, and four gene tests have been released into the electronic health record (EHR) for clinical implementation: TPMT, CYP2D6, SLCO1B1, and CYP2C19. These genes are coupled to 12 high-risk drugs. Of the 1,016 patients with genotype test results available, 78% of them had at least one high-risk (i.e., actionable) genotype result placed in their EHR. Each diplotype result released to the EHR is coupled with an interpretive consult that is created in a concise, standardized format. To support-gene based prescribing at the point of care, 55 interruptive clinical decision support (CDS) alerts were developed. Patients are informed of their genotyping result and its relevance to their medication use through a letter. Key elements necessary for our successful implementation have included strong institutional support, a knowledgeable clinical laboratory, a process to manage any incidental findings, a strategy to educate clinicians and patients, a process to return results, and extensive use of informatics, especially CDS. Our approach to pre-emptive clinical pharmacogenetics has proven feasible, clinically useful, and scalable.

Keywords: clinical decision support; electronic health record; personalized medicine; pharmacogenetics; pharmacogenomics.

Figure 1. The PG4KDS Data Flow and Result Process

CDS = clinical decision support; CLIA = Clinical Laboratory Improvement Amendments; DB = database; DMET = Drug Metabolizing Enzymes and Transporters; DT = diplotype; EMR= Electronic Medical Record; MCW = Medical College of Wisconsin; PG = pharmacogenetics; PL Nmcltr = problem list nomenclature; PT = phenotype; Res DB = research database; Rx = prescription; SJ = St. Jude; SFTP = Secure File Transfer Protocol.

Figure 2. Patients Grouped by Number of High-risk Genotypes (N=1016)

Of the total number of patients genotyped, 78% have at least one high-risk genotype that warrants making medication therapy adjustments. “Possible” phenotypes are defined as genetic test results that cannot distinguish between two statuses, but are partially informative. In these cases, either the most actionable phenotype or the most likely phenotype is labeled as possible. [Color figure can be viewed in the online issue, which is available at http://onlinelibrary.wiley.com/journal/xxx].

Figure 3. Distribution of Phenotypes on the PG4KDS Protocol

Percentages for CYP2C19 (A), CYP2D6 (B), SLCO1B1 (C), and TPMT (D) are displayed. The table lists the number of patients with each observed phenotype. “Possible” phenotypes are defined as genetic test results that cannot distinguish between two statuses, but are partially informative. In these cases, either the most actionable phenotype or the most likely phenotype is labeled as possible. For example a patient with a TPMT result of “*1/*3A,*3B/*3C” is labeled as having a possible intermediate TPMT phenotype because it is > 100,000 times more likely than a low or absent function phenotype, and the test cannot distinguish whether the variants identified are on the same allele (*1/*3A, intermediate function phenotype) or on two separate alleles (3B/*3C, low or absent function phenotype). [Color figure can be viewed in the online issue, which is available at http://onlinelibrary.wiley.com/journal/xxx].