Ending the pharmacogenomic gag rule: the imperative to report all results

Development of a Multifaceted Program for Pharmacogenetics Adoption at an Academic Medical Center: Practical Considerations and Lessons Learned

In 2019, Indiana University launched the Precision Health Initiative to enhance the institutional adoption of precision medicine, including pharmacogenetics (PGx) implementation, at university-affiliated practice sites across Indiana. The overarching goal of this PGx implementation program was to facilitate the sustainable adoption of genotype-guided prescribing into routine clinical care. To accomplish this goal, we pursued the following specific objectives: (i) to integrate PGx testing into existing healthcare system processes; (ii) to implement drug-gene pairs with high-level evidence and educate providers and pharmacists on established clinical management recommendations; (iii) to engage key stakeholders, including patients to optimize the return of results for PGx testing; (iv) to reduce health disparities through the targeted inclusion of underrepresented populations; (v) and to track third-party reimbursement. This tutorial details our multifaceted PGx implementation program, including descriptions of our interventions, the critical challenges faced, and the major program successes. By describing our experience, we aim to assist other clinical teams in achieving sustainable PGx implementation in their health systems.

Utilization of supportive care medications and opportunities for pre-emptive pharmacogenomic testing in pediatric and young adults with leukemia

This study aimed to evaluate the utilization of drugs with pharmacogenomic guidelines (PGx-drugs) for personalized dosing in pediatric leukemia. A retrospective observational study of pediatric leukemia patients admitted between 2009-2019 at a single-center academic children's hospital was conducted to determine PGx-drug exposure within 3 years of diagnosis. Along with baseline demographic and clinical characteristics of these patients, data regarding dates of diagnosis, relapse, death were collected. During the study period, inclusion criteria were met by 714 patients. The most frequently given medications were ondansetron (96.1%), morphine (92.2%), and allopurinol (85.3%) during the study period. In this cohort, 82% of patients received five or more PGx-drugs. Patients diagnosed with acute myeloid leukemia and leukemia unspecified were prescribed more PGx-drugs than other types of leukemia. There was a significant relationship between age at diagnosis and the number of PGx-drugs prescribed. Adolescents and adults both received a median of 10 PGx-drugs, children received a median of 6 PGx-drugs, and infants received a median of 7 PGx-drugs (p < 0.001). Patients with recurrent leukemia had significantly more PGx-drugs prescribed compared to those without recurrent disease, 10 drugs and 6 drugs, respectively (p < 0.001). Patients diagnosed with childhood leukemia are high utilizers of PGx-drugs. There is a vital need to understand how PGx testing may be utilized to optimize treatment and enhance quality of life. Preemptive PGx testing is a tool that aids in optimization of drug therapy and decreases the need for later treatment modifications. This can result in financial savings from decreased health-care encounters.

Validation of Pharmacogenomic Interaction Probability (PIP) Scores in Predicting Drug-Gene, Drug-Drug-Gene, and Drug-Gene-Gene Interaction Risks in a Large Patient Population

Utilizing pharmacogenomic (PGx) testing and integrating evidence-based guidance in drug therapy enables an improved treatment response and decreases the occurrence of adverse drug events. We conducted a retrospective analysis to validate the YouScript^® PGx interaction probability (PIP) algorithm, which predicts patients for whom PGx testing would identify one or more evidence-based, actionable drug-gene, drug-drug-gene, or drug-gene-gene interactions (EADGIs). PIP scores generated for 36,511 patients were assessed according to the results of PGx multigene panel testing. PIP scores versus the proportion of patients in whom at least one EADGI was found were 22.4% vs. 22.4% (p = 1.000), 23.5% vs. 23.4% (p = 0.6895), 30.9% vs. 29.4% (p = 0.0667), and 27.3% vs. 26.4% (p = 0.3583) for patients tested with a minimum of 3-, 5-, 14-, and 25-gene panels, respectively. These data suggest a striking concordance between the PIP scores and the EAGDIs found by gene panel testing. The ability to identify patients most likely to benefit from PGx testing has the potential to reduce health care costs, enable patient access to personalized medicine, and ultimately improve drug efficacy and safety.

Moving Pharmacogenetics Into Practice: It's All About the Evidence!

The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.