The Outlier in All of Us: Why Implementing Pharmacogenomics Could Matter for Everyone

Optimus-Era Dose Finding for Rare Cancers

SUMMARY

Advances in cancer biology and diagnostics have led to the recognition of a multitude of rare cancer subtypes, emphasizing the pressing need for strategies to accelerate drug development for patients with these cancers. This paper addresses the unique challenges of dose finding in trials that accrue small numbers of patients with rare cancers; strategies for dose optimization are proposed, in line with evolving approaches to dose determination in the age of the US Food and Drug Administration's Project Optimus.

ACE Phenotyping in Human Blood and Tissues: Revelation of ACE Outliers and Sex Differences in ACE Sialylation

Angiotensin-converting enzyme (ACE) metabolizes a number of important peptides participating in blood pressure regulation and vascular remodeling. Elevated ACE expression in tissues (which is generally reflected by blood ACE levels) is associated with an increased risk of cardiovascular diseases. Elevated blood ACE is also a marker for granulomatous diseases. Decreased blood ACE activity is becoming a new risk factor for Alzheimer's disease. We applied our novel approach-ACE phenotyping-to characterize pairs of tissues (lung, heart, lymph nodes) and serum ACE in 50 patients. ACE phenotyping includes (1) measurement of ACE activity with two substrates (ZPHL and HHL); (2) calculation of the ratio of hydrolysis of these substrates (ZPHL/HHL ratio); (3) determination of ACE immunoreactive protein levels using mAbs to ACE; and (4) ACE conformation with a set of mAbs to ACE. The ACE phenotyping approach in screening format with special attention to outliers, combined with analysis of sequencing data, allowed us to identify patient with a unique ACE phenotype related to decreased ability of inhibition of ACE activity by albumin, likely due to competition with high CCL18 in this patient for binding to ACE. We also confirmed recently discovered gender differences in sialylation of some glycosylation sites of ACE. ACE phenotyping is a promising new approach for the identification of ACE phenotype outliers with potential clinical significance, making it useful for screening in a personalized medicine approach.

Knowledge, perceptions, and attitudes toward pharmacogenomics among pharmacists and pharmacy students: A systematic review

Background and Aims

Pharmacists have been recognized as one of the most qualified healthcare professionals in the clinical implementation of pharmacogenomics, yet its widespread implementation in clinical pharmacy practice has remained limited. The review aims to systematically investigate knowledge, perceptions, and attitudes toward pharmacogenomics among pharmacists and pharmacy students to inform the future delivery of pharmacogenomics education programs.

Methods

PubMed, MEDLINE, Embase, Scopus, and the International Pharmaceutical Abstracts were searched up to May 17, 2022. Studies were selected if they included data on pharmacists' or pharmacy students' knowledge, perception, or attitude about pharmacogenomics and were published in a peer-reviewed, English-language journal with full-text availability. Any published study not deemed original research was excluded. All included studies were critically appraised using the Center for Evidence-Based Management's critical appraisal tools. The data were descriptively analyzed and presented based on pharmacists' and pharmacy students' knowledge/awareness, perception/attitudes toward pharmacogenomic (PGx), confidence in using or interpreting PGx testing results, and their desire to get further PGx education or their most preferred method of further education.

Results

A combined total of 12,430 pharmacists and pharmacy students from 26 countries are represented in the 52 included studies. Despite overwhelmingly positive attitudes and perceptions toward pharmacogenomics among pharmacists and pharmacy students, an overall lack of adequate knowledge and confidence was found. The review also found a strong desire for further pharmacogenomics education among pharmacists and pharmacy students.

Conclusion

Pharmacists and pharmacy students have positive perceptions and attitudes toward pharmacogenomics, which is hindered by a lack of knowledge and confidence. However, inadequate control for confounders, limited representativeness of the studied population or region, and small sample sizes diminish the generalizability of the review results. Knowledge and confidence could be improved through enhanced delivery of pharmacogenomic courses within the pharmacy curriculum and continuing education programs.

Clinical Utility of Pharmacogenomic Data Collected by a Health-System Biobank to Predict and Prevent Adverse Drug Events

INTRODUCTION

Medication-related harm represents a significant issue for patient safety and quality of care. One strategy to avoid preventable adverse drug events is to utilize patient-specific factors such as pharmacogenomics (PGx) to individualize therapy.

OBJECTIVE

We measured the number of patients enrolled in a health-system biobank with actionable PGx results who received relevant medications and assessed the incidence of adverse drug events (ADEs) that might have been prevented had the PGx results been used to inform prescribing.

METHODS

Patients with actionable PGx results in the following four genes with Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines were identified: HLA-A*31:01, HLA-B*15:02, TPMT, and VKORC1. The patients who received interacting medications (carbamazepine, oxcarbazepine, thiopurines, or warfarin) were identified, and electronic health records were reviewed to determine the incidence of potentially preventable ADEs.

RESULTS

Of 36,424 patients with PGx results, 2327 (6.4%) were HLA-A*31:01 positive; 3543 (9.7%) were HLA-B*15:02 positive; 2893 (7.9%) were TPMT intermediate metabolizers; and 4249 (11.7%) were homozygous for the VKORC1 c.1639 G>A variant. Among patients positive for one of the HLA variants who received carbamazepine or oxcarbazepine (n = 92), four (4.3%) experienced a rash that warranted drug discontinuation. Among the TPMT intermediate metabolizers who received a thiopurine (n = 56), 11 (19.6%) experienced severe myelosuppression that warranted drug discontinuation. Among patients homozygous for the VKORC1 c.1639 G>A variant who received warfarin (n = 379), 85 (22.4%) experienced active bleeding and/or international normalized ratio (INR) > 5 that warranted drug discontinuation or dose reduction.

CONCLUSION

Patients with actionable PGx results from a health-system biobank who received relevant medications experienced predictable ADEs. These ADEs may have been prevented if the patients' PGx results were available in the electronic health record with clinical decision support prior to prescribing.

Analysis of comprehensive pharmacogenomic profiling to impact in-hospital prescribing

INTRODUCTION

In-hospital adverse medication events result in increased morbidity and mortality. Many implicated drugs carry pharmacogenomic information. We hypothesized that comprehensive pre-emptive pharmacogenomic profiling could have high relevance for in-hospital prescribing.

PATIENTS AND METHODS

We retrospectively analyzed the in-hospital medications of a genotyped outpatient cohort admitted at our institution from 2012 to 2015. The endpoints were medication changes (new medications initiated, dose adjustments, or medications discontinued) involving drugs with pharmacogenomic annotations from three sources: Clinical Pharmacogenetics Implementation Consortium guidance, Food and Drug Administration label information, and drugs with clinical decision supports in our institutional pharmacogenomic Genomic Prescribing System.

RESULTS

Of 867 genotyped outpatients, 20 were hospitalized (mean: 78.2 years, 65% male). This hospitalized cohort was significantly older (78.2 vs. 61.3 years, P<0.0001) and took more medications (8.9 vs. 5.0 medications, P<0.0001). Out of 159 medication changes made, most (67.9%) were new medications (average: 2.5/hospitalization) with one-third of these having clinically annotated pharmacogenomic information. Half of all hospitalizations involved at least one pharmacogenomic medication. Over half (55%) of the hospitalized cohort was newly prescribed at least one of eight key pharmacogenomic medications, including high-risk drugs such as clopidogrel, codeine, and warfarin.

CONCLUSION

Our study suggested that older patients and those with polypharmacy were at increased risk for hospitalizations, where many new prescriptions included frequently used pharmacogenomic drugs. Targeting this group for pre-emptive genotyping would facilitate the delivery of highly relevant information to inform inpatient prescribing.

Estimated nationwide impact of implementing a preemptive pharmacogenetic panel approach to guide drug prescribing in primary care in The Netherlands

BACKGROUND

Pharmacogenetics (PGx) is currently implemented in hospitals to optimize therapy with high-risk drugs. However, many drugs with dosing recommendations from the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium are used in primary care. Actionable phenotypes for the genes covered in these guidelines are common with estimates ranging from 85 to 95% of the population carrying at least one actionable phenotype. The goal of this study was to estimate the clinical impact of implementation of an upfront panel-based pharmacogenetic screening for eight genes related to drugs used in primary care for 2016.

METHODS

For this study, dispensing data concerning first prescription for the period January 1-December 31, 2016, were combined with frequency data obtained in the "Implementation of Pharmacogenetics into Primary Care Project" (IP3) study to estimate the occurrence of actionable gene-drug pairs in daily practice in community pharmacies.

RESULTS

In 23.6% of all new prescriptions of 45 drugs (n = 856,002 new prescriptions/year), an actionable gene-drug interaction (GDI) was present according to the guidelines of the Dutch Pharmacogenetics Working Group. More importantly, these GDIs would result in a dose adjustment or switch to another drug in 5.4% of all new prescriptions.

CONCLUSIONS

Consequently, with an anticipated near future where healthcare professionals will be regularly confronted with PGx test results, adjusting pharmacotherapy based on this information will become a routine task in healthcare.

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Pharmacogenomics-Based Point-of-Care Clinical Decision Support Significantly Alters Drug Prescribing

Changes in behavior are necessary to apply genomic discoveries to practice. We prospectively studied medication changes made by providers representing eight different medicine specialty clinics whose patients had submitted to preemptive pharmacogenomic genotyping. An institutional clinical decision support (CDS) system provided pharmacogenomic results using traffic light alerts: green = genomically favorable, yellow = genomic caution, red = high risk. The influence of pharmacogenomic alerts on prescribing behaviors was the primary endpoint. In all, 2,279 outpatient encounters were analyzed. Independent of other potential prescribing mediators, medications with high pharmacogenomic risk were changed significantly more often than prescription drugs lacking pharmacogenomic information (odds ratio (OR) = 26.2 (9.0-75.3), P < 0.0001). Medications with cautionary pharmacogenomic information were also changed more frequently (OR = 2.4 (1.7-3.5), P < 0.0001). No pharmacogenomically high-risk medications were prescribed during the entire study when physicians consulted the CDS tool. Pharmacogenomic information improved prescribing in patterns aimed at reducing patient risk, demonstrating that enhanced prescription decision-making is achievable through clinical integration of genomic medicine.

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.