Translating pharmacogenomics into clinical decisions: do not let the perfect be the enemy of the good

Prescription Patterns and Relationship to Pharmacogenomics Testing in the Military Health System

INTRODUCTION

Clinical utilization of pharmacogenomics (PGx) testing is highly institutionally dependent, and little information is known about provider practices of PGx testing in the Military Health System (MHS). In this study, we aimed to characterize Clinical Pharmacogenetics Implementation Consortium (CPIC) actionable prescription (Rx) patterns and their temporal relationship with PGx testing in the MHS.

METHODS

Using data from the Military Health System Management Analysis and Reporting Tool (M2) database, this retrospective cohort study included all patients receiving at least one PGx test and at least one CPIC actionable Rx from January 2015 to August 2020 (845 patients, 1,471 PGx, 7,725 index CPIC actionable Rxs). Rx patterns and temporal relationships with PGx testing were characterized via descriptive statistics. Binomial regression was used to determine which patient and provider characteristics were associated with a patient receiving a PGx test within 30 days of an index Rx.

RESULTS

Patients had a median of 9 index CPIC actionable Rx's (range 1-26). Pain medications were most commonly prescribed (N = 794, 94% patients with at least 1 Rx). However, pain medication had the lowest Rx-PGx match rate (40%) compared to an average of 62% Rx-PGx match rate for all CPIC drugs. Antidepressants were also commonly prescribed (N = 668, 79.1% patients with at least 1 Rx), and antidepressants had the highest Rx-PGx match rate of 86.7%. A minority of providers (20%, N = 249) ordered the majority of PGx tests (86.1%, N = 1,266) and only 8.3% of PGx tests (N = 398) matched to a CPIC actionable drug within 30 days of the test (defined by Rxs ordered within 30 days before or after the PGx test). However, approximately 39.8% of patients (N = 317) had at least one drug match to a PGx test within 30 days. The largest predictor of whether a patient received a PGx test within 30 days of any index Rx was whether or not a specific psychiatry provider ordered the PGx test (odds ratio; OR 3.7, 95% CI 2.13-6.54, P < 0.001). Neither the CPIC level of evidence nor FDA PGx actionable or informative labels had a significant effect on PGx test timing.

CONCLUSIONS

PGx testing was generally limited to high Rx-drug users and was found to be an under-utilized resource. PGx testing did not typically follow CPIC guidelines. Implementing PGx testing protocols, simplifying PGx test-ordering by incorporating at minimum CYP2D6, CYP2C19, and CYP2C9 into PGx-testing panels, and unifying providers' PGx knowledgebase in the MHS are feasible and would improve the clinical utilization of PGx tests in the MHS.

Pharmacogenomic testing in paediatrics: clinical implementation strategies

Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited.

As with most paediatric pharmacological studies, there are well‐recognised barriers to obtaining high‐quality PGx evidence, particularly when patient numbers may be small, and off‐label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential.

This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences.

Improving the evidence base demonstrating the clinical utility and cost‐effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.

Use of Pharmacogenomics to Guide Proton Pump Inhibitor Therapy in Clinical Practice

Prescribing the right medication, at the right dose, to the right patient is the goal of every physician. Pharmacogenomic information is an emerging tool that can be used to deliver precision medicine. In this review, we discuss the pharmacogenomics of available PPIs, racial differences of CYP2C19 and how PPI pharmacogenomics affects the treatment of common gastrointestinal diseases. We also provide practical guidance on when to order pharmacogenomic testing, which test to order, and how to modify treatment based on published guidelines.

PharmVIP: A Web-Based Tool for Pharmacogenomic Variant Analysis and Interpretation

The increasing availability of next generation sequencing (NGS) for personal genomics could promote pharmacogenomics (PGx) discovery and application. However, current tools for analysis and interpretation of pharmacogenomic variants from NGS data are inadequate, as none offer comprehensive analytic functions in a simple, web-based platform. In addition, no tools exist to analyze human leukocyte antigen (HLA) genes for determining potential risks of immune-mediated adverse drug reaction (IM-ADR). We describe PharmVIP, a web-based PGx tool, for one-stop comprehensive analysis and interpretation of genome-wide variants obtained from NGS platforms. PharmVIP comprises three main interpretation modules covering analyses of pharmacogenes involved in pharmacokinetics, pharmacodynamics and IM-ADR. The Guideline module provides Clinical Pharmacogenetics Implementation Consortium (CPIC) drug guideline recommendations based on the translation of genotypic data in genes having guidelines. The HLA module reports HLA genotypes, potential adverse drug reactions, and the relevant drug guidelines. The Pharmacogenes module is employed for prioritizing variants according to variant effect on gene function. Detailed, customizable reports are provided as exportable files and as an interactive web version. PharmVIP is a new integrated NGS workflow for the PGx community to facilitate discovery and clinical application.

Building an information system to facilitate pharmacogenomics clinical translation with clinical decision support

Pharmacogenomics clinical decision support (PGx-CDS) is an important tool to incorporate PGx information into existing clinical workflows and facilitate PGx clinical translation. However, due to the lack of a computable formalization to represent the primary PGx knowledge, the complexity of genomics information and the lag of current commercial electronic health record (EHR) system for precision medicine, it is difficult to develop computerized PGx-CDS. Therefore, we explored a novel approach to build an information system, named the Pharmacogenomics Clinical Translation Platform (PCTP), for PGx clinical implementation. The PCTP can represent, store, and manage the primary PGx knowledge in a structured and computable format. Moreover, it has the potential to provide various PGx-CDS services and simplify the integration of PGx-CDS into EHRs.

Pharmacogenomics: A road ahead for precision medicine in psychiatry

Psychiatric genomics is providing insights into the nature of psychiatric conditions that in time should identify new drug targets and improve patient care. Less attention has been paid to psychiatric pharmacogenomics research, despite its potential to deliver more rapid change in clinical practice and patient outcomes. The pharmacogenomics of treatment response encapsulates both pharmacokinetic ("what the body does to a drug") and pharmacodynamic ("what the drug does to the body") effects. Despite early optimism and substantial research in both these areas, they have to date made little impact on clinical management in psychiatry. A number of bottlenecks have hampered progress, including a lack of large-scale replication studies, inconsistencies in defining valid treatment outcomes across experiments, a failure to routinely incorporate adverse drug reactions and serum metabolite monitoring in study designs, and inadequate investment in the longitudinal data collections required to demonstrate clinical utility. Nonetheless, advances in genomics and health informatics present distinct opportunities for psychiatric pharmacogenomics to enter a new and productive phase of research discovery and translation.

Engaging pharmacogenomics in pain management and opioid selection

Opioid misuse and mismanagement has been a public health crisis for several years. Pharmacogenomics (PGx) has been proposed as another tool to enhance opioid selection and optimization, with recent studies demonstrating successful implementation and outcomes. However, broad engagement with PGx for opioid management is presently limited. The purpose of this article is to highlight a series of barriers to PGx implementation within the specific context of opioid management. Areas of advancement needed for more robust pharmacogenomic engagement with opioids will be discussed, including clinical and economic research needs, education and training needs, policy and public health considerations, as well as legal and ethical issues. Continuing efforts to address these issues may help to further operationalize PGx toward improving opioid use.

Pharmacist-Led Medication Evaluation Considering Pharmacogenomics and Drug-Induced Phenoconversion in the Treatment of Multiple Comorbidities: A Case Report

Pharmacogenomic (PGx) information can guide drug and dose selection, optimize therapy outcomes, and/or decrease the risk of adverse drug events (ADEs). This report demonstrates the impact of a pharmacist-led medication evaluation, with PGx assisted by a clinical decision support system (CDSS), of a patient with multiple comorbidities. Following several sub-optimal pharmacotherapy attempts, PGx testing was recommended. The results were integrated into the CDSS, which supported the identification of clinically significant drug–drug, drug–gene, and drug–drug–gene interactions that led to the phenoconversion of cytochrome P450. The pharmacist evaluated PGx results, concomitant medications, and patient-specific factors to address medication-related problems. The results identified the patient as a CYP2D6 intermediate metabolizer (IM). Duloxetine-mediated competitive inhibition of CYP2D6 resulted in phenoconversion, whereby the patient’s CYP2D6 phenotype was converted from IM to poor metabolizer for CYP2D6 co-medication. The medication risk score suggested a high risk of ADEs. Recommendations that accounted for PGx and drug-induced phenoconversion were accepted. After 1.5 months, therapy changes led to improved pain control, depression status, and quality of life, as well as increased heart rate, evidenced by patient-reported improved sleep patterns, movement, and cognition. This case highlights the pharmacist’s role in using PGx testing and a CDSS to identify and mitigate medication-related problems to optimize medication regimen and medication safety.

Applying Next-Generation Sequencing Platforms for Pharmacogenomic Testing in Clinical Practice

Pharmacogenomics (PGx) studies the use of genetic data to optimize drug therapy. Numerous clinical centers have commenced implementing pharmacogenetic tests in clinical routines. Next-generation sequencing (NGS) technologies are emerging as a more comprehensive and time- and cost-effective approach in PGx. This review presents the main considerations for applying NGS in guiding drug treatment in clinical practice. It discusses both the advantages and the challenges of implementing NGS-based tests in PGx. Moreover, the limitations of each NGS platform are revealed, and the solutions for setting up and management of these technologies in clinical practice are addressed.

Applications for pharmacogenomics in pharmacy practice: A scoping review

BACKGROUND

Pharmacogenomics (PGx) can provide valuable pharmacokinetic and pharmacodynamic information for the pharmacist's assessment of drug therapy, especially within medication therapy management (MTM) services. However, no review has comprehensively mapped the pharmacists' use of PGx in practice-based research. Doing so would allow future researchers, practitioners, and policy-makers to identify the ideal populations and settings for PGx implementation within the pharmacy.

OBJECTIVE

The purpose of this review is to identify the evidence to date of PGx use in pharmacy practice.

METHODS

A scoping review was conducted to find all studied non-oncologic pharmacy practices incorporating PGx testing. Search terms were applied to 5 databases and relevant journals. Characteristics of patients, pharmacy settings, genetic tests, and outcomes were summarized to determine models most likely to benefit patients.

RESULTS

The search identified 43 studies on the use of PGx by pharmacists published between 2007 and 2020. CYP2C19 testing with antiplatelets was the most studied model, found in both community and institutional settings. It also was the most actionable test: approximately 30% of patients have polymorphisms indicating a need for alternative antiplatelets, and identifying these patients can reduce morbidity and mortality by more than 50%. As technology shifts, broader studies using multi-gene panel tests within MTM demonstrate an approximate 50% decrease in emergency visits and hospitalizations in elderly polypharmacy patients. Clinical benefit or drug-gene interactions are also found in other cardiovascular, psychiatric, analgesic, and gastrointestinal indications. No evaluations of actual costs or of pharmacist prescribing within pharmacy-based PGx have been performed. Facilitators towards successful PGx implementation included pharmacist education, collaboration with other healthcare providers, and the use of clinical decision software.

CONCLUSIONS

Pharmacogenomic testing has demonstrated feasibility and improved medication outcomes in pharmacy practice, including in the community pharmacy. Further PGx research should be directed towards pharmacist prescribing, pharmacist education, and pharmacoeconomics.

Genomewide Association Studies in Pharmacogenomics

The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.

A Systematic Review of Parkinson's Disease Pharmacogenomics: Is There Time for Translation into the Clinics?

BACKGROUND

Parkinson's disease (PD) is the second most frequent neurodegenerative disease, which creates a significant public health burden. There is a challenge for the optimization of therapies since patients not only respond differently to current treatment options but also develop different side effects to the treatment. Genetic variability in the human genome can serve as a biomarker for the metabolism, availability of drugs and stratification of patients for suitable therapies. The goal of this systematic review is to assess the current evidence for the clinical translation of pharmacogenomics in the personalization of treatment for Parkinson's disease.

METHODS

We performed a systematic search of Medline database for publications covering the topic of pharmacogenomics and genotype specific mutations in Parkinson's disease treatment, along with a manual search, and finally included a total of 116 publications in the review.

RESULTS

We analyzed 75 studies and 41 reviews published up to December of 2020. Most research is focused on levodopa pharmacogenomic properties and catechol-O-methyltransferase (COMT) enzymatic pathway polymorphisms, which have potential for clinical implementation due to changes in treatment response and side-effects. Likewise, there is some consistent evidence in the heritability of impulse control disorder via Opioid Receptor Kappa 1 (OPRK1), 5-Hydroxytryptamine Receptor 2A (HTR2a) and Dopa decarboxylase (DDC) genotypes, and hyperhomocysteinemia via the Methylenetetrahydrofolate reductase (MTHFR) gene. On the other hand, many available studies vary in design and methodology and lack in sample size, leading to inconsistent findings.

CONCLUSIONS

This systematic review demonstrated that the evidence for implementation of pharmacogenomics in clinical practice is still lacking and that further research needs to be done to enable a more personalized approach to therapy for each patient.

Pharmacogenomics research and its clinical implementation in Thailand: Lessons learned from the resource-limited settings

Several barriers present challenges to implementing pharmacogenomics into practice. This review will provide an overview of the current pharmacogenomics practices and research in Thailand, address the challenges and lessons learned from delivering clinical pharmacogenomic services in Thailand, emphasize the pharmacogenomics implementation issues that must be overcome, and identify current pharmacogenomic initiatives and plans to facilitate clinical implementation of pharmacogenomics in Thailand. Ever since the pharmacogenomics research began in 2004 in Thailand, a multitude of pharmacogenomics variants associated with drug responses have been identified in the Thai population, such as HLA-B∗15:02 for carbamazepine and oxcarbazepine, HLA-B∗58:01 for allopurinol, HLA-B∗13:01 for dapsone and cotrimoxazole, CYP2B6 variants for efavirenz, CYP2C9∗3 for phenytoin and warfarin, CYP3A5∗3 for tacrolimus, and UGT1A1∗6 and UGT1A1∗28 for irinotecan, etc. The future of pharmacogenomics guided therapy in clinical settings across Thailand appears promising because of the availability of evidence of clinical validity of the pharmacogenomics testing and support for reimbursement of pharmacogenomics testing.

Assessment of the Implementation of Pharmacogenomic Testing in a Pediatric Tertiary Care Setting

IMPORTANCE

Pharmacogenomic (PGx) testing provides preemptive pharmacotherapeutic guidance regarding the lack of therapeutic benefit or adverse drug reactions of PGx targeted drugs. Pharmacogenomic information is of particular value among children with complex medical conditions who receive multiple medications and are at higher risk of developing adverse drug reactions.

OBJECTIVES

To assess the implementation outcomes of a PGx testing program comprising both a point-of-care model that examined targeted drugs and a preemptive model informed by whole-genome sequencing that evaluated a broad range of drugs for potential therapy among children in a pediatric tertiary care setting.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study was conducted at The Hospital for Sick Children in Toronto, Ontario, from January 2017 to September 2020. Pharmacogenomic analyses were performed among 172 children who were categorized into 2 groups: a point-of-care cohort and a preemptive cohort. The point-of-care cohort comprised 57 patients referred to the consultation clinic for planned therapy with PGx targeted drugs and/or for adverse drug reactions, including lack of therapeutic benefit, after the receipt of current or past medications. The preemptive cohort comprised 115 patients who received exploratory whole-genome sequencing-guided PGx testing for their heart conditions from the cardiac genome clinic at the Ted Rogers Centre for Heart Research.

EXPOSURES

Patients received PGx analysis of whole-genome sequencing data and/or multiplex genotyping of 6 pharmacogenes (CYP2C19, CYP2C9, CYP2D6, CYP3A5, VKORC1, and TPMT) that have established PGx clinical guidelines.

MAIN OUTCOMES AND MEASURES

The number of patients for whom PGx test results warranted deviation from standard dosing regimens.

RESULTS

A total of 172 children (mean [SD] age, 8.5 [5.6] years; 108 boys [62.8%]) were enrolled in the study. In the point-of-care cohort, a median of 2 target genes (range, 1-5 genes) were investigated per individual, with CYP2C19 being the most frequently examined; genotypes in 21 of 57 children (36.8%) were incompatible with standard treatment regimens. As expected from population allelic frequencies, among the 115 children in the whole-genome sequencing-guided preemptive cohort, 92 children (80.0%) were recommended to receive nonstandard treatment regimens for potential drug therapies based on their 6-gene pharmacogenetic profile.

CONCLUSIONS AND RELEVANCE

In this cohort study, among both the point-of-care and preemptive cohorts, the multiplex PGx testing program provided dosing recommendations that deviated from standard regimens at an overall rate that was similar to the population frequencies of relevant variants.

Towards population-specific pharmacogenomics in the era of next-generation sequencing

Pharmacogenomics (PGx) has essential roles in identifying optimal drug responders, optimizing dosage regimens and avoiding adverse events. Population-specific therapeutic interventions that tackle the genetic root causes of clinical outcomes are an important precision medicine strategy. In this perspective, we discuss next-generation sequencing genotyping and its significance for population-specific PGx applications. We emphasize the potential of NGS for preemptive pharmacogenotyping, which is crucial to population-specific clinical studies and patient care. We also provide examples that use publicly available population-based genomics data for population-specific PGx studies. Last, we discuss the remaining challenges and regulatory efforts towards improvements in this field.

Clinical pharmacogenomics in action: design, assessment and implementation of a novel pharmacogenetic panel supporting drug selection for diseases of the central nervous system (CNS)

Background

Pharmacogenomics describes the link between gene variations (polymorphisms) and drug responses. In view of the implementation of precision medicine in personalized healthcare, pharmacogenetic tests have recently been introduced in the clinical practice. However, the translational aspects of such tests have been limited due to the lack of robust population-based evidence.

Materials

In this paper we present a novel pharmacogenetic panel (iDNA Genomics-PGx–CNS or PGx–CNS), consisting of 24 single nucleotide polymorphisms (SNPs) on 13 genes involved in the signaling or/and the metabolism of 28 approved drugs currently administered to treat diseases of the Central Nervous System (CNS). We have tested the PGx–CNS panel on 501 patient-derived DNA samples from a southeastern European population and applied biostatistical analyses on the pharmacogenetic associations involving drug selection, dosing and the risk of adverse drug events (ADEs).

Results

Results reveal the occurrences of each SNP in the sample and a strong correlation with the European population. Nonlinear principal component analysis strongly indicates co-occurrences of certain variants. The metabolization efficiency (poor, intermediate, extensive, ultra-rapid) and the frequency of clinical useful pharmacogenetic, associations in the population (drug relevance), are also described, along with four exemplar clinical cases illustrating the strong potential of the PGx–CNS panel, as a companion diagnostic assay. It is noted that pharmacogenetic associations involving copy number variations (CNVs) or the HLA gene were not included in this analysis.

Conclusions

Overall, results illustrate that the PGx–CNS panel is a valuable tool supporting therapeutic medical decisions, urging its broad clinical implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02816-3.

Prospects for personalization of depression treatment with genome sequencing

The effectiveness of antidepressants in the treatment of major depressive disorder varies considerably between patients. With these interindividual differences and a number of antidepressants to choose from, the first choice of treatment often fails to produce improvement in the patient's condition. A substantial part of the variation in response to antidepressants can be explained by genetic factors. Accordingly, variants related to drug metabolism in two pharmacogenes, CYP2D6 and CYP2C19, have already been translated into guidelines for antidepressant prescriptions. The role of variants in other genes that influence antidepressant responses is not yet understood. Furthermore, rare and individual variants account for a substantial part of genetic differences in antidepressant efficacy. Recent years have brought a tremendous increase in the accessibility of genome sequencing in terms of data availability and its clinical use. In this review, we summarize recent developments and current issues in the personalization of major depressive disorder treatment through pharmacogenomics.

A retrospective analysis of actionable pharmacogenetic/genomic biomarker language in FDA labels

The primary goal of precision medicine is to maximize the benefit‐risk relationships for individual patients by delivering the right drug to the right patients at the right dose. To achieve this goal, it has become increasingly important to assess gene‐drug interactions (GDIs) in clinical settings. The US Food and Drug Administration (FDA) periodically updates the table of pharmacogenetic/genomic (PGx) biomarkers in drug labeling on their website. As described herein, an effort was made to categorize various PGx biomarkers covered by the FDA‐PGx table into certain groups. There were 2 major groups, oncology molecular targets (OMT) and drug‐metabolizing enzymes and transporters (DMETs), which constitute ~70% of all biomarkers (~33% and ~35%, respectively). These biomarkers were further classified whether their labeling languages could be actionable in clinical practice. For OMT biomarkers, ~70% of biomarkers are considered actionable in clinical practice as they are critical for the selection of appropriate drugs to individual patients. In contrast, ~30% of DMET biomarkers are considered actionable for the dose adjustments or alternative therapies in specific populations, such as CYP2C19 and CYP2D6 poor metabolizers. In addition, the GDI results related to some of the other OMT and DMET biomarkers are considered to provide valuable information to clinicians. However, clinical GDI results on the other DMET biomarkers can possibly be used more effectively for dose recommendation. As the labels of some drugs already recommend the precise doses in specific populations, it will be desirable to have clear language for dose recommendation of other (or new) drugs if appropriate.

PharmaKU: A Web-Based Tool Aimed at Improving Outreach and Clinical Utility of Pharmacogenomics

With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug–genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive easy-to-use interface. PharmaKU can help to overcome several hurdles posed by previous pharmacogenomics tools, including input in hg38 format only, while hg19/GRCh37 is now the most popular reference genome assembly among clinicians and geneticists, as well as the lack of clinical recommendations and other pertinent dosage-related information. This tool extracts genetic variants from nine well-annotated pharmacogenes (for which diplotype to phenotype information is available) from whole genome variant files and uses Stargazer software to assign diplotypes and apply prescribing recommendations from pharmacogenomic resources. The tool is wrapped with a user-friendly web interface, which allows for choosing hg19 or hg38 as the reference genome version and reports results as a comprehensive PDF document. PharmaKU is anticipated to enable bench to bedside implementation of pharmacogenomics knowledge by bringing precision medicine closer to a clinical reality.

Strategies to Improve the Clinical Outcomes for Direct-to-Consumer Pharmacogenomic Tests

Direct-to-consumer genetic tests (DTC-GT) have become a bridge between marketing and traditional healthcare services. After earning FDA endorsement for such facilities, several fast-developing companies started to compete in the related area. Pharmacogenomic (PGx) tests have been introduced as potentially one of the main medical services of such companies. Most of the individuals will be interested in finding out about the phenotypic consequences of their genetic variants and molecular risk factors against diverse medicines they take or will take later. Direct-to-consumer pharmacogenomic tests (DTC-PT) is still in its young age, however it is expected to expand rapidly through the industry in the future. The result of PGx tests could be considered as the main road toward the implementation of personalized and precision medicine in the clinic. This narrative critical review study provides a descriptive overview on DTC-GT, then focuses on DTC-PT, and also introduces and suggests the potential approaches for improving the clinical related outcomes of such tests on healthcare systems.

Knowledge, perception, and confidence of hospital pharmacists toward pharmacogenetics in Jeddah, Kingdom of Saudi Arabia

Background

Integrating pharmacogenetics (PGx) testing into clinical practice leads to personalized medicine, which improves treatments’ efficacy and safety. Successful implementation of such a service requires sufficient knowledge, perception, and self-confidence among healthcare providers, especially pharmacists.

Objectives

To evaluate governmental hospital pharmacists’ knowledge, perception, and self-confidence toward PGx testing in Jeddah, Kingdom of Saudi Arabia.

Method

This cross-sectional study was conducted using previously validated questionnaire. Pharmacists working in five randomly selected general governmental hospitals in Jeddah between August and October 2019 were interviewed. Comparative and descriptive analyses were used to analyze the data, and the significance level was at P-value < 0.05.

Results

A total of 119 pharmacists with a mean (±SD) age of 31.2 (±5.05) years were included with a response rate of 79.3%. The average total mean (±SD) score for PGx knowledge-based questions was low (2.4 ± 1.09 out of 5). Most of the participants, with a total mean score of (10.1 ± 1.6 out of 12), revealed a positive perception toward PGx testing and its implications. A moderate self-confidence score for utilizing PGx testing (4.3 ± 2.3 out of 8) was observed among the participants. Pharmacists who had completed postgraduate studies had a statistically higher mean knowledge score (P = 0.006) compared with pharmacists with undergraduate degrees.

Conclusion

Governmental hospital pharmacists have limited knowledge and understanding about PGx testing; however, the majority expressed a high level of awareness and agreed that PGx testing is a valuable tool for enhancing drug efficacy and safety. The study also highlighted the importance of improving pharmacists’ knowledge about PGx testing, which will help them in implementing such a valuable service into their clinical practice in Saudi hospitals.

Potential of whole-genome sequencing-based pharmacogenetic profiling

Pharmacogenetics represents a major driver of precision medicine, promising individualized drug selection and dosing. Traditionally, pharmacogenetic profiling has been performed using targeted genotyping that focuses on common/known variants. Recently, whole-genome sequencing (WGS) is emerging as a more comprehensive short-read next-generation sequencing approach, enabling both gene diagnostics and pharmacogenetic profiling, including rare/novel variants, in a single assay. Using the example of the pharmacogene CYP2D6, we demonstrate the potential of WGS-based pharmacogenetic profiling as well as emphasize the limitations of short-read next-generation sequencing. In the near future, we envision a shift toward long-read sequencing as the predominant method for gene diagnostics and pharmacogenetic profiling, providing unprecedented data quality and improving patient care.

Pharmacogenetics Guidelines: Overview and Comparison of the DPWG, CPIC, CPNDS, and RNPGx Guidelines

Many studies have shown that the efficacy and risk of side effects of drug treatment is influenced by genetic variants. Evidence based guidelines are essential for implementing pharmacogenetic knowledge in daily clinical practice to optimize pharmacotherapy of individual patients. A literature search was performed to select committees developing guidelines with recommendations being published in English. The Dutch Pharmacogenetics Working Group (DPWG), the Clinical Pharmacogenetics Implementation Consortium (CPIC), the Canadian Pharmacogenomics Network for Drug Safety (CPNDS), and the French National Network (Réseau) of Pharmacogenetics (RNPGx) were selected. Their guidelines were compared with regard to the methodology of development, translation of genotypes to predicted phenotypes, pharmacotherapeutic recommendations and recommendations on genotyping. A detailed overview of all recommendations for gene-drug combinations is given. The committees have similar methodologies of guideline development. However, the objectives differed at the start of their projects, which have led to unique profiles and strengths of their guidelines. DPWG and CPIC have a main focus on pharmacotherapeutic recommendations for a large number of drugs in combination with a patient’s genotype or predicted phenotype. DPWG, CPNDS and RNPGx also recommend on performing genetic testing in daily clinical practice, with RNPGx even describing specific clinical settings or medical conditions for which genotyping is recommended. Discordances exist, however committees also initiated harmonizing projects. The outcome of a consensus project was to rename “extensive metabolizer (EM)” to “normal metabolizer (NM)”. It was decided to translate a CYP2D6 genotype with one nonfunctional allele (activity score 1.0) into the predicted phenotype of intermediate metabolizer (IM). Differences in recommendations are the result of the methodologies used, such as assessment of dose adjustments of tricyclic antidepressants. In some cases, indication or dose specific recommendations are given for example for clopidogrel, codeine, irinotecan. The following drugs have recommendations on genetic testing with the highest level: abacavir (HLA), clopidogrel (CYP2C19), fluoropyrimidines (DPYD), thiopurines (TPMT), irinotecan (UGT1A1), codeine (CYP2D6), and cisplatin (TPMT). The guidelines cover many drugs and genes, genotypes, or predicted phenotypes. Because of this and their unique features, considering the totality of guidelines are of added value. In conclusion, many evidence based pharmacogenetics guidelines with clear recommendations are available for clinical decision making by healthcare professionals, patients and other stakeholders.

[How to manage polypharmacia?]

Pharmacogenomics (PGx) is a key component of personalized medicine to improve clinical outcome of drug therapy and/or to avoid adverse drug reactions. Major efforts are currently spent internationally to implement PGx diagnostics into clinical practice. Evidence-based recommendations for dose-adjusted treatment which are established by international expert groups covering clinical and pharmacological expertise are publicly available. Clinical relevant examples for PGx diagnostics such as genetic testing for dihydropyrimidin-dehydrogenase and thiopurin-S-methyltransferase, as well as for various cytochrome P450 enzymes are summarized to promote the clinical implementation process of PGx in Germany.

Retrospective Review of Pharmacogenetic Testing at an Academic Children's Hospital

There is limited evidence to support pharmacogenetic (PGx) testing in children. We conducted a retrospective review of PGx testing among 452 patients at an academic children's hospital to determine the potential utility of PGx in diseases of childhood and to identify targets for future pediatric pharmacogenetic research. An actionable gene-drug pair associated with the 28 genes tested (Clinical Pharmacogenetics Implementation Consortium (CPIC) level A or B, Pharmacogenomics Knowledge Base (PharmGKB) level 1A or B, or US Food and Drug Administration (FDA) recommendation and a PharmGKB level) was present in 98.7% of patients. We identified 203 actionable gene-drug-diagnosis groups based on the indications for each actionable drug listed in Lexicomp. Among patients with an actionable gene-drug-diagnosis group, 49.3% had a diagnosis where the drug was a therapeutic option and PGx could be used to guide treatment selection. Among patients with an associated diagnosis, 30.9% had a prescription for the actionable drug allowing PGx guided dosing. Three genes (CYP2C19, CYP2D6, and CYP3A5) accounted for all the gene-drug-diagnosis groups with matching diagnoses and prescriptions. The most common gene-drug-diagnosis groups with matching diagnoses and prescriptions were CYP2C19-citalopram-escitalopram-depression 3.3% of patients tested; CYP2C19-dexlansoprazole-gastritis-esophagitis 3.1%; CYP2C19-omeprazole-gastritis-esophagitis 2.4%; CYP2D6-atomoxetine-attention deficit hyperactivity disorder 2.2%; and CYP2C19-citalopram-escitalopram-obsessive-compulsive disorder 1.5%. PGx could be used to guide selection of current treatment options or medication dosing in almost half (48.7%) of pediatric patients tested. Mood disorders and gastritis/esophagitis are promising targets for future study of PGx testing because of the high prevalence of these diagnoses and associated actionable gene-drug pairs in the pediatric population.

Personalized Medicine Using Cutting Edge Technologies for Genetic Epilepsies

Epilepsy is the most common chronic neurologic disorder in the world, affecting 1-2% of the population. Besides, 30% of epilepsy patients are drug-resistant. Genomic mutations seem to play a key role in its etiology and knowledge of strong effect mutations in protein structures might improve prediction and the development of efficacious drugs to treat epilepsy. Several genetic association studies have been undertaken to examine the effect of a range of candidate genes for resistance. Although, few studies have explored the effect of the mutations into protein structure and biophysics in the epilepsy field. Much work remains to be done, but the plans made for exciting developments will hold therapeutic potential for patients with drug-resistance. In summary, we provide a critical review of the perspectives for the development of individualized medicine for epilepsy based on genetic polymorphisms/mutations in light of core elements such as transcriptomics, structural biology, disease model, pharmacogenomics and pharmacokinetics in a manner to improve the success of trial designs of antiepileptic drugs.

Drug Response Pharmacogenetics for 200,000 UK Biobank Participants

Pharmacogenetics studies how genetic variation leads to variability in drug response. Guidelines for selecting the right drug and right dose for patients based on their genetics are clinically effective, but are widely unused. For some drugs, the normal clinical decision making process may lead to the optimal dose of a drug that minimizes side effects and maximizes effectiveness. Without measurements of genotype, physicians and patients may adjust dosage in a manner that reflects the underlying genetics. The emergence of genetic data linked to longitudinal clinical data in large biobanks offers an opportunity to confirm known pharmacogenetic interactions as well as discover novel associations by investigating outcomes from normal clinical practice. Here we use the UK Biobank to search for pharmacogenetic interactions among 200 drugs and 9 genes among 200,000 participants. We identify associations between pharmacogene phenotypes and drug maintenance dose as well as differential drug response phenotypes. We find support for several known drug-gene associations as well as novel pharmacogenetic interactions.

Pharmacogenomics at the Point of Care: A Community Pharmacy Project in British Columbia

In this study 180 patients were consented and enrolled for pharmacogenomic testing based on current antidepressant/antipsychotic usage. Samples from patients were genotyped by PCR, MassArray, and targeted next generation sequencing. We also conducted a quantitative, frequency-based analysis of participants’ perceptions using simple surveys. Pharmacogenomic information, including medication changes and altered dosing recommendations were returned to the pharmacists and used to direct patient therapy. Overwhelmingly, patients perceived pharmacists/pharmacies as an appropriate healthcare provider to deliver pharmacogenomic services. In total, 81 medication changes in 33 unique patients, representing 22% of all genotyped participants were recorded. We performed a simple drug cost analysis and found that medication adjustments and dosing changes across the entire cohort added $24.15CAD per patient per year for those that required an adjustment. Comparing different platforms, we uncovered a small number, 1.7%, of genotype discrepancies. We conclude that: (1). Pharmacists are competent providers of pharmacogenomic services. (2). The potential reduction in adverse drug responses and optimization of drug selection and dosing comes at a minimal cost to the health care system. (3). Changes in drug therapy, based on PGx tests, result in inconsequential changes in annual drug therapy cost with small cost increases just as likely as costs savings. (4). Pharmacogenomic services offered by pharmacists are ready for wide commercial implementation.

Practical Barriers and Facilitators Experienced by Patients, Pharmacists and Physicians to the Implementation of Pharmacogenomic Screening in Dutch Outpatient Hospital Care-An Explorative Pilot Study

Pharmacogenomics (PGx) can provide optimized treatment to individual patients while potentially reducing healthcare costs. However, widespread implementation remains absent. We performed a pilot study of PGx screening in Dutch outpatient hospital care to identify the barriers and facilitators to implementation experienced by patients (n = 165), pharmacists (n = 58) and physicians (n = 21). Our results indeed suggest that the current practical experience of healthcare practitioners with PGx is limited, that proper education is necessary, that patients want to know the exact implications of the results, that healthcare practitioners heavily rely on their computer systems, that healthcare practitioners encounter practical problems in the systems used, and a new barrier was identified, namely that there is an unclear allocation of responsibilities between healthcare practitioners about who should discuss PGx with patients and apply PGx results in healthcare. We observed a positive attitude toward PGx among all the stakeholders in our study, and among patients, this was independent of the occurrence of drug-gene interactions during their treatment. Facilitators included the availability of and adherence to Dutch Pharmacogenetics Working Group guidelines. While clinical decision support (CDS) is available and valued in our medical center, the lack of availability of CDS may be an important barrier within Dutch healthcare in general.

Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization

Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician's ability to understand the obtained results in a standardized way for each particular patient. The review aims to lead the reader through the general conception of PGx and related issues of PGx testing efficiency, personal data security, and health safety at a current clinical level.

Technologies for Pharmacogenomics: A Review

The continuous development of new genotyping technologies requires awareness of their potential advantages and limitations concerning utility for pharmacogenomics (PGx). In this review, we provide an overview of technologies that can be applied in PGx research and clinical practice. Most commonly used are single nucleotide variant (SNV) panels which contain a pre-selected panel of genetic variants. SNV panels offer a short turnaround time and straightforward interpretation, making them suitable for clinical practice. However, they are limited in their ability to assess rare and structural variants. Next-generation sequencing (NGS) and long-read sequencing are promising technologies for the field of PGx research. Both NGS and long-read sequencing often provide more data and more options with regard to deciphering structural and rare variants compared to SNV panels-in particular, in regard to the number of variants that can be identified, as well as the option for haplotype phasing. Nonetheless, while useful for research, not all sequencing data can be applied to clinical practice yet. Ultimately, selecting the right technology is not a matter of fact but a matter of choosing the right technique for the right problem.

Barriers, solutions, and effect of using pharmacogenomics data to support opioid prescribing

Opioid use and misuse are continued issues facing clinicians across all aspects of health care. As clinicians struggle to effectively manage opioid prescribing, pharmacogenomics (PGx) further offers the prescriber an improved ability to understand the potential for an individual patient's genetics to influence opioid efficacy and safety. When PGx data are available at the point of initial prescribing, clinicians can apply that data to drug therapy selection. However, barriers continue to exist relative to PGx data sharing and interpretation, which have created difficulties for widespread PGx implementation. This article briefly describes potential barriers to PGx data integration, strategies to overcome those barriers, and the potential positive effect of successful data sharing on opioid prescribing. Prescription drug monitoring programs (PDMPs) have been successfully operationalized to share controlled substance prescribing data across health care settings. Such data sharing enables clinicians to, among other things, better understand risks associated with misuse. Because a relatively limited volume of PGx data is currently pertinent to opioid prescribing, such PGx data could be added to PDMPs as a way to communicate genetic information within current technology platforms. Not only would this integrate into existing clinical workflow models where PDMP data are accessed at this point of prescribing and/or dispensing, but associated clinical guidance for PGx data interpretation in the context of opioids could be integrated into the workflow process. Such clinical decision support could be provided directly through the PDMP interface for uniformity or could be provided via systems that access PDMP data. Clinical, economic, and policy implications of the inclusion of PGx data within PDMPs are also discussed. Through harnessing PDMP for data sharing, multiple barriers to PGx implementation could be mitigated, and clinicians may have better access to PGx data to optimize opioid prescribing. DISCLOSURES: No outside funding supported this study. Bright has a patent pending related to opioid use disorder risk assessment that includes genetic information and was a collaborator on funded research projects with pharmacogenomics-related companies. Petry has been a consultant to the North Dakota Department of Health and has received grants from IGNITE I and IGNITE II (NIH), unrelated to this work. The other authors are aware of no financial conflicts of interest.

A Tutorial for Pharmacogenomics Implementation Through End-to-End Clinical Decision Support Based on Ten Years of Experience from PREDICT

Vanderbilt University Medical Center implemented pharmacogenomics (PGx) testing with the Pharmacogenomic Resource for Enhanced Decisions in Care and Treatment (PREDICT) initiative in 2010. This tutorial reviews the laboratory considerations, technical infrastructure, and programmatic support required to deliver panel-based PGx testing across a large health system with examples and experiences from the first decade of the PREDICT initiative. From the time of inception, automated clinical decision support (CDS) has been a critical capability for delivering PGx results to the point-of-care. Key features of the CDS include human-readable interpretations and clinical guidance that is anticipatory, actionable, and adaptable to changes in the scientific literature. Implementing CDS requires that structured results from the laboratory be encoded in standards-based messages that are securely ingested by electronic health records. Translating results to guidance also requires an informatics infrastructure with multiple components: (1) to manage the interpretation of raw genomic data to "star allele" results to expected phenotype, (2) to define the rules that associate a phenotype with recommended changes to clinical care, and (3) to manage and update the knowledge base. Knowledge base management is key to processing new results with the latest guidelines, and to ensure that historical genomic results can be reinterpreted with revised CDS. We recommend that these components be deployed with institutional authorization, programmatic support, and clinician education to govern the CDS content and policies around delivery.

Prevalence and types of inconsistencies in clinical pharmacogenetic recommendations among major U.S. sources

Clinical implementation of pharmacogenomics (PGx) is slow. Previous studies have identified some inconsistencies among clinical PGx recommendations, but the prevalence and types of inconsistencies have not been comprehensively analyzed among major PGx guidance sources in the U.S. PGx recommendations from the Clinical Pharmacogenetics Implementation Consortium, U.S. Food and Drug Administration drug labels, and major U.S. professional medical organizations were analyzed through May 24, 2019. Inconsistencies were analyzed within the following elements: recommendation category; whether routine screening was recommended; and the specific biomarkers, variants, and patient groups involved. We identified 606 total clinical PGx recommendations, which contained 267 unique drugs. Composite inconsistencies occurred in 48.1% of clinical PGx recommendations overall, and in 93.3% of recommendations from three sources. Inconsistencies occurred in the recommendation category (29.8%), the patient group (35.4%), and routine screening (15.2%). In conclusion, almost one-half of clinical PGx recommendations from prominent U.S. guidance sources contain inconsistencies, which can potentially slow clinical implementation.

Pharmacogenetics in psychiatric care, a call for uptake of available applications

In this narrative, we evaluate the role of pharmacogenetics in psychiatry from a pragmatic clinical perspective and address current barriers of clinical implementation of pharmacogenetics. Pharmacogenetics has been successfully implemented to improve drug therapy in several clinical areas, but not psychiatry. Yet, psychotropics account for more than one-third of the drugs for which pharmacogenetic guidelines are available and drug therapy in mental disorders is suboptimal with insufficient effectiveness and frequent adverse events. The limited application of pharmacogenetics in psychiatry is influenced by several factors; e.g. the complexity of psychotropic drug metabolism, possibly impeding the clinical understanding of the benefits of pharmacogenetics. Also, recommendations for most psychotropics classify pharmacogenetic testing only as (potentially) beneficial, not as essential, possibly because life-threatening adverse events are often not involved in these drug-gene interactions. Implementing pharmacogenetics in psychiatry could improve the current practice of time-consuming switching of therapies causing undue delays associated with worse outcomes. We expect pharmacogenetics in psychiatry to expedite with panel-based genotyping, including clinically relevant variants, which will address the complex enzymatic metabolism of psychotropic drugs. Until then, we stress that available pharmacogenetic testing should be seen as an integrated companion, not a competitor, in current clinical psychiatric care.

Post marketing surveillance of suspected adverse drug reactions through spontaneous reporting: current status, challenges and the future

BACKGROUND

To highlight the importance of spontaneous reporting programs in post marketing surveillance of medicines. Authors also aimed at providing various dimensions of spontaneous programs, including the strengths and weakness, and providing an insight on the future prospects of pharmacovigilance systems.

METHODS

Various literature related to post marketing surveillance and spontaneous reporting programs were reviewed and the relevant ones highlighting the strengths and weaknesses are summarized. A balance of information on strengths and weaknesses is listed. The health professionals' awareness regarding existing spontaneous reporting programs is highlighted. Future prospects of pharmacovigilance are discussed.

RESULTS

Though beneficial, spontaneous reporting programs encounter several limitations and difficulties in diagnosing adverse drug reaction. Under-reporting and bias are major challenges. Online signal detection tools and innovative methods are needed to strengthen the spontaneous reporting programs. We provide the various issues to be considered while depending on spontaneous reporting programs as a method of post marketing surveillance.

CONCLUSION

To strengthen the spontaneous reporting programs as an effective post marketing surveillance method, more awareness among health professionals and innovative strategies is needed. Integrating pharmacogenetic data can be a potential aspect of future pharmacovigilance.

PLAIN LANGUAGE SUMMARY

Monitoring adverse effects of marketed medicines through reporting by healthcare professionals and its challenges and way forward.

INTRODUCTION

This article highlights the importance of safety monitoring of medicines after they are launched in the market, mainly through reporting by healthcare professionals. We also highlight the strengths and weaknesses, and provide an insight on the future prospects of pharmacovigilance systems.

METHODS

Various literature related to the topic were reviewed and the relevant ones highlighting the strengths and weaknesses are summarized. A balance of information on strengths and weaknesses is listed. Health professionals' awareness regarding existing programs on reporting safety of medicines is highlighted.

RESULTS

Though beneficial, reporting of adverse effects by healthcare professionals who deal with patient lacks clarity in diagnosing the adverse effects. Under-reporting and bias are the major challenges. Online software is needed to strengthen reporting by healthcare professionals. We list the various issues to be considered while depending on healthcare professionals' reporting of adverse effects as a method of post marketing surveillance.

CONCLUSION

To strengthen medicine safety monitoring and reporting by healthcare professionals, more awareness among health professionals and innovative strategies are needed. Integrating the genetic data of patients can be beneficial in predicting adverse effects, therefore avoiding them and enhancing safe prescribing and dispensing by healthcare professionals.

National survey of physicians' perspectives on pharmacogenetic testing in solid organ transplantation

INTRODUCTION

Our objective was to evaluate physicians' perspectives on the clinical utility of pharmacogenetic (PGx) testing in kidney, liver, heart, and lung transplantation (KLHL-Tx).

METHODS

A 36-question web-based survey was developed and administered to medical and surgical directors of US KLHL-Tx centers.

RESULTS

There were 82 respondents (10% response rate). The majority were men (78%), non-Hispanic whites (70%), medical directors (72%), and kidney transplant physicians (35%). Although 78% of respondents reported having some PGx education, most reported lack of confidence in their PGx knowledge and ability to apply a PGx test. Participants reported mixed views about the clinical utility of PGx testing-most agreed with the efficacy of PGx testing, but not the benefits relative to the risks or standard of care. While 55% reported that testing was available at their institution, only 38% ordered a PGx test in the past year, most commonly thiopurine-S-methyltransferase. Physician-reported barriers to PGx implementation included uncertainty about the clinical value of PGx testing and patient financial burden.

CONCLUSION

Together, our findings suggest prospective PGx research and pilot implementation programs are needed to elucidate the clinical utility and value of PGx in KLHL-Tx. These initiatives should include educational efforts to inform the use of PGx testing.

Germline and Somatic Pharmacogenomics to Refine Rectal Cancer Patients Selection for Neo-Adjuvant Chemoradiotherapy

Neoadjuvant chemoradiotherapy (nCRT) followed by radical surgery is the standard of care for patients with Locally Advanced Rectal Cancer (LARC). Current selection for nCRT is based on clinical criteria regardless of any molecular marker. Pharmacogenomics may be a useful strategy to personalize and optimize nCRT in LARC. This review aims to summarize the most recent and relevant findings about the role of germline and somatic pharmacogenomics in the prediction of nCRT outcome in patients with LARC, discussing the state of the art of their application in the clinical practice. A systematic literature search of the PubMed database was completed to identify relevant English-language papers published up to January 2020. The chemotherapeutic backbone of nCRT is represented by fluoropyrimidines, mainly metabolized by DPD (Dihydro-Pyrimidine Dehydrogenase, DPYD). The clinical impact of testing DPYD*2A, DPYD*13, c.2846A > T and c.1236G > A-HapB3 before a fluoropyrimidines administration to increase treatment safety is widely acknowledged. Other relevant target genes are TYMS (Thymidylate Synthase) and MTHFR (Methylene-Tetrahydro-Folate Reductase), whose polymorphisms were mainly studied as potential markers of treatment efficacy in LARC. A pivotal role of a TYMS polymorphism in the gene promoter region (rs34743033) was reported and was pioneeringly used to guide nCRT treatment in a phase II study. The pharmacogenomic analysis of other pathways mostly involved in the cellular response to radiation damage, as the DNA repair and the activation of the inflammatory cascade, provided less consistent results. A high rate of somatic mutation in genes belonging to PI3K (Phosphatidyl-Inositol 3-Kinase) and MAPK (Mitogen-Activated Protein Kinase) pathways, as BRAF (V-raf murine sarcoma viral oncogene homolog B1), KRAS (Kirsten Rat Sarcoma viral oncogene homolog), NRAS (Neuroblastoma RAS viral (v-ras) oncogene homolog), PIK3CA (Phosphatidyl-Inositol-4,5-bisphosphate 3-Kinase, Catalytic Subunit Alpha), as well as TP53 (Tumor Protein 53) was reported in LARC. Their pharmacogenomic role, already defined in colorectal cancer, is under investigation in LARC with promising results concerning specific somatic mutations in KRAS and TP53, as predictors of tumor response and prognosis. The availability of circulating tumor DNA in plasma may also represent an opportunity to monitor somatic mutations in course of therapy.

Prescription patterns of outpatients and the potential of multiplexed pharmacogenomic testing

BACKGROUND

Pre-emptive pharmacogenomic (PGx) testing is potentially an efficient approach to improve drug safety and efficacy but the target population to test is unclear.

OBJECTIVES

We aim to describe the prescription pattern of PGx drugs among adult medical outpatients.

METHODS

We estimated the 5-year cumulative incidence (CI) for receiving three groups of PGx drugs using competing risks analysis: (i) all PGx drugs, (ii) PGx drugs with guidelines and (iii) PGx drugs with serious clinical effects. Comparisons of CIs were also done by patient characteristics using Gray's test.

RESULTS

The 5-year CIs of receiving any new PGx drug, PGx drug with guidelines and serious clinical effects were 42.6%, 37.3% and 13.7%, respectively. The 5-year CI of receiving any new PGx drug was higher for patients >40 years old (43.6% vs ≤40 years old 36.0%, P < 2.2 × 10^-22 ), Malays and Indians (50.3% and 49.8% vs Chinese 31.1%, P < 2.2 × 10^-22 ), those who attended one of the following four specialties at the index visit compared to other specialties (infectious diseases [46.2% vs 42.6%, P = 2.9 × 10^-4 ], psychiatry [48.3% vs 42.3%, P = 7.4 × 10^-13 ], renal [49.8% vs 40.9%, P < 2.2 × 10^-22 ], and rheumatology and immunology [54.8% vs 41.7%, P < 2.2 × 10^-22 ]) and those prescribed ≥5 drugs at index visit (51.7% vs 0-4 drugs 41.7%, P < 2.2 × 10^-22 ).

CONCLUSIONS

Medical outpatients have a substantial probability of benefiting from pre-emptive PGx testing and this is higher in certain subgroups of patients.

Pharmacogenomics of anticancer drugs: Personalising the choice and dose to manage drug response

The field of pharmacogenomics has made great strides in oncology over the last 20 years and indeed a significant number of pre-emptive genetic tests are now routinely undertaken prior to anticancer drug administration. Many of these gene-drug interactions are the fruits of candidate gene and genome-wide association studies, which have largely focused on common genetic variants (allele frequency>1%). Examples where there is clinical utility include genotyping or phenotyping for G6PD to prevent rasburicase-induced RBC haemolysis, and TPMT to prevent thiopurine-induced bone marrow suppression. Other associations such as CYP2D6 status in determining the efficacy of tamoxifen are more controversial because of contradictory evidence from different sources, which has led to variability in the implementation of testing. As genomic technology becomes ever cheaper and more accessible, we must look to the additional data our genome can provide to explain interindividual variability in anticancer drug response. Clearly genes do not act on their own and it is therefore important to investigate genetic factors in conjunction with clinical factors, interacting concomitant drug therapies and other factors such as the microbiome, which can all affect drug disposition. Taking account of all of these factors, in conjunction with the somatic genome, is more likely to provide better predictive accuracy in determining anticancer drug response, both efficacy and safety. This review summarises the existing knowledge related to the pharmacogenomics of anticancer drugs and discusses areas of opportunity for further advances in personalisation of therapy in order to improve both drug safety and efficacy.

Clinical implementation of pharmacogenetics and model-informed precision dosing to improve patient care

Providing maximal therapeutic efficacy without toxicity is a universal goal of rational drug therapy. However, substantial between-patient variability in drug response often impedes such successful treatments and brings the necessity of tailoring drug dose to individual needs for more precise therapy. In many cases plenty of patient characteristics, such as body size, genetic makeup and environmental factors, need to be taken into consideration to find the optimal dose in clinical practice. A pharmacokinetics and pharmacodynamics (PK/PD) model-informed approach offers integration of various patient information to provide an expectation of drug response and derive practical dose estimates to support clinicians' dosing decisions. Such an approach was pioneered in the late 1970s, but its broad clinical acceptance and implementation have been hampered by the lack of widespread computer technology, including user-friendly software tools. This has significantly changed in recent years. With the advent of electronic health records (EHRs) and the ubiquity of user-friendly software tools, we now experience a convergence of clinical information, pharmacogenetics, systems pharmacology and pharmacometrics, and technology. Advanced pharmacometrics research is now more appliable and implementable to improve health care. This article presents examples of successful development and implementation of pharmacogenetics-guided and PK/PD model-informed decision support to facilitate precision dosing, including the development of an EHR-embedded decision support tool. Through the integration of clinical decision support tools in EHRs, clinical pharmacometrics support can be brought directly to the clinical team and the bedside.

Influence of metabolic profiles on the safety of drug therapy in routine care in Germany: protocol of the cohort study EMPAR

INTRODUCTION

Pre-emptive testing of pharmacogenetically relevant single-nucleotide polymorphisms can be an effective tool in the prevention of adverse drug reactions and therapy resistance. However, most of the tests are not used as standard in routine care in Germany because of lacking evidence for the clinical and economical benefit and their impact on the usage of healthcare services. We address this issue by investigating the influence of pharmacogenetic profiles on the use of healthcare services over an extended period of several years using routine care data from a statutory health insurance company. The goal is to provide clinical evidence whether pre-emptive pharmacogenetic testing of metabolic profiles in routine care in Germany is beneficial and cost-effective.

METHODS AND ANALYSIS

The EMPAR (Einfluss metabolischer Profile auf die Arzneimitteltherapiesicherheit in der Routineversorgung) study is a non-interventional cohort study conducted to analyse pharmacogenetic risk factors that are important for drug therapy by means of endpoints relevant for healthcare. The analysis is based on pharmacogenetic profiles and statutory health insurance data. We perform pharmacogenetic, pharmacoepidemiological and pharmacoeconomic analyses using health care utilisation scores and machine learning techniques. Therefore, we aim to include about 10 000 patients (≥18 years) insured by the health insurance provider Techniker Krankenkasse. The study focuses on patients with prescriptions of anticoagulants and prescriptions of cholesterol-lowering drugs. Also, a screening for special pharmacogenetic characteristics will be performed in patients with at least one Y57.9! diagnosis (Complication of medical and surgical care: drug or medicament, unspecified). Outcomes include the utilisation of health insurance services, the incidence of incapacity for work and costs for drugs and treatment.

ETHICS AND DISSEMINATION

The protocol was approved by the Ethics Committee of the Medical Faculty, University of Bonn (Lfd. Nr. 339/17). The results of this research project will be published in scientific open access journals and at conferences.

TRIAL REGISTRATION NUMBER

German Clinical Trials Register, DRKS00013909.

Survey of physicians' views on the clinical implementation of pharmacogenomics-based personalized therapy

Despite quantitative increases and qualitative advances in pharmacogenomics (PGx) research, the clinical implementation of PGx-based personalized therapy has still been limited. The objective of this study was to assess physicians' self-reported knowledge of PGx-based personalized therapy, and to explore the most problematic and highest priority barriers preventing physicians from applying PGx into clinical practice under the Korean healthcare system. A 36-question survey was distributed to 53 physicians with various specialties in Korea. In the physicians' self-perceived knowledge, twenty-eight physicians (53%) reported a lack sufficient knowledge about PGx. The perceived largest barrier to clinical implementation of PGx was the high cost of PGx testing, followed by a lack of PGx education for healthcare providers or lack of clinical PGx experts. Physicians without clinical PGx experience or with indirect experience reported that the largest barrier to clinical implementation of PGx was the high cost of PGx testing, while physicians with clinical PGx experience pointed out that a lack of patients' education was the major concern, followed by a lack of PGx education for healthcare providers or lack of clinical PGx experts. The highest priority problem was reported to be a lack of actionable guidelines for drug selection and dosing using PGx. In conclusion, we should increase and expand extensive educational programs for healthcare providers and patients, and to develop and establish a clinical decision support systems for PGx-based personalized therapy in Korea.

Primary Care Prescription Drug Use and Related Actionable Drug-Gene Interactions in the Danish Population

Pharmacogenetics (PGx) aims to improve drug therapy using the individual patients' genetic make-up. Little is known about the potential impact of PGx on the population level, possibly hindering implementation of PGx in clinical care. Therefore, we investigated how many patients use actionable PGx drugs, have actionable genotypes or phenotypes and which patients could benefit the most of PGx testing. We included PGx recommendations from two international PGx consortia (Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG)). Using data from publically accessible sales information drawn from the Danish Register of Medicinal Product Statistics (MEDSTAT), we identified the number of users of actionable prescription PGx drugs among the total Danish population in 2017. We estimated actionable genotypes or phenotypes based on reported frequencies from literature. We identified 49 drug-gene interactions related to 41 unique prescription drugs. The estimated median frequency of actionable genotypes or phenotypes among prescription drug users was 25% (interquartile range 7-26%). Six of 41 drugs were used more than twice as much in women. Actionable PGx drugs were most frequently used by 45-79 year old patients (62%), followed by 25-44 year old patients (18%). Almost half of the actionable PGx drugs (19/41) were psychotropics (i.e., antidepressants, antipsychotics, or psychostimulants). PGx testing can have a substantial impact on the population, as one in four prescription drug users has an actionable genotype or phenotype and could thus benefit from PGx testing. We advocate for prospective panel-based PGx testing at the time of the first PGx drug prescription ("as needed"), with PGx results ready prior to start of the first, and all future, therapies.

Clinical implementation of pharmacogenomics via a health system-wide research biobank: the University of Colorado experience

In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.

Pharmacogenomics of Pain Management: The Impact of Specific Biological Polymorphisms on Drugs and Metabolism

PURPOSE OF REVIEW

Pain is multifactorial and complex, often with a genetic component. Pharmacogenomics is a relative new field, which allows for the development of a truly unique and personalized therapeutic approach in the treatment of pain.

RECENT FINDINGS

Until recently, drug mechanisms in humans were determined by testing that drug in a population and calculating response averages. However, some patients will inevitably fall outside of those averages, and it is nearly impossible to predict who those outliers might be. Pharmacogenetics considers a patient's unique genetic information and allows for anticipation of that individual's response to medication. Pharmacogenomic testing is steadily making progress in the management of pain by being able to identify individual differences in the perception of pain and susceptibility and sensitivity to drugs based on genetic markers. This has a huge potential to increase efficacy and reduce the incidence of iatrogenic drug dependence and addiction. The streamlining of relevant polymorphisms of genes encoding receptors, transporters, and drug-metabolizing enzymes influencing the pain phenotype can be an important guide to develop safe new strategies and approaches to personalized pain management. Additionally, some challenges still prevail and preclude adoption of pharmacogenomic testing universally. These include lack of knowledge about pharmacogenomic testing, inadequate standardization of the process of data handling, questionable benefits about the clinical and financial aspects of pharmacogenomic testing-guided therapy, discrepancies in clinical evidence supporting these tests, and doubtful reimbursement of the tests by health insurance agencies.