Next-generation sequencing in pharmacogenomics - fit for clinical decision support?

INTRODUCTION

The technological advances of sequencing methods during the past 20 years have fuelled the generation of large amounts of sequencing data that comprise common variations, as well as millions of rare and personal variants that would not be identified by conventional genotyping. While comprehensive sequencing is technically feasible, its clinical utility for guiding personalized treatment decisions remains controversial.

AREAS COVERED

We discuss the opportunities and challenges of comprehensive sequencing compared to targeted genotyping for pharmacogenomic applications. Current pharmacogenomic sequencing panels are heterogeneous and clinical actionability of the included genes is not a major focus. We provide a current overview and critical discussion of how current studies utilize sequencing data either retrospectively from biobanks, databases or repurposed diagnostic sequencing, or prospectively using pharmacogenomic sequencing.

EXPERT OPINION

While sequencing-based pharmacogenomics has provided important insights into genetic variations underlying the safety and efficacy of a multitude pharmacological treatments, important hurdles for the clinical implementation of pharmacogenomic sequencing remain. We identify gaps in the interpretation of pharmacogenetic variants, technical challenges pertaining to complex loci and variant phasing, as well as unclear cost-effectiveness and incomplete reimbursement. It is critical to address these challenges in order to realize the promising prospects of pharmacogenomic sequencing.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response.

Pharmacogenomics in practice: a review and implementation guide

Considerable efforts have been exerted to implement Pharmacogenomics (PGx), the study of interindividual variations in DNA sequence related to drug response, into routine clinical practice. In this article, we first briefly describe PGx and its role in improving treatment outcomes. We then propose an approach to initiate clinical PGx in the hospital setting. One should first evaluate the available PGx evidence, review the most relevant drugs, and narrow down to the most actionable drug-gene pairs and related variant alleles. This is done based on data curated and evaluated by experts such as the pharmacogenomics knowledge implementation (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC), as well as drug regulatory authorities such as the US Food and Drug Administration (FDA) and European Medicinal Agency (EMA). The next step is to differentiate reactive point of care from preemptive testing and decide on the genotyping strategy being a candidate or panel testing, each of which has its pros and cons, then work out the best way to interpret and report PGx test results with the option of integration into electronic health records and clinical decision support systems. After test authorization or testing requirements by the government or drug regulators, putting the plan into action involves several stakeholders, with the hospital leadership supporting the process and communicating with payers, the pharmacy and therapeutics committee leading the process in collaboration with the hospital laboratory and information technology department, and healthcare providers (HCPs) ordering the test, understanding the results, making the appropriate therapeutic decisions, and explaining them to the patient. We conclude by recommending some strategies to further advance the implementation of PGx in practice, such as the need to educate HCPs and patients, and to push for more tests' reimbursement. We also guide the reader to available PGx resources and examples of PGx implementation programs and initiatives.

Evaluation of out-of-pocket pay genetic testing in a publicly funded healthcare system

When genetic tests are not funded publicly, out-of-pocket (OOP) pay options may be discussed with patients. We evaluated trends in genetic testing and OOP pay for two publicly funded British Columbia clinical programs serving >12 000 patients/year (The Hereditary Cancer Program [HCP] and Provincial Medical Genetics Program [PMGP]) between 2015-2019. Linear and regression models were used to explore the association of OOP pay with patient demographic variables at HCP. An interrupted time series and linear and logistic regression models were used on PMGP data to examine the effect of a change in the funding body. The total number of tests completed through PMGP, and HCP increased by 260% and 320%, respectively. OOP pay increased at HCP by 730%. The mean annual income of patients who paid OOP at HCP was ≥$3500 higher than in the group with funded testing (p < 0.0001). The likelihood of OOP pay increased at PMGP before the funding body change (OR per month: 1.07; 95% CI: 1.04, 1.10); while this likelihood had an immediate 87% drop when the change occurred (OR: 0.13; 95% CI: 0.06, 0.32). Patients with higher incomes are more likely to pay OOP. Financial barriers can create disparities in clinical outcomes. Funding decisions have a significant impact on rate of OOP pay.

Genomic medicine in Africa: a need for molecular genetics and pharmacogenomics experts

The large-scale implementation of genomic medicine in Africa has not been actualized. This overview describes how routine molecular genetics and advanced protein engineering/structural biotechnology could accelerate the implementation of genomic medicine. By using data-mining and analysis approaches, we analyzed relevant information obtained from public genomic databases on pharmacogenomics biomarkers and reviewed published studies to discuss the ideas. The results showed that only 68 very important pharmacogenes currently exist, while 867 drug label annotations, 201 curated functional pathways, and 746 annotated drugs have been catalogued on the largest pharmacogenomics database (PharmGKB). Only about 5009 variants of the reported ∼25,000 have been clinically annotated. Predominantly, the genetic variants were derived from 43 genes that contribute to 2318 clinically relevant variations in 57 diseases. Majority (∼60%) of the clinically relevant genetic variations in the pharmacogenes are missense variants (1390). The enrichment analysis showed that 15 pharmacogenes are connected biologically and are involved in the metabolism of cardiovascular and cancer drugs. The review of studies showed that cardiovascular diseases are the most frequent non-communicable diseases responsible for approximately 13% of all deaths in Africa. Also, warfarin pharmacogenomics is the most studied drug on the continent, while CYP2D6, CYP2C9, DPD, and TPMT are the most investigated pharmacogenes with allele activities indicated in African and considered to be intermediate metaboliser for DPD and TPMT (8.4% and 11%). In summary, we highlighted a framework for implementing genomic medicine starting from the available resources on ground.

Financing and Reimbursement Models for Personalised Medicine: A Systematic Review to Identify Current Models and Future Options

BACKGROUND

The number of healthcare interventions described as 'personalised medicine' (PM) is increasing rapidly. As healthcare systems struggle to decide whether to fund PM innovations, it is unclear what models for financing and reimbursement are appropriate to apply in this context.

OBJECTIVE

To review financing and reimbursement models for PM, summarise their key characteristics, and describe whether they can influence the development and uptake of PM.

METHODS

A literature review was conducted in Medline, Embase, Web of Science, and Econlit to identify studies published in English between 2009 and 2021, and reviews published before 2009. Grey literature was identified through Google Scholar, Google and subject-specific webpages. Articles that described financing and reimbursement of PM, and financing of non-PM were included. Data were extracted and synthesised narratively to report on the models, as well as facilitators, incentives, barriers and disincentives that could influence PM development and uptake.

RESULTS

One hundred and fifty-three papers were included. Research and development of PM was financed through both public and private sources and reimbursed largely through traditional models such as single fees, Diagnosis-Related Groups, and bundled payments. Financial-based reimbursement, including rebates and price-volume agreements, was mainly applied to targeted therapies. Performance-based reimbursement was identified mainly for gene and targeted therapies, and some companion diagnostics. Gene therapy manufacturers offered outcome-based rebates for treatment failure for interventions including Luxturna®, Kymriah®, Yescarta®, Zynteglo®, Zolgensma® and Strimvelis®, and coverage with evidence development for Kymriah® and Yescarta®. Targeted testing with OncotypeDX® was granted value-based reimbursement through initial coverage with evidence development. The main barriers and disincentives to PM financing and reimbursement were the lack of strong links between stakeholders and the lack of demonstrable benefit and value of PM.

CONCLUSIONS

Public-private financing agreements and performance-based reimbursement models could help facilitate the development and uptake of PM interventions with proven clinical benefit.

Health Technology Assessment for In Silico Medicine: Social, Ethical and Legal Aspects

The application of in silico medicine is constantly growing in the prevention, diagnosis, and treatment of diseases. These technologies allow us to support medical decisions and self-management and reduce, refine, and partially replace real studies of medical technologies. In silico medicine may challenge some key principles: transparency and fairness of data usage; data privacy and protection across platforms and systems; data availability and quality; data integration and interoperability; intellectual property; data sharing; equal accessibility for persons and populations. Several social, ethical, and legal issues may consequently arise from its adoption. In this work, we provide an overview of these issues along with some practical suggestions for their assessment from a health technology assessment perspective. We performed a narrative review with a search on MEDLINE/Pubmed, ISI Web of Knowledge, Scopus, and Google Scholar. The following key aspects emerge as general reflections with an impact on the operational level: cultural resistance, level of expertise of users, degree of patient involvement, infrastructural requirements, risks for health, respect of several patients’ rights, potential discriminations for access and use of the technology, and intellectual property of innovations. Our analysis shows that several challenges still need to be debated to allow in silico medicine to express all its potential in healthcare processes.

Genetic testing and diagnosis of inherited retinal diseases

Inherited retinal diseases (IRDs) are a diverse group of degenerative diseases of the retina that can lead to significant reduction in vision and blindness. Because of the considerable phenotypic overlap among IRDs, genetic testing is a critical step in obtaining a definitive diagnosis for affected individuals and enabling access to emerging gene therapy–based treatments and ongoing clinical studies. While advances in molecular diagnostic technologies have significantly improved the understanding of IRDs and identification of disease-causing variants, training in genetic diagnostics among ophthalmologists is limited. In this review, we will provide ophthalmologists with an overview of genetic testing for IRDs, including the types of available testing, variant interpretation, and genetic counseling. Additionally, we will discuss the clinical applications of genetic testing in the molecular diagnosis of IRDs through case studies.

Neptune: an environment for the delivery of genomic medicine

PURPOSE

Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process.

METHODS

We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration.

RESULTS

Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow.

CONCLUSION

Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .

Inaugural Pharmacogenomics Access and Reimbursement Symposium

The Pharmacogenomics Access & Reimbursement Symposium, a landmark event presented by the Golden Helix Foundation and the Pharmacogenomics Access & Reimbursement Coalition, was a 1-day interactive meeting comprised of plenary keynotes from thought leaders across healthcare that focused on value-based strategies to improve patient access to personalized medicine. Stakeholders including patients, healthcare providers, industry, government agencies, payer organizations, health systems and health policy organizations convened to define opportunities to improve patient access to personalized medicine through best practices, successful reimbursement models, high quality economic evaluations and strategic alignment. Session topics included health technology assessment, health economics, health policy and value-based payment models and innovation.

Governing Personalized Health: A Scoping Review

Genetic research is advancing rapidly. One important area for the application of the results from this work is personalized health. These are treatments and preventive interventions tailored to the genetic profile of specific groups or individuals. The inclusion of personalized health in existing health systems is a challenge for policymakers. In this article, we present the results of a thematic scoping review of the literature dealing with governance and policy of personalized health. Our analysis points to four governance challenges that decisionmakers face against the background of personalized health. First, researchers have highlighted the need to further extend and harmonize existing research infrastructures in order to combine different types of genetic data. Second, decisionmakers face the challenge to create trust in personalized health applications, such as genetic tests. Third, scholars have pointed to the importance of the regulation of data production and sharing to avoid discrimination of disadvantaged groups and to facilitate collaboration. Fourth, researchers have discussed the challenge to integrate personalized health into regulatory-, financing-, and service provision structures of existing health systems. Our findings summarize existing research and help to guide further policymaking and research in the field of personalized health governance.

Real-world characteristics and outcomes of advanced non-small-cell lung cancer patients with EGFR exon 19 deletions or exon 21 mutations

Aim: To estimate real-world (rw) outcomes for first-line therapy in patients with advanced EGF receptor (EGFR)-mutated non-small-cell lung cancer (NSCLC), focusing on specific mutation types. Patients & methods: Retrospective observational study (n = 244 patients). Results: Univariate/multivariate analyses showed longer rw progression-free survival (rwPFS) and rwPFS2 in patients with ex19del versus Leu858Arg mutations. Median overall survival was 12.3 months longer with ex19del versus Leu858Arg mutations (HR: 1.47 [95% CI: 0.96-2.25]; p = 0.074). With EGFR-tyrosine kinase inhibitor monotherapy, unadjusted rwPFS for ex19del mutations was longer than for Leu858Arg mutations (HR: 1.62 [95% CI: 1.03-2.56]; p = 0.036). Conclusion: In this rw cohort of patients with advanced EGFR+ NSCLC, ex19del mutations conferred a prognostic advantage over Leu858Arg mutations, with significantly better rwPFS and rwPFS2.

Molecular predictive testing in precision oncology: The Italian experience

In this review, we describe molecular pathology testing to predict response to targeted treatment of solid tumors, focusing on Italian routine clinical practice. The combination of the universal health care system organized at national, regional, and local levels has led a decentralized model, with a large number of local laboratories performing in-house molecular testing following guidelines issued and external quality assessment organized by the Italian Society of Pathology and Cytopathology-Italian Division of the International Academy of Pathology. In this framework, in the early days of predictive testing, sponsored informatics platforms support to set up national programs that aimed to integrate the activity of oncologists and pathologists to test cancer patients for druggable alterations. More recently, reimbursement for molecular testing is being covered completely by the Italian National Health Service. In the near future, considering the development of complex technologies, we expect that outsourcing samples to next-generation sequencing referral laboratories will take place.

Conference report: inaugural Pharmacogenomics Access & Reimbursement Symposium

The Pharmacogenomics Access & Reimbursement Symposium, a landmark event presented by the Golden Helix Foundation and the Pharmacogenomics Access & Reimbursement Coalition (PARC), was a one-day interactive meeting comprised of plenary keynotes from thought leaders across health care that focused on value-based strategies to improve patient access to personalized medicine. Stakeholders including patients, healthcare providers, industry, government agencies, payer organizations, health systems and health policy organizations convened to define opportunities to improve patient access to personalized medicine through best practices, successful reimbursement models, high-quality economic evaluations, and strategic alignment. Session topics included health technology assessment, health economics, health policy, and value-based payment models and innovation.

PARC report: health outcomes and value of personalized medicine interventions: impact on patient care

The incorporation of personalized medicine interventions into routine healthcare constitutes an opportunity to improve patients' quality of life, as it empowers implementation of innovative, individualized clinical interventions that maximize efficacy and/or minimize the risk of adverse drug reactions. In order to ensure equal access to genomic testing for all patients, the costs associated with these interventions must be reimbursed by payers and insurance bodies. As such, it is of utmost importance to thoroughly evaluate these interventions both in terms of their clinical effectiveness and their economic cost. This article discusses the impact of personalized medicine interventions in terms of both health outcomes and value, which directly impacts on their pricing and reimbursement by the various national healthcare systems.

Clinical sequencing: From raw data to diagnosis with lifetime value

High-throughput sequencing (HTS) has revolutionized genetics by enabling the detection of sequence variants at hitherto unprecedented large scale. Despite these advances, however, there are still remaining challenges in the complete coverage of targeted regions (genes, exome or genome) as well as in HTS data analysis and interpretation. Moreover, it is easy to get overwhelmed by the plethora of available methods and tools for HTS. Here, we review the step-by-step process from the generation of sequence data to molecular diagnosis of Mendelian diseases. Highlighting advantages and limitations, this review addresses the current state of (1) HTS technologies, considering targeted, whole-exome, and whole-genome sequencing on short- and long-read platforms; (2) read alignment, variant calling and interpretation; as well as (3) regulatory issues related to genetic counseling, reimbursement, and data storage.

Building evidence and measuring clinical outcomes for genomic medicine

Human genomic sequencing has potential diagnostic, prognostic, and therapeutic value across a wide breadth of clinical disciplines. One barrier to widespread adoption is the paucity of evidence for improved outcomes in patients who do not already have an indication for more focused testing. In this Series paper, we review clinical outcome studies in genomic medicine and discuss the important features and key challenges to building evidence for next generation sequencing in the context of routine patient care.

Application of Economic Evaluation to Assess Feasibility for Reimbursement of Genomic Testing as Part of Personalized Medicine Interventions

Background: The incorporation of genomic testing into clinical practice constitutes an opportunity to improve patients' lives, as it makes possible the implementation of innovative, individualized clinical interventions that maximize efficacy and/or minimize the risk of adverse drug reactions. In order to ensure equal access to genomic testing for all patients, the costs associated with these tests should be reimbursed by their respective national healthcare systems. Given that funding for the public health sector is decreasing in real terms, it is of paramount importance that the emerging interventions are thoroughly evaluated both in terms of their clinical effectiveness and their full economic cost. Objective: The aim of this study was to identify those genome-guided interventions that could be adopted and reimbursed by national healthcare systems. Further, we recorded the underlying factors determining the broad adoption of genome-guided interventions in clinical practice, in order to identify potential reimbursement criteria. Methods: We performed a systematic review of published (PubMed-listed) scientific articles on the economic evaluation of those individualized clinical interventions that include genomic tests. Information on genomic tests reimbursed by the US Medicare program was also included. Subsequently, we correlated the regulatory guidance given for the interventions collated in our systematic review with the corresponding economic evaluation results and policies of the Medicare program. Regulatory guidance information was collected from the PharmGKB online knowledgebase and the Clinical Pharmacogenetics Implementation Consortium (CPIC). Results: Most of the included studies constitute cost-utility analyses, in which the outcome of the interventions has been measured in quality-adjusted life years (QALYs) whereas an estimate of the total cost has been based upon direct medical cost data. Favorable economic evaluation results, as well as concrete evidence demonstrating the clinical utility of pre-emptive genotyping, are considered as prerequisites for the broad adoption and reimbursement of the costs incurred during genomic testing. Indicatively, pre-emptive HLA-B*5701 and TPMT testing before administration of abacavir and azathioprine, respectively, is reimbursed by Medicare based on both economic and efficacy evidence. Likewise, the medical necessary screening for MMR and BRCA1/2 genes are reimbursed for high-risk populations. Conclusions: Our findings further underline the need for further cost-utility analyses within different national healthcare systems, in order to promote the reimbursement of the cost of innovative genome-guided therapeutic interventions.

Operational models and criteria for incorporating microbial whole genome sequencing in hospital microbiology - A systematic literature review

BACKGROUND

Microbial whole genome sequencing (WGS) has many advantages over standard microbiological methods. However, it is not yet widely implemented in routine hospital diagnostics due to notable challenges.

OBJECTIVES

The aim was to extract managerial, financial and clinical criteria supporting the decision to implement WGS in routine diagnostic microbiology, across different operational models of implementation in the hospital setting.

METHODS

This was a systematic review of literature identified through PubMed and Web of Science. English literature studies discussing the applications of microbial WGS without limitation on publication date were eligible. A narrative approach for categorization and synthesis of the sources identified was adopted.

RESULTS

A total of 98 sources were included. Four main alternative operational models for incorporating WGS in clinical microbiology laboratories were identified: full in-house sequencing and analysis, full outsourcing of sequencing and analysis and two hybrid models combining in-house/outsourcing of the sequencing and analysis components. Six main criteria (and multiple related sub-criteria) for WGS implementation emerged from our review and included cost (e.g. the availability of resources for capital and operational investment); manpower (e.g. the ability to provide training programmes or recruit trained personnel), laboratory infrastructure (e.g. the availability of supplies and consumables or sequencing platforms), bioinformatics requirements (e.g. the availability of valid analysis tools); computational infrastructure (e.g. the availability of storage space or data safety arrangements); and quality control (e.g. the existence of standardized procedures).

CONCLUSIONS

The decision to incorporate WGS in routine diagnostics involves multiple, sometimes competing, criteria and sub-criteria. Mapping these criteria systematically is an essential stage in developing policies for adoption of this technology, e.g. using a multicriteria decision tool. Future research that will prioritize criteria and sub-criteria that were identified in our review in the context of operational models will inform decision-making at clinical and managerial levels with respect to effective implementation of WGS for routine use. Beyond WGS, similar decision-making challenges are expected with respect to future integration of clinical metagenomics.

Genomic Medicine Without Borders: Which Strategies Should Developing Countries Employ to Invest in Precision Medicine? A New "Fast-Second Winner" Strategy

Genomic medicine has greatly matured in terms of its technical capabilities, but the diffusion of genomic innovations worldwide faces significant barriers beyond mere access to technology. New global development strategies are sorely needed for biotechnologies such as genomics and their applications toward precision medicine without borders. Moreover, diffusion of genomic medicine globally cannot adhere to a "one-size-fits-all-countries" development strategy, in the same way that drug treatments should be customized. This begs a timely, difficult but crucial question: How should developing countries, and the resource-limited regions of developed countries, invest in genomic medicine? Although a full-scale investment in infrastructure from discovery to the translational implementation of genomic science is ideal, this may not always be feasible in all countries at all times. A simple "transplantation of genomics" from developed to developing countries is unlikely to be feasible. Nor should developing countries be seen as simple recipients and beneficiaries of genomic medicine developed elsewhere because important advances in genomic medicine have materialized in developing countries as well. There are several noteworthy examples of genomic medicine success stories involving resource-limited settings that are contextualized and described in this global genomic medicine innovation analysis. In addition, we outline here a new long-term development strategy for global genomic medicine in a way that recognizes the individual country's pressing public health priorities and disease burdens. We term this approach the "Fast-Second Winner" model of innovation that supports innovation commencing not only "upstream" of discovery science but also "mid-stream," building on emerging highly promising biomarker and diagnostic candidates from the global science discovery pipeline, based on the unique needs of each country. A mid-stream entry into innovation can enhance collective learning from other innovators' mistakes upstream in discovery science and boost the probability of success for translation and implementation when resources are limited. This à la carte model of global innovation and development strategy offers multiple entry points into the global genomics innovation ecosystem for developing countries, whether or not extensive and expensive discovery infrastructures are already in place. Ultimately, broadening our thinking beyond the linear model of innovation will help us to enable the vision and practice of genomics without borders in both developed and resource-limited settings.

Care and cost consequences of pediatric whole genome sequencing compared to chromosome microarray

The clinical use of whole-genome sequencing (WGS) is expected to alter pediatric medical management. The study aimed to describe the type and cost of healthcare activities following pediatric WGS compared to chromosome microarray (CMA). Healthcare activities prompted by WGS and CMA were ascertained for 101 children with developmental delay over 1 year. Activities following receipt of non-diagnostic CMA were compared to WGS diagnostic and non-diagnostic results. Activities were costed in 2016 Canadian dollars (CDN). Ongoing care accounted for 88.6% of post-test activities. The mean number of lab tests was greater following CMA than WGS (0.55 vs. 0.09; p = 0.007). The mean number of specialist visits was greater following WGS than CMA (0.41 vs. 0; p = 0.016). WGS results (diagnostic vs. non-diagnostic) modified the effect of test type on mean number of activities (p < 0.001). The cost of activities prompted by diagnostic WGS exceeded $557CDN for 10% of cases. In complex pediatric care, CMA prompted additional diagnostic investigations while WGS prompted tailored care guided by genotypic variants. Costs for prompted activities were low for the majority and constitute a small proportion of total test costs. Optimal use of WGS depends on robust evaluation of downstream care and cost consequences.

The challenges of implementing pharmacogenomic testing in the clinic

INTRODUCTION

Pharmacogenomic testing has the potential to greatly benefit patients by enabling personalization of medication management, ensuring better efficacy and decreasing the risk of side effects. However, to fully realize the potential of pharmacogenomic testing, there are several important issues that must be addressed. Areas covered: In this expert review we discuss current challenges impacting the implementation of pharmacogenomic testing in the clinical practice. We emphasize issues related to testing methods, reporting of the results, test selection, clinical interpretation of the results, cost-effectiveness, and the long-term use of pharmacogenomic results in clinical practice. We identify opportunities and future directions to facilitate clinical implementation. Expert commentary: Several key elements are necessary to optimally integrate pharmacogenomic testing into clinical practice. Collaborative efforts among laboratories are needed to improve standardization of testing and reporting of the results. Clinicians need educational opportunities to improve understanding of which test to order and how to interpret the results. The electronic health records and other clinical systems need to improve their storage of the pharmacogenomics test results and interoperability to facilitate the use of clinically actionable results to improve patient care.

The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals

Aim: The aim of this study was to assess the physicians’ attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals. Materials & methods: We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed. Results: The remaining knowledge gap, the uncertainty of test reimbursement and the physicians’ lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists. Conclusion: Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.

Key Pharmacogenomic Considerations for Sickle Cell Disease Patients

Sickle cell disease (SCD), although a monogenic disease, exhibits a complex clinical phenotype that hampers optimum patient stratification and disease management, especially on hydroxyurea treatment. Moreover, theranostics, the combination of diagnostics to individualize and optimize therapeutic interventions, has not been firmly on the forefront of SCD research and clinical management to date. We suggest that if tailor-made theranostics in SCD is envisaged, pharmacogenomics is anticipated to be the way forward. Herein, we present the current key pharmacogenomic opportunities and challenges in SCD, considering population variation, ethics, and socioeconomic aspects. We focus on pharmacogenomics and pain management, genethics, and cost-effectiveness in SCD. We searched for and synthesized data from PubMed and Google Scholar, and the references from relevant articles, using the keywords "pharmacogenomics," "sickle cell disease," "hydroxyurea," "ethics," "pain management," "morphine metabolism," "opioids," "pharmacogenomics and chronic pain," "cost-effectiveness," and "economic evaluation." Only articles published in English were included. So far, when pharmacogenomics in SCD has been considered, interindividual variability in hydroxyurea response/toxicity has been of primary interest. We underscore the need to extend pharmacogenomic considerations on other therapeutic interventions currently present using a holistic patient-centric approach, and taking disease complications into account as well. Furthermore, we raise awareness toward socioeconomic, ethical, and population differences in the way sickle cell pharmacogenomics might unfold in the future. If pharmacogenomics in SCD is to be used in the clinic in an evidence-based manner, cost-effectiveness and population-specific empirical ethics data are urgently needed.

Toward health technology assessment of whole-genome sequencing diagnostic tests: challenges and solutions

Whole-genome sequencing (WGS) is being applied within research settings across Europe to develop genomic WGS-based diagnostic tests. The focus of this perspective paper is to describe if, and how, current approaches of health technology assessment could be applied to WGS-based diagnostic tests. This perspective draws on the collective view from a trans-European multidisciplinary consortium of methodologists, clinicians and scientists. Specific challenges can be described by using the PICO (population, intervention, comparator, outcome) framework to inform health technology assessment. Practical solutions are suggested which require joined-up, multidisciplinary working across healthcare systems using existing expert networks so that emergent issues for the health technology assessment of WGS can be met in a timely fashion.

Performance Ratio Based Resource Allocation Decision-Making in Genomic Medicine

In modern healthcare systems, the available resources may influence the morbidity, mortality, and-consequently-the level of healthcare provided in every country. This is of particular interest in developing countries where the resources are limited and must be spent wisely to address social justice and the right for equal access in healthcare services by all the citizens in economically viable terms. In this light, the current allocation is, in practice, inefficient and rests mostly on each country's individual political and historical context and, thus, does not always incorporate decision-making enabled by economic models. In this study, we present a new economic model, specifically for resource allocation for genomic medicine, based on performance ratio, with potential applications in diverse healthcare sectors, which are particularly appealing for developing countries and low-resource environments. The model proposes a new method for resource allocation taking into account (1) the size of innovation of a new technology, (2) the relative effectiveness in comparison with social preferences, and (3) the cost of the technology, which permits the measurement of effectiveness to be determined differently in the context of a specific disease and then to be expressed in a relative form using a common performance ratio. The present work expands on previous work for innovation in economic models pertaining to genomic medicine and supports translational science.