Implementation of genotype-guided dosing of warfarin with point-of-care genetic testing in three UK clinics: a matched cohort study

Tribulations and future opportunities for artificial intelligence in precision medicine

Upon a diagnosis, the clinical team faces two main questions: what treatment, and at what dose? Clinical trials' results provide the basis for guidance and support for official protocols that clinicians use to base their decisions. However, individuals do not consistently demonstrate the reported response from relevant clinical trials. The decision complexity increases with combination treatments where drugs administered together can interact with each other, which is often the case. Additionally, the individual's response to the treatment varies with the changes in their condition. In practice, the drug and the dose selection depend significantly on the medical protocol and the medical team's experience. As such, the results are inherently varied and often suboptimal. Big data and Artificial Intelligence (AI) approaches have emerged as excellent decision-making tools, but multiple challenges limit their application. AI is a rapidly evolving and dynamic field with the potential to revolutionize various aspects of human life. AI has become increasingly crucial in drug discovery and development. AI enhances decision-making across different disciplines, such as medicinal chemistry, molecular and cell biology, pharmacology, pathology, and clinical practice. In addition to these, AI contributes to patient population selection and stratification. The need for AI in healthcare is evident as it aids in enhancing data accuracy and ensuring the quality care necessary for effective patient treatment. AI is pivotal in improving success rates in clinical practice. The increasing significance of AI in drug discovery, development, and clinical trials is underscored by many scientific publications. Despite the numerous advantages of AI, such as enhancing and advancing Precision Medicine (PM) and remote patient monitoring, unlocking its full potential in healthcare requires addressing fundamental concerns. These concerns include data quality, the lack of well-annotated large datasets, data privacy and safety issues, biases in AI algorithms, legal and ethical challenges, and obstacles related to cost and implementation. Nevertheless, integrating AI in clinical medicine will improve diagnostic accuracy and treatment outcomes, contribute to more efficient healthcare delivery, reduce costs, and facilitate better patient experiences, making healthcare more sustainable. This article reviews AI applications in drug development and clinical practice, making healthcare more sustainable, and highlights concerns and limitations in applying AI.

Precision Medicine-Are We There Yet? A Narrative Review of Precision Medicine's Applicability in Primary Care

Precision medicine (PM), also termed stratified, individualised, targeted, or personalised medicine, embraces a rapidly expanding area of research, knowledge, and practice. It brings together two emerging health technologies to deliver better individualised care: the many "-omics" arising from increased capacity to understand the human genome and "big data" and data analytics, including artificial intelligence (AI). PM has the potential to transform an individual's health, moving from population-based disease prevention to more personalised management. There is however a tension between the two, with a real risk that this will exacerbate health inequalities and divert funds and attention from basic healthcare requirements leading to worse health outcomes for many. All areas of medicine should consider how this will affect their practice, with PM now strongly encouraged and supported by government initiatives and research funding. In this review, we discuss examples of PM in current practice and its emerging applications in primary care, such as clinical prediction tools that incorporate genomic markers and pharmacogenomic testing. We look towards potential future applications and consider some key questions for PM, including evidence of its real-world impact, its affordability, the risk of exacerbating health inequalities, and the computational and storage challenges of applying PM technologies at scale.

Being precise with anticoagulation to reduce adverse drug reactions: are we there yet?

Anticoagulants are potent therapeutics widely used in medical and surgical settings, and the amount spent on anticoagulation is rising. Although warfarin remains a widely prescribed oral anticoagulant, prescriptions of direct oral anticoagulants (DOACs) have increased rapidly. Heparin-based parenteral anticoagulants include both unfractionated and low molecular weight heparins (LMWHs). In clinical practice, anticoagulants are generally well tolerated, although interindividual variability in response is apparent. This variability in anticoagulant response can lead to serious incident thrombosis, haemorrhage and off-target adverse reactions such as heparin-induced thrombocytopaenia (HIT). This review seeks to highlight the genetic, environmental and clinical factors associated with variability in anticoagulant response, and review the current evidence base for tailoring the drug, dose, and/or monitoring decisions to identified patient subgroups to improve anticoagulant safety. Areas that would benefit from further research are also identified. Validated variants in VKORC1, CYP2C9 and CYP4F2 constitute biomarkers for differential warfarin response and genotype-informed warfarin dosing has been shown to reduce adverse clinical events. Polymorphisms in CES1 appear relevant to dabigatran exposure but the genetic studies focusing on clinical outcomes such as bleeding are sparse. The influence of body weight on LMWH response merits further attention, as does the relationship between anti-Xa levels and clinical outcomes. Ultimately, safe and effective anticoagulation requires both a deeper parsing of factors contributing to variable response, and further prospective studies to determine optimal therapeutic strategies in identified higher risk subgroups.

Real-world evidence that among atrial fibrillation patients warfarin is associated with reduced nonelective admissions compared with those on DOACs

BACKGROUND

Randomized trials show inconsistent estimates on risks of direct-acting oral anticoagulants (DOACs) versus warfarin in bleeding and mortality for atrial fibrillation (AF) patients. Trials are confounded by additional DOAC adherence support, while warfarin has a low time in therapeutic range. Few real-world studies compared emergency hospitalization risk between DOAC and warfarin users in AF. This study aimed to determine emergency hospitalization risk for AF patients on DOACs or warfarin in real-world settings.

METHODS

A tapered-matched real-world cohort extracted data from 412 English general practices' primary care records linked with emergency department (ED) and hospitalization data from the ECLIPSE database. AF patients with new DOAC or warfarin prescriptions were included. The primary outcome was all-cause ED attendance; the secondary outcomes were ED re-attendance, nonelective hospitalization, and rehospitalization within 12 months. Weighted Cox regression estimated relative risk difference.

RESULTS

39 201 DOAC patients were matched with 13 145 warfarin patients. DOAC patients had a 25% higher likelihood of attending ED (odds ratio 1.25; 95% confidence interval [CI] 1.01-1.55). DOAC use also associated with higher ED re-attendance, nonelective hospitalization, and rehospitalization within 12 months: 1.41 (95% CI 1.00-1.98), 1.26 (1.00-1.57), and 1.54 (1.01-2.34), respectively, with p-values < .05.

CONCLUSIONS

DOACs for AF thromboprophylaxis are associated with the increased risk of ED attendance, recurrent hospitalization, and numerical rise in ED re-attendance and first nonelective hospitalization compared to warfarin. However, these real-world data cannot establish if this difference results from medication adherence, lack of regular DOAC clinic monitoring, unmeasured confounders, or fundamental agent efficacy disparities.

Impact of Pharmacogenomics in Clinical Practice

Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.

Anticoagulant use in older persons at risk for falls: therapeutic dilemmas-a clinical review

PURPOSE

The aim of this clinical narrative review was to summarise the existing knowledge on the use of anticoagulants and potential adverse events in older people at risk of falls with a history of atrial fibrillation or venous thromboembolism. The review also offers practical steps prescribers can take when (de-)prescribing anticoagulants to maximise safety.

METHODS

Literature searches were conducted using PubMed, Embase and Scopus. Additional articles were identified by searching reference lists.

RESULTS

Anticoagulants are often underused in older people due to concerns about the risk of falls and intracranial haemorrhage. However, evidence suggests that the absolute risk is low and outweighed by the reduction in stroke risk. DOACs are now recommended first line for most patients due to their favourable safety profile. Off-label dose reduction of DOACs is not recommended due to reduced efficacy with limited reduction in bleeding risk. Medication review and falls prevention strategies should be implemented before prescribing anticoagulation. Deprescribing should be considered in severe frailty, limited life expectancy and increased bleeding risk (e.g., cerebral microbleeds).

CONCLUSION

When considering whether to (de-)prescribe anticoagulants, it is important to consider the risks associated with stopping therapy in addition to potential adverse events. Shared decision-making with the patient and their carers is crucial as patient and prescriber views often differ.

Efficacy of Warfarin Therapy Guided by Pharmacogenetics: A Real-world Investigation Among Han Taiwanese

PURPOSE

The anticoagulation activity of warfarin in populations with CYP2C9, VKORC1, and CYP4F2 variants differs between individuals and is correlated with poor international normalized ratio (INR) control. Pharmacogenetics-guided warfarin dosing has been successfully developed for patients with genetic variations in recent years. However, few real-world data have been used to investigate the INR and warfarin dosage and the time to target INR. This study examined the largest collection of genetic and clinical real-world data related to warfarin to provide further evidence supporting the benefits of pharmacogenetics in clinical outcomes.

METHODS

We retrieved a total of 69,610 INR-warfarin records after the index date from 2,613 patients in the China Medical University Hospital database between January 2003 and December 2019. Each INR reading was obtained from the latest laboratory data after the hospital visit date. Patients with a history of malignant neoplasms or pregnancy before the index date were excluded, as were patients without data on INR measurements after the fifth day of prescription, genetic information, or gender variables. The primary outcomes were the INR and warfarin dosage during days 7, 14, 28, 56, and 84 after prescription. The secondary outcome was the time required to reach the INR ranges of 1.5 to 3.0 and >4.0.

FINDINGS

A total of 59,643 INR-warfarin records from 2188 patients were retrieved. The average INR was higher for homozygous carriers of the minor allele at CYP2C9 and VKORC1 during the first 7 days (1.83 [1.03] [CYP2C9*1] and 2.46 [1.44] [CYP2C9*3], P < 0.001; 1.39 [0.36] [rs9923231 G/G], 1.55 [0.79] [rs9923231 G/A], and 1.96 [1.13] [rs9923231 A/A], P < 0.001) than for the wild-type allele. These patients with variants required lower warfarin doses than those with the wild-type allele during the first 28 days. CYP4F2 variant patients seemed to require higher doses of warfarin than those in the wild-type group; however, no significant difference in the average INR was observed (1.95 [1.14] [homozygous V433 carriers], 1.78 [0.98] [heterozygous V433M carriers], and 1.66 [0.91] [homozygous M433 carriers], P = 0.016).

IMPLICATIONS

Our study indicates that genetic variants in the Han population may enhance warfarin responsiveness, which holds clinical relevance. An increased warfarin dosage was not linked to a shorter time to therapeutic INR between CYP4F2 variant patients and those with a wild-type allele. Assessing CYP2C9 and VKORC1 genetic polymorphisms before initiating warfarin treatment in real-world practice is essential for potentially vulnerable patients and is likely to optimize therapeutic dosing.

Investigations into the use of machine learning to predict drug dosage form design to obtain desired release profiles for 3D printed oral medicines

Three-dimensional (3D) printing, digitalization, and artificial intelligence (AI) are gaining increasing interest in modern medicine. All three aspects are combined in personalized medicine where 3D-printed dosage forms are advantageous because of their variable geometry design. The geometry design can be used to determine the surface area to volume (SA/V) ratio, which affects drug release from the dosage forms. This study investigated artificial neural networks (ANN) to predict suitable geometries for the desired dose and release profile. Filaments with 5% API load and polyvinyl alcohol were 3D printed using Fused Deposition Modeling to provide a wide variety of geometries with different dosages and SA/V ratios. These were dissolved in vitro, and the API release profiles were described mathematically. Using these data, ANN architectures were designed with the goal of predicting a suitable dosage form geometry. Poor accuracies of 68.5% in the training and 44.4% in the test settings were achieved with a classification architecture. However, the SA/V ratio could be predicted accurately with a mean squared error loss of only 0.05. This study shows that the prediction of the SA/V ratio using AI works, but not of the exact geometry. For this purpose, a global database could be built with a range of geometries to simplify the prescription process.

Pharmacogenomics in Stroke and Cardiovascular Disease: State of the Art

There is considerable interindividual variability in the response to antiplatelet and anticoagulant therapies, and this variation may be attributable to genetic variants. There has been an increased understanding of the genetic architecture of stroke and cardiovascular disease, which has been driven by advancements in genomic technologies and this has raised the possibility of more targeted pharmaceutical treatments. Pharmacogenetics promises to use a patient's genetic profile to treat those who are more likely to benefit from a particular intervention by selecting the best possible therapy. Although there are numerous studies indicating strong evidence for the effect of specific genotypes on the outcomes of vascular drugs, the adoption of pharmacogenetic testing in clinical practice has been slow. This resistance may stem from sometimes conflicting findings among pharmacogenetic studies, a lack of stroke-specific randomized controlled trials to test the effectiveness of genetically-guided therapies, and the practical and cost-effective implementation of genetic testing within the clinic. Thus, this review provides an overview of the genetic variants that influence the individual responses to aspirin, clopidogrel, warfarin and statins and the different methods for pharmacogenetic testing and guidelines for clinical implementation for stroke patients.

Advancing Pharmacogenomics from Single-Gene to Preemptive Testing

Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.

Polymorphisms in common antihypertensive targets: Pharmacogenomic implications for the treatment of cardiovascular disease

The idea of personalized medicine came to fruition with sequencing the human genome; however, aside from a few cases, the genetic revolution has yet to materialize. Cardiovascular diseases are the leading cause of death globally, and hypertension is a common prelude to nearly all cardiovascular diseases. Thus, hypertension is an ideal candidate disease to apply tenants of personalized medicine to lessen cardiovascular disease. Herein is a survey that visually depicts the polymorphisms in the top eight antihypertensive targets. Although there are numerous genome-wide association studies regarding cardiovascular disease, few studies look at the effects of receptor polymorphisms on drug treatment. With 17,000+ polymorphisms in the combined target proteins examined, it is expected that some of the clinical variability in the treatment of hypertension is due to polymorphisms in the drug targets. Recent advances in techniques and technology, such as high throughput examination of single mutations, structure prediction, computational power for modeling, and CRISPR models of point mutations, allow for a relatively rapid and comprehensive examination of the effects of known and future polymorphisms on drug affinity and effects. As hypertension is easy to measure and has a plethora of clinically viable ligands, hypertension makes an excellent disease to study pharmacogenomics in the lab and the clinic. If the promises of personalized medicine are to materialize, a concerted effort to examine the effects polymorphisms have on drugs is required. A clinician with the knowledge of a patient's genotype can then prescribe drugs that are optimal for treating that specific patient.

Rapid Point-of-Care Genotyping to Avoid Aminoglycoside-Induced Ototoxicity in Neonatal Intensive Care

Importance

Aminoglycosides are commonly prescribed antibiotics used for the treatment of neonatal sepsis. The MT-RNR1 m.1555A>G variant predisposes to profound aminoglycoside-induced ototoxicity (AIO). Current genotyping approaches take several days, which is unfeasible in acute settings.

Objective

To develop a rapid point-of-care test (POCT) for the m.1555A>G variant before implementation of this technology in the acute neonatal setting to guide antibiotic prescribing and avoid AIO.

Design, Setting, and Participants

This pragmatic prospective implementation trial recruited neonates admitted to 2 large neonatal intensive care units between January 6, 2020, and November 30, 2020, in the UK.

Interventions

Neonates were tested for the m.1555A>G variant via the rapid POCT on admission to the neonatal intensive care unit.

Main Outcomes and Measures

The primary outcome assessed the proportion of neonates successfully tested for the variant of all infants prescribed antibiotics. Secondary outcomes measured whether implementation was negatively associated with routine clinical practice and the performance of the system. The study was statistically powered to detect a significant difference between time to antibiotic administration before and after implementation of the MT-RNR1 POCT.

Results

A total of 751 neonates were recruited and had a median (range) age of 2.5 (0-198) days. The MT-RNR1 POCT was able to genotype the m.1555A>G variant in 26 minutes. Preclinical validation demonstrated a 100% sensitivity (95% CI, 93.9%-100.0%) and specificity (95% CI, 98.5%-100.0%). Three participants with the m.1555A>G variant were identified, all of whom avoided aminoglycoside antibiotics. Overall, 424 infants (80.6%) receiving antibiotics were successfully tested for the variant, and the mean time to antibiotics was equivalent to previous practice.

Conclusions and Relevance

The MT-RNR1 POCT was integrated without disrupting normal clinical practice, and genotype was used to guide antibiotic prescription and avoid AIO. This approach identified the m.1555A>G variant in a practice-changing time frame, and wide adoption could significantly reduce the burden of AIO.

W. Emerging technologies and their impact on regulatory science

There is an evolution and increasing need for the utilization of emerging cellular, molecular and in silico technologies and novel approaches for safety assessment of food, drugs, and personal care products. Convergence of these emerging technologies is also enabling rapid advances and approaches that may impact regulatory decisions and approvals. Although the development of emerging technologies may allow rapid advances in regulatory decision making, there is concern that these new technologies have not been thoroughly evaluated to determine if they are ready for regulatory application, singularly or in combinations. The magnitude of these combined technical advances may outpace the ability to assess fit for purpose and to allow routine application of these new methods for regulatory purposes. There is a need to develop strategies to evaluate the new technologies to determine which ones are ready for regulatory use. The opportunity to apply these potentially faster, more accurate, and cost-effective approaches remains an important goal to facilitate their incorporation into regulatory use. However, without a clear strategy to evaluate emerging technologies rapidly and appropriately, the value of these efforts may go unrecognized or may take longer. It is important for the regulatory science field to keep up with the research in these technically advanced areas and to understand the science behind these new approaches. The regulatory field must understand the critical quality attributes of these novel approaches and learn from each other's experience so that workforces can be trained to prepare for emerging global regulatory challenges. Moreover, it is essential that the regulatory community must work with the technology developers to harness collective capabilities towards developing a strategy for evaluation of these new and novel assessment tools.

Efficacy and safety of genotype-guided warfarin dosing versus non-genotype-guided warfarin dosing strategies: A systematic review and meta-analysis of 27 randomized controlled trials

OBJECTIVE

To evaluate the efficacy and safety of genotype-guided dosing (GD) strategies compared to non-genotype-guided dosing (non-GD) strategies for warfarin.

METHODS

Databases were searched up to July 2021. Meta-analysis was conducted with the Review Manager software (version 5.4) and R (version 4.0.5). Risk ratio (RR), mean difference (MD), and 95% confidence intervals (CIs) were used. Subgroup analyses were conducted based on ethnicity and dosing regimen in non-GD group. Meta-regression was performed to evaluate the relation of covariates. This study is registered with PROSPERO (CRD42021245654).

RESULTS

27 randomized controlled trials with a total of 9906 patients were included. The GD group resulted in a significantly improved time in therapeutic range compared with non-GD group in follow-up duration within 30 days (MD: 5.95, 95%CI: 2.41-9.22, P = 0.001) and beyond 30 days (MD: 4.93, 1.40-8.47, P = 0.006), time to the first therapeutic international normalized ratio (MD: -1.80, -2.69 - -0.92, P < 0.0001), and time to reach stable dose (MD: -5.08, -7.09 - -3.07, P < 0.00001), incidence of major bleeding events (RR: 0.50, 0.33-0.75, P = 0.0008), total bleeding events (RR: 0.83, 0.73-0.95, P = 0.006), and thromboembolism (RR: 0.69, 0.49-0.96, P = 0.03). No differences were found in stable dose achievement, minor bleeding events, over anticoagulation, and all-cause mortality. Four improved efficacy outcomes were observed in GD group compared with fixed dosing group. Only time to the therapeutic INR was shortened in GD group compared with clinical adjusted dosing group. The result showed no difference of safety outcomes between GD group and fixed dosing group whereas a decreased incidence of major bleeding events was observed when comparing to clinical adjusted dosing group.

CONCLUSION

GD strategy was superior to fixed dosing strategy in term of efficacy outcomes and comparable to fixed dosing strategy in safety outcomes. Clinical adjusted regimen could partly substitute the genotype-guided dosing strategy for efficacy in insufficient conditions, but the risk of major bleeding events should be monitored.

Pharmacogenetics to guide cardiovascular drug therapy

Over the past decade, pharmacogenetic testing has emerged in clinical practice to guide selected cardiovascular therapies. The most common implementation in practice is CYP2C19 genotyping to predict clopidogrel response and assist in selecting antiplatelet therapy after percutaneous coronary intervention. Additional examples include genotyping to guide warfarin dosing and statin prescribing. Increasing evidence exists on outcomes with genotype-guided cardiovascular therapies from multiple randomized controlled trials and observational studies. Pharmacogenetic evidence is accumulating for additional cardiovascular medications. However, data for many of these medications are not yet sufficient to support the use of genotyping for drug prescribing. Ultimately, pharmacogenetics might provide a means to individualize drug regimens for complex diseases such as heart failure, in which the treatment armamentarium includes a growing list of medications shown to reduce morbidity and mortality. However, sophisticated analytical approaches are likely to be necessary to dissect the genetic underpinnings of responses to drug combinations. In this Review, we examine the evidence supporting pharmacogenetic testing in cardiovascular medicine, including that available from several clinical trials. In addition, we describe guidelines that support the use of cardiovascular pharmacogenetics, provide examples of clinical implementation of genotype-guided cardiovascular therapies and discuss opportunities for future growth of the field.

Stroke Genetics: Turning Discoveries into Clinical Applications

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

The Role of Pharmacogenomics in Contemporary Cardiovascular Therapy: A position statement from the European Society of Cardiology Working Group on Cardiovascular Pharmacotherapy

There is a strong and ever-growing body of evidence regarding the use of pharmacogenomics to inform cardiovascular pharmacology. However, there is no common position taken by international cardiovascular societies to unite diverse availability, interpretation and application of such data, nor is there recognition of the challenges of variation in clinical practice between countries within Europe. Aside from the considerable barriers to implementing pharmacogenomic testing and the complexities of clinically actioning results, there are differences in the availability of resources and expertise internationally within Europe. Diverse legal and ethical approaches to genomic testing and clinical therapeutic application also require serious thought. As direct-to-consumer genomic testing becomes more common, it can be anticipated that data may be brought in by patients themselves, which will require critical assessment by the clinical cardiovascular prescriber. In a modern, pluralistic and multi-ethnic Europe, self-identified race/ethnicity may not be concordant with genetically detected ancestry and thus may not accurately convey polymorphism prevalence. Given the broad relevance of pharmacogenomics to areas such as thrombosis and coagulation, interventional cardiology, heart failure, arrhythmias, clinical trials, and policy/regulatory activity within cardiovascular medicine, as well as to genomic and pharmacology subspecialists, this position statement attempts to address these issues at a wide-ranging level.

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.

Current trends in the use of anticoagulant pharmacotherapy in the United Kingdom are changes on the horizon?

INTRODUCTION

Effective stroke prevention with oral anticoagulation (OAC) reduces the risk of stroke and death among patients with atrial fibrillation (AF). For most patients with AF, treatment options include vitamin K antagonists (VKA) or non-vitamin K antagonist oral anticoagulants (NOACs). NOACs have been introduced as an alternative to VKAs, and their use has been steadily increasing in the United Kingdom and Europe over a decade. In randomized clinical trials, NOACs had a favorable risk-benefit profile as compared to warfarin. However, there is a concern about their long-term safety in clinical practice, especially in high-risk patients. There have been a number of registries and surveys based on the real-world patients with AF which has been conducted and published, providing data on contemporary AF management.

AREAS COVERED

In this narrative review, the authors discuss current trends in the use of OAC in the United Kingdom and Europe, considering the potential directions for future anticoagulant therapy in patients with AF.

EXPERT OPINION

The increasing prevalence of AF and AF-related comorbidities proves the need for comprehensive prevention and management strategies. The challenge is the optimization of therapy for each patient. However, there are still gaps in optimal stroke prevention, and the mortality rates remain high in patients with AF.

Biochip-based approach for comprehensive pharmacogenetic testing

OBJECTIVES

Individual sensitivity to many widely used drugs is significantly associated with genetic factors. The purpose of our work was to develop an instrument for simultaneous determination of the most clinically relevant pharmacogenetic markers to allow personalized treatment, mainly in patients with cardiovascular diseases.

METHODS

Multiplex one-step polymerase chain reaction (PCR) followed by hybridization on a low-density biochip was applied to interrogate 15 polymorphisms in the following eight genes: VKORC1 -1639 G>A, CYP4F2 1297 G>A, GGCX 2374 C>G, CYP2C9 *2,*3 (430 C>T, 1075 A>C), CYP2D6 *3,*4, *6, *9, *41 (2549delA, 1846 G>A, 1707delT, 2615_2617delAAG, 2988 G>A), CYP2C19 *2,*3,*17 (681 G>A, 636 G>A, -806 C>T), ABCB1 (3435 C>T), SLCO1B1 *5.

RESULTS

Two hundred nineteen patients with cardiovascular diseases (CVD) and 48 female patients with estrogen receptor (ER)-positive breast cancer (BC) were genotyped. Of the 219 CVD patients, 203 (92.7%) carried one or more actionable at-risk genotypes based on VKORC1/CYP2C9, CYP2C9, CYP2C19, SLCO1B1, and CYP2D6 genotypes. Among them, 67 patients (30.6%) carried one, 58 patients (26.5%) carried two, 51 patients (23.3%) carried three, 26 patients (11.9%) carried four, and one patient (0.4%) carried five risk actionable genotypes. In the ER-positive BC group 12 patients (25%) were CYP2D6 intermediate or poor metabolizers.

CONCLUSIONS

The developed biochip is applicable for rapid and robust genotyping of patients who were taking a wide spectrum of medications to optimize drugs and dosage and avoid adverse drug reactions in cardiology, oncology, psychiatry, rheumatology and gastroenterology.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

The future is now? Clinical and translational aspects of "Omics" technologies

Big data has become a central part of medical research, as well as modern life generally. "Omics" technologies include genomics, proteomics, microbiomics and increasingly other omics. These have been driven by rapid advances in laboratory techniques and equipment. Crucially, improved information handling capabilities have allowed concepts such as artificial intelligence and machine learning to enter the research world. The COVID-19 pandemic has shown how quickly information can be generated and analyzed using such approaches, but also showed its limitations. This review will look at how "omics" has begun to be translated into clinical practice. While there appears almost limitless potential in using big data for "precision" or "personalized" medicine, the reality is that this remains largely aspirational. Oncology is the only field of medicine that is widely adopting such technologies, and even in this field uptake is irregular. There are practical and ethical reasons for this lack of translation of increasingly affordable techniques into the clinic. Undoubtedly, there will be increasing use of large data sets from traditional (e.g. tumor samples, patient genomics) and nontraditional (e.g. smartphone) sources. It is perhaps the greatest challenge of the health-care sector over the coming decade to integrate these resources in an effective, practical and ethical way.

Precision Medicine, AI, and the Future of Personalized Health Care

The convergence of artificial intelligence (AI) and precision medicine promises to revolutionize health care. Precision medicine methods identify phenotypes of patients with less‐common responses to treatment or unique healthcare needs. AI leverages sophisticated computation and inference to generate insights, enables the system to reason and learn, and empowers clinician decision making through augmented intelligence. Recent literature suggests that translational research exploring this convergence will help solve the most difficult challenges facing precision medicine, especially those in which nongenomic and genomic determinants, combined with information from patient symptoms, clinical history, and lifestyles, will facilitate personalized diagnosis and prognostication.

Has the introduction of direct oral anticoagulants (DOACs) in England increased emergency admissions for bleeding conditions? A longitudinal ecological study

OBJECTIVE

There is concern about long-term safety of direct oral coagulants (DOACs) in clinical practice. Our aim was to investigate whether the introduction of DOACs compared with vitamin-K antagonists in England was associated with a change in admissions for bleeding or thromboembolic complications.

SETTING

5508 General practitioner (GP) practices in England between 2011 and 2016.

PARTICIPANTS

All GP practices in England with a registered population size of greater than 1000 that had data for all 6 years.

MAIN OUTCOME MEASURE

The rate of emergency admissions to hospital for bleeding or thromboembolism, per 100 000 population for each GP practice in England.

MAIN EXPOSURE MEASURE

The annual number of DOAC items prescribed for each GP practice population as a proportion of all anticoagulant items prescribed.

DESIGN

This longitudinal ecological study used panel regression models to investigate the association between trends in DOAC prescribing within GP practice populations and trends in emergency admission rates for bleeding and thromboembolic conditions, while controlling for confounders.

RESULTS

For each additional 10% of DOACs prescribed as a proportion of all anticoagulants, there was a 0.9% increase in bleeding complications (rate ratio 1.008 95% CI 1.003 to 1.013). The introduction of DOACs between 2011 and 2016 was associated with additional 4929 (95% CI 2489 to 7370) emergency admissions for bleeding complications. Increased DOAC prescribing was associated with a slight decline in admission for thromboembolic conditions.

CONCLUSION

Our data show that the rapid increase in prescribing of DOACs after changes in National Institute for Health and Care Excellence guidelines in 2014 may have been associated with a higher rate of emergency admissions for bleeding conditions. These consequences need to be considered in assessing the benefits and costs of the widespread use of DOACs.

Stencil Printing-A Novel Manufacturing Platform for Orodispersible Discs

Stencil printing is a commonly used printing method, but it has not previously been used for production of pharmaceuticals. The aim of this study was to explore whether stencil printing of drug containing polymer inks could be used to manufacture flexible dosage forms with acceptable mass and content uniformity. Formulation development was supported by physicochemical characterization of the inks and final dosage forms. The printing of haloperidol (HAL) discs was performed using a prototype stencil printer. Ink development comprised of investigations of ink rheology in combination with printability assessment. The results show that stencil printing can be used to manufacture HAL doses in the therapeutic treatment range for 6–17 year-old children. The therapeutic HAL dose was achieved for the discs consisting of 16% of hydroxypropyl methylcellulose (HPMC) and 1% of lactic acid (LA). The formulation pH remained above pH 4 and the results imply that the drug was amorphous. Linear dose escalation was achieved by an increase in aperture area of the print pattern, while keeping the stencil thickness fixed. Disintegration times of the orodispersible discs printed with 250 and 500 µm thick stencils were below 30 s. In conclusion, stencil printing shows potential as a manufacturing method of pharmaceuticals.

Biomarker-guided trials: Challenges in practice

Biomarker-guided trials have drawn considerable attention as they promise to lead to improvements in the benefit-risk ratio of treatments and enhanced opportunities for drug development. A variety of such designs have been proposed in the literature, many of which have been adopted in practice. Implementing such trial designs in practice can be challenging, and identifying those challenges was the main objective of a workshop organised by the MRC Hubs for Trials Methodology Research Network's Stratified Medicine Working Group in March 2017. Participants reflected on completed and ongoing biomarker-guided trials to identify the practical challenges encountered. Here, the key challenges identified during the workshop including those related to funding, ethical and regulatory issues, recruitment, monitoring of samples and laboratories, biomarker assessment, and data sharing and resources, are discussed. Despite the complexities often associated with biomarker-guided trials, the workshop concluded that they can play an important role in advancing the field of personalised medicine. Therefore, it is important that the practical challenges surrounding their implementation are acknowledged and addressed.

Translational genomics and precision medicine: Moving from the lab to the clinic

Translational genomics aims to improve human health by building on discoveries made through genetics research and applying them in the clinical setting. This progress has been made possible by technological advances in genomics and analytics and by the digital revolution. Such advances should enable the development of prognostic markers, tailored interventions, and the design of prophylactic preventive approaches. We are at the cusp of predicting disease risk for some disorders by means of polygenic risk scores integrated with classical epidemiological risk factors. This should lead to better risk stratification and clinical decision-making. A deeper understanding of the link between genome-wide sequence and association with well-characterized phenotypes will empower the development of biomarkers to aid diagnosis, inform disease progression trajectories, and allow better targeting of treatments to those patients most likely to respond.