Pharmacogenomic information in drug labels: European Medicines Agency perspective

Systematic analysis of the pharmacogenomics landscape towards clinical implementation of precision therapeutics in Greece

Pharmacogenomics (PGx) aims to delineate a patient's genetic profile with differences in drug efficacy and/or toxicity, particularly focusing on genes encoding for drug-metabolizing enzymes and transporters. Clinical implementation of PGx is a complex undertaking involving a multidisciplinary approach that includes, among others, a thorough understanding of a country's preparedness to adopt this modern discipline and a detailed knowledge of PGx biomarkers allelic spectrum at a population level. In several European populations, particularly in countries with lower income, clinical implementation of PGx is still in its infancy. We have previously performed a pilot study to determine the prevalence of PGx biomarkers in 18 European populations, as the first step towards population PGx at the European level. Here, we provide a comprehensive analysis of the current state of PGx in Greece, including a detailed allelic frequency spectrum of clinically actionable PGx biomarkers, the level of PGx education in academia, the provision of PGx testing services from public and private laboratories, and the aspects of the regulatory PGx environment, especially with respect to the discrepancies between the Greek National Organization of Medicines and the European Medicine Agency and health technology assessment. This study would not only provide the foundations for expediting the adoption of PGx in clinical reality in Greece but can also serve as a paradigm for replicating future studies in other European countries, to expand on previously available pilot studies.

The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation

Pharmacogenetics promises to optimize treatment-related outcomes by informing optimal drug selection and dosing based on an individual's genotype in conjunction with other important clinical factors. Despite significant evidence of genetic associations with drug response, pharmacogenetic testing has not been widely implemented into clinical practice. Among the barriers to broad implementation are limited guidance for how to successfully integrate testing into clinical workflows and limited data on outcomes with pharmacogenetic implementation in clinical practice. The Pharmacogenomics Global Research Network Implementation Working Group seeks to engage institutions globally that have implemented pharmacogenetic testing into clinical practice or are in the process or planning stages of implementing testing to collectively disseminate data on implementation strategies, metrics, and health-related outcomes with the use of genotype-guided drug therapy to ultimately help advance pharmacogenetic implementation. This paper describes the goals, structure, and initial projects of the group in addition to implementation priorities across sites and future collaborative opportunities.

Allele frequency of genetic variations related to the UGT1A1 gene-drug pair in a group of Iranian population

Objectives

The efficacy and safety of drug treatments vary widely due to genetic variations. Pharmacogenomics investigates the impact of genetic variations on patient drug response. This research investigates the frequency of UGT1A1 genetic variations in the Iranian population, comparing them with global data to provide insights into the pharmacogenomic approach in the Iranian population.

Methods

The study was conducted using the data of the Bushehr Elderly Health (BEH) program, a population-based cohort study of the elderly population aged ≥ 60 years. Genotyping of three UGT1A1 variant alleles (UGT1A1*6, UGT1A1*27, and UGT1A1*80) was performed on a group of 2730 elderly Iranian participants with the Infinium Global Screening Array.

Results

The genotyping analysis revealed significant differences compared to major global populations that were addressed in the gnomAD database. UGT1A1*80 was found at a high frequency (32.34%), and followed by UGT1A1*6 (0.76%) and UGT1A1*27 (0.018) at a low frequency in the Iranian group.

Conclusions

The UGT1A1*80 was the more prevalent allele between investigated alleles in the present study which can be considered as an important allele for pharmacogenomic testing.

Pharmacogenetic DPYD allele variant frequencies: A comprehensive analysis across an ancestrally diverse Iranian population

BACKGROUND

Cancer treatment has improved over the past decades, but many cancer patients still experience adverse drug reactions (ADRs). Pharmacogenomics (PGx), known as personalized treatment, is a pillar of precision medicine that aims to optimize the efficacy and safety of medications by studying the germline variations. Germline variations in the DPYD lead to significant ADRs. The present cross-sectional study aims to evaluate the allele frequency of the DPYD gene variations in the Iranian population to provide insights into personalized treatment decisions in the Iranian population.

METHODS

The allele frequency of 51 pharmacogenetic variations in the clinically relevant DPYD was assessed in a representative sample set of 1142 unrelated Iranian individuals and subpopulations of different ethnic groups who were genotyped using the Infinium Global Screening Array-24 BeadChip.

RESULTS

The genotyping assay revealed eight pharmacogenetic variants including DPYD rs1801265 (c.85T > C; DPYD*9A), rs2297595 (c.496A > G), rs1801158 (c.1601G > A; DPYD*4), rs1801159 (c.1627A > G; DPYD*5), rs1801160 (c.2194G > A; DPYD*6), rs17376848 (c.1896T > C), rs56038477 (c.1236G > A; HapB3), and rs75017182 (c.1129-5923C > G; HapB3) with minor allele frequency (MAF) ≥ 1%.

CONCLUSION

The results of the study reveal significant genetic variations among Iranian population that could significantly influence clinical decision-making. These variants, with their potential to explain the substantial variability in drug response phenotypes among different populations, shed light on a crucial aspect of pharmacogenomics. These findings not only provide valuable insights but also inspire the design and implementation of future pharmacogenomic clinical trials, motivating further research in this crucial area.

Genetic ancestry in population pharmacogenomics unravels distinct geographical patterns related to drug toxicity

Genetic ancestry plays a major role in pharmacogenomics, and a deeper understanding of the genetic diversity among individuals holds immerse promise for reshaping personalized medicine. In this pivotal study, we have conducted a large-scale genomic analysis of 1,136 pharmacogenomic variants employing machine learning algorithms on 3,714 individuals from publicly available datasets to assess the risk proximity of experiencing drug-related adverse events. Our findings indicate that Admixed Americans and Europeans have demonstrated a higher risk of experiencing drug toxicity, whereas individuals with East Asian ancestry and, to a lesser extent, Oceanians displayed a lower risk proximity. Polygenic risk scores for drug-gene interactions did not necessarily follow similar assumptions, reflecting distinct genetic patterns and population-specific differences that vary depending on the drug class. Overall, our results provide evidence that genetic ancestry is a pivotal factor in population pharmacogenomics and should be further exploited to strengthen even more personalized drug therapy.

A qualitative approach to assess the opinion of physicians about the challenges and prospects of pharmacogenomic testing implementation in clinical practice in Greece

BACKGROUND

Pharmacogenomics (PGx) constitutes an important part of personalized medicine and has several clinical applications. PGx role in clinical practice is known, however, it has not been widely adopted yet. In this study, we aim to investigate the perspectives of Greek physicians regarding the implementation of PGx testing in clinical practice and the key issues associated with it.

METHODS

Fourteen interviews were conducted with physicians of various specialties for which PGx applications are available. A semi-structured interview guide was utilized based on the Consolidated Framework for Implementation Research (CFIR) context and the Diffusion of Innovation model. Transcripts were coded independently and compared by two members of the research team. Descriptive statistics were generated using Microsoft Excel.

RESULTS

Six main themes emerged: awareness and use of PGx testing; source of information; key stakeholders of the PGx supply chain, their interactions and change agents; clinical benefit and significance of PGx testing; barriers and lack of reimbursement; and recommendations to boost the PGx adoption rate. Most respondents were aware of PGx applications, but only three had already recommended PGx testing. Peer-reviewed journals along with clinical guidelines were regarded as the most used source of information while stakeholders of the PGx supply chain were discussed. PGx was considered that promote patient-centered care, enhance medication clinical effectiveness, decrease the risk of side effects, and reduce healthcare costs. Lack of reimbursement, scarcity of resources, and high PGx cost were the foremost barriers affecting PGx adoption.

CONCLUSIONS

It was concluded that if case PGx testing is reimbursed and physicians' training is reinforced, PGx implementation will be boosted and improved shortly.

Pharmacogenomic biomarker information on drug labels of the Spanish Agency of Medicines and Sanitary products: evaluation and comparison with other regulatory agencies

This work aimed to analyse the pharmacogenetic information in the Spanish Drug Regulatory Agency (AEMPS) Summary of Products Characteristics (SmPC), evaluating the presence of pharmacogenetic biomarkers, as well as the associated recommendations. A total of 55.4% of the 1891 drug labels reviewed included information on pharmacogenetic biomarker(s). Pharmacogenomic information appears most frequently in the "antineoplastic and immunomodulating agents", "nervous system", and "cardiovascular system" Anatomical Therapeutic Chemical groups. A total of 509 different pharmacogenetic biomarkers were found, of which CYP450 enzymes accounted for almost 34% of the total drug-biomarker associations evaluated. A total of 3679 drug-biomarker pairs were identified, 102 of which were at the 1A level (PharmGKB® classification system), and 33.33% of these drug-pharmacogenetic biomarker pairs were assigned to "actionable PGx", 12.75% to "informative PGx", 4.9% to "testing recommended", and 4.9% to "testing required". The rate of coincidence in the assigned PGx level of recommendation between the AEMPS and regulatory agencies included in the PharmGKB® Drug Label Annotations database (i.e., the FDA, EMA, SWISS Medic, PMDA, and HCSC) ranged from 45% to 65%, being 'actionable level' the most frequent. On the other hand, discrepancies between agencies did not exceed 35%. This study highlights the presence of relevant pharmacogenetic information on Spanish drug labels, which would help avoid interactions, toxicity, or lack of treatment efficacy.

Drug Metabolizing Enzymes: An Exclusive Guide into Latest Research in Pharmaco-genetic Dynamics in Arab Countries

Drug metabolizing enzymes play a crucial role in the pharmacokinetics and pharmacodynamics of therapeutic drugs, influencing their efficacy and safety. This review explores the impact of genetic polymorphisms in drug-metabolizing genes on drug response within Arab populations. We examine the genetic diversity specific to Arab countries, focusing on the variations in key drug-metabolizing enzymes such as CYP450, GST, and UGT families. The review highlights recent research on polymorphisms in these genes and their implications for drug metabolism, including variations in allele frequencies and their effects on therapeutic outcomes. Additionally, the paper discusses how these genetic variations contribute to the variability in drug response and adverse drug reactions among individuals in Arab populations. By synthesizing current findings, this review aims to provide a comprehensive understanding of the pharmacogenetic landscape in Arab countries and offer insights into personalized medicine approaches tailored to genetic profiles. The findings underscore the importance of incorporating pharmacogenetic data into clinical practice to enhance drug efficacy and minimize adverse effects, ultimately paving the way for more effective and individualized treatment strategies in the region.

Structure-activity relationships andz interindividual variability of drug responses: pharmacogenomics with antimicrobial drugs as a paradigm

Adverse drug reactions represent a major health burden because they cause notable patient morbidity and mortality. From this viewpoint, several strategies have been developed to prevent or reduce adverse drug reactions. One such strategy is the use of pharmacogenomics. Interindividual variability in drug response and adverse effects is mainly attributable to genetic variation in enzymes such as sulfotransferases and cytochrome P450s. The current narrative review discusses the relationship between the structure and activity of drugs. Specifically, the activity of drugs can be increased and/or their adverse effects can be reduced by altering specific positions in their structures.

Cardiovascular precision medicine - A pharmacogenomic perspective

Precision medicine envisages the integration of an individual's clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.

Using human genetics to improve safety assessment of therapeutics

Human genetics research has discovered thousands of proteins associated with complex and rare diseases. Genome-wide association studies (GWAS) and studies of Mendelian disease have resulted in an increased understanding of the role of gene function and regulation in human conditions. Although the application of human genetics has been explored primarily as a method to identify potential drug targets and support their relevance to disease in humans, there is increasing interest in using genetic data to identify potential safety liabilities of modulating a given target. Human genetic variants can be used as a model to anticipate the effect of lifelong modulation of therapeutic targets and identify the potential risk for on-target adverse events. This approach is particularly useful for non-clinical safety evaluation of novel therapeutics that lack pharmacologically relevant animal models and can contribute to the intrinsic safety profile of a drug target. This Review illustrates applications of human genetics to safety studies during drug discovery and development, including assessing the potential for on- and off-target associated adverse events, carcinogenicity risk assessment, and guiding translational safety study designs and monitoring strategies. A summary of available human genetic resources and recommended best practices is provided. The challenges and future perspectives of translating human genetic information to identify risks for potential drug effects in preclinical and clinical development are discussed.

ABCG2 and SLCO1B1 gene polymorphisms in the Croatian population

BACKGROUND

Organic anion-transporting polypeptide 1B1 (OATP1B1) and the ATP-binding cassette subfamily G member 2, ABCG2, are important transporters involved in the transport of endogenous substrates and xenobiotics, including drugs. Genetic polymorphisms of these transporters have effect on transporter activity. There is significant interethnic variability in the frequency of allele variants.

AIM

To determined allele and genotype frequencies of ABCG2 and SLCO1B1 genes in Croatian populations of European descent.

SUBJECTS AND METHODS

A total of 905 subjects (482 women) were included. Genotyping for ABCG2 c.421C > A (rs2231142) and for SLCO1B1 c.521T > C (rs4149056), was performed by real-time polymerase chain reaction (PCR) using TaqMan^® DME Genotyping Assays.

RESULTS

For ABCG2 c.421C > A, the frequency of CC, CA and AA genotypes was 81.4%, 17.8% and 0.8% respectively. The frequency of variant ABCG2 421 A allele was 9.7%. For SLCO1B1 c.521T > C, the frequency of TT, TC and CC genotypes was 61.7%, 34.8% and 3.5% respectively. The frequency of variant SLCO1B1 521 C allele was 20.9%.

CONCLUSION

The frequency of the ABCG2 and SLCO1B1 allelic variants and genotypes in the Croatian population is in accordance with other European populations. Pharmacogenetic analysis can serve to individualise drug therapy and minimise the risk of developing adverse drug reactions.

Population genetic polymorphisms of pharmacogenes in Zimbabwe, a potential guide for the safe and efficacious use of medicines in people of African ancestry

OBJECTIVE

Pharmacogenomics (PGx) is a clinically significant factor in the safe and efficacious use of medicines. While PGx knowledge is abundant for other populations, there are scarce PGx data on African populations and is little knowledge on drug-gene interactions for medicines used to treat diseases common in Africa. The aim of this study was to use a custom-designed open array to genotype clinically actionable variants in a Zimbabwean population. This study also identified some of the commonly used drugs in Zimbabwe and the associated genes involved in their metabolism.

METHODS

A custom-designed open array that covers 120 genetic variants was used to genotype 522 black Zimbabwean healthy volunteers using TaqMan-based single nucleotide polymorphism genotyping. Data were also accessed from Essential Drugs' List in Zimbabwe (EDLIZ), and the medicines were grouped into the associated biomarker groups based on their metabolism. We also estimated the national drug procurement levels for medicines that could benefit from PGx-guided use based on the data obtained from the national authorities in Zimbabwe.

RESULTS

The results demonstrate the applicability of an open-array chip in simultaneously determining multiple genetic variants in an individual, thus significantly reducing cost and time to generate PGx data. There were significantly high frequencies of African-specific variants, such as the CYP2D6*17 and *29 variants and the CYP2B6*18 variant. The data obtained showed that the Zimbabwean population exhibits PGx variations in genes important for the safe and efficacious use of drugs approved by the EDLIZ and are procured at significantly large amounts annually. The study has established a cohort of genotyped healthy volunteers that can be accessed and used in the conduct of clinical pharmacogenetic studies for drugs entering a market of people of predominantly African ancestry.

CONCLUSION

Our study demonstrated the potential benefit of integrating PGx in Zimbabwe for the safe and efficacious use of drugs that are commonly used.

Genetic diversity of CYP3A5 and ABCB1 variants in East-Central and South European populations

BACKGROUND

CYP3A5 enzyme encoded by CYP3A5 is important for drug metabolism in gut and liver, whereas P-glycoprotein by ABCB1, is an ATP-dependent drug efflux pump which exports endo- and exogenous substances outside the cell.

AIM

The study was to assess the prevalence of CYP3A5 alleles: *1, *2, *3, *4, *6 and *7, and C and T of ABCB1 in Poles, Belarusians and Bosnians and to compare it with the data reported from other European populations.

SUBJECTS AND METHODS

Overall, 511 unrelated healthy subjects from Poland (n = 239), Belarus (n = 104) and Bosnia and Herzegovina (n = 168) were included in this study. Allele frequencies and statistical parameters (AMOVA version 2.9.3) were determined.

RESULTS

In Poles, Belarusians and Bosnians the *3 allele of CYP3A5 was the most common, and wild-type allele *1, were: 5.8%, 1.6% and 2.1%, respectively. Allele *2 was very rare, and alleles *4, *6 and *7 were not detected. For the populations mentioned above, the ABCB1 allele C was: 48.1%, 51.4%, 52.4%, respectively.

CONCLUSION

In compared populations, the distribution of CYP3A5 variants but not ABCB1, differed significantly. Alleles *4, *6 and *7 of CYP3A5 did not occur or occurred rarely.

Effects of Pharmacogenomic Testing in Clinical Pain Management: Retrospective Study

BACKGROUND

The availability of pharmacogenomic (PGx) methods to determine the right drug and dosage for individualized patient treatment has increased over the past decade. Adoption of the resulting PGx reports in a clinical setting and monitoring of clinical outcomes is a challenging and long-term commitment.

OBJECTIVE

This study summarizes an extended PGx deep sequencing panel intended for medication dosing and prescription guidance newly adopted in a pain management clinic. The primary outcome of this retrospective study reports the number of cases and types of drugs covered, for which PGx data appears to have assisted in optimal drug prescription and dosing.

METHODS

A PGx panel is described, encompassing 23 genes and 141 single-nucleotide polymorphisms or indels, combined with PGx dosing guidance and drug-gene interaction (DGI) and drug-drug interaction (DDI) reporting to prevent adverse drug reactions (ADRs). During a 2-year period, patients (N=171) were monitored in a pain management clinic. Urine toxicology, PGx reports, and progress notes were studied retrospectively for changes in prescription regimens before and after the PGx report was made available to the provider. An additional algorithm provided DGIs and DDIs to prevent ADRs.

RESULTS

Among patient PGx reports with medication lists provided (n=146), 57.5% (n=84) showed one or more moderate and 5.5% (n=8) at least one serious PGx interaction. A total of 96 (65.8%) patients showed at least one moderate and 15.1% (n=22) one or more serious DGIs or DDIs. A significant number of active changes in prescriptions based on the 102 PGx/DGI/DDI report results provided was observed for 85 (83.3%) patients for which a specific drug was either discontinued or switched within the defined drug classes of the report, or a new drug was added.

CONCLUSIONS

Preventative action was observed for all serious interactions, and only moderate interactions were tolerated for the lack of other alternatives. This study demonstrates the application of an extended PGx panel combined with a customized informational report to prevent ADRs and improve patient care.

Implementation of CYP2D6 copy-number imputation panel and frequency of key pharmacogenetic variants in Finnish individuals with a psychotic disorder

We demonstrate that CYP2D6 copy-number variation (CNV) can be imputed using existing imputation algorithms. Additionally, we report frequencies of key pharmacogenetic variants in individuals with a psychotic disorder from the genetically bottle-necked population of Finland. We combined GWAS chip and CYP2D6 CNV data from the Breast Cancer Pain Genetics study to construct an imputation panel (n = 902) for CYP2D6 CNV. The resulting data set was used as a CYP2D6 CNV imputation panel in 9262 non-related individuals from the SUPER-Finland study. Based on imputation of 9262 individuals we confirm the higher frequency of CYP2D6 ultrarapid metabolizers and a 22-fold enrichment of the UGT1A1 decreased function variant rs4148323 (UGT1A1*6) in Finland compared with non-Finnish Europeans. Similarly, the NUDT15 variant rs116855232 was highly enriched in Finland. We demonstrate that imputation of CYP2D6 CNV is possible and the methodology enables studying CYP2D6 in large biobanks with genome-wide data.

Clinical pharmacogenetic analysis in 5,001 individuals with diagnostic Exome Sequencing data

Exome sequencing is utilized in routine clinical genetic diagnosis. The technical robustness of repurposing large-scale next-generation sequencing data for pharmacogenetics has been demonstrated, supporting the implementation of preemptive pharmacogenetic strategies based on adding clinical pharmacogenetic interpretation to exomes. However, a comprehensive study analyzing all actionable pharmacogenetic alleles contained in international guidelines and applied to diagnostic exome data has not been performed. Here, we carried out a systematic analysis based on 5001 Spanish or Latin American individuals with diagnostic exome data, either Whole Exome Sequencing (80%), or the so-called Clinical Exome Sequencing (20%) (60 Mb and 17 Mb, respectively), to provide with global and gene-specific clinical pharmacogenetic utility data. 788 pharmacogenetic alleles, distributed through 19 genes included in Clinical Pharmacogenetics Implementation Consortium guidelines were analyzed. We established that Whole Exome and Clinical Exome Sequencing performed similarly, and 280 alleles in 11 genes (CACNA1S, CYP2B6, CYP2C9, CYP4F2, DPYD, G6PD, NUDT15, RYR1, SLCO1B1, TPMT, and UGT1A1) could be used to inform of pharmacogenetic phenotypes that change drug prescription. Each individual carried in average 2.2 alleles and overall 95% (n = 4646) of the cohort could be informed of at least one actionable pharmacogenetic phenotype. Differences in variant allele frequency were observed among the populations studied and the corresponding gnomAD population for 7.9% of the variants. In addition, in the 11 selected genes we uncovered 197 novel variants, among which 27 were loss-of-function. In conclusion, we provide with the landscape of actionable pharmacogenetic information contained in diagnostic exomes, that can be used preemptively in the clinics.

Pharmacogenetics of Drugs Used in the Treatment of Cancers

Pharmacogenomics is based on the understanding of the individual differences in drug use, the response to drug therapy (efficacy and toxicity), and the mechanisms underlying variable drug responses. The identification of DNA variants which markedly contribute to inter-individual variations in drug responses would improve the efficacy of treatments and decrease the rate of the adverse side effects of drugs. This review focuses only on the impact of polymorphisms within drug-metabolizing enzymes on drug responses. Anticancer drugs usually have a very narrow therapeutic index; therefore, it is very important to use appropriate doses in order to achieve the maximum benefits without putting the patient at risk of life-threatening toxicities. However, the adjustment of the appropriate dose is not so easy, due to the inheritance of specific polymorphisms in the genes encoding the target proteins and drug-metabolizing enzymes. This review presents just a few examples of such polymorphisms and their impact on the response to therapy.

Gene-drug pairings for antidepressants and antipsychotics: level of evidence and clinical application

Substantial inter-individual discrepancies exist in both therapeutic effectiveness and adverse effects of antidepressant and antipsychotic medications, which can, in part, be explained by genetic variation. Here, we searched the Pharmacogenomics Knowledge Base for gene-antidepressant and gene-antipsychotic pairs with the highest level of evidence. We then extracted and compared the associated prescribing recommendations for these pairs developed by the Clinical Pharmacogenomics Implementation Consortium, the Dutch Pharmacogenetics Working Group or approved product labels in the US, Canada, Europe, and Asia. Finally, we highlight key economical, educational, regulatory, and ethical issues that, if not appropriately considered, can hinder the implementation of these recommendations in clinical practice. Our review indicates that evidence-based guidelines are available to assist with the implementation of pharmacogenetic-guided antidepressant and antipsychotic prescribing, although the maximum impact of these guidelines on patient care will not be realized until key barriers are minimized or eliminated.

Biomarker and Companion Diagnostics-A Review of Medicinal Products Approved by the European Medicines Agency

Background: An increasing number of medicines authorised in Europe recommend or require biomarker-based patient selection. For some of these the use of a companion diagnostic (CDx), a subset of in vitro diagnostics (IVDs), to identify patient populations eligible for a specific medicinal product may be required. The information and recommendations of use of a medicinal product for which a CDx is required is particularly important to healthcare professionals for correct patient identification.

Methods: We reviewed the existing information in SmPCs and European Public Assessment Reports (EPARs) of EU medicinal products approved via the centralised procedure at EMA where reference was made to biomarker testing, including by CDx, for patient selection.

Results: The results show that varying levels of detail are provided for the biomarker and the diagnostic test, including variability in where the information was presented. The overall results demonstrate transparent but sometimes heterogeneous reporting of CDx in the SmPC and EPAR.

Conclusions: With the introduction of the new Regulation (EU) 2017/746 on in vitro diagnostic medical devices, medicines regulatory authorities' will be required to be consulted during the review of CDx conformity assessment and so, there is opportunity for more consistent and transparent information on CDx to be provided in the SmPC and EPAR.

A novel machine learning-based approach for the computational functional assessment of pharmacogenomic variants

BACKGROUND

The field of pharmacogenomics focuses on the way a person's genome affects his or her response to a certain dose of a specified medication. The main aim is to utilize this information to guide and personalize the treatment in a way that maximizes the clinical benefits and minimizes the risks for the patients, thus fulfilling the promises of personalized medicine. Technological advances in genome sequencing, combined with the development of improved computational methods for the efficient analysis of the huge amount of generated data, have allowed the fast and inexpensive sequencing of a patient's genome, hence rendering its incorporation into clinical routine practice a realistic possibility.

METHODS

This study exploited thoroughly characterized in functional level SNVs within genes involved in drug metabolism and transport, to train a classifier that would categorize novel variants according to their expected effect on protein functionality. This categorization is based on the available in silico prediction and/or conservation scores, which are selected with the use of recursive feature elimination process. Toward this end, information regarding 190 pharmacovariants was leveraged, alongside with 4 machine learning algorithms, namely AdaBoost, XGBoost, multinomial logistic regression, and random forest, of which the performance was assessed through 5-fold cross validation.

RESULTS

All models achieved similar performance toward making informed conclusions, with RF model achieving the highest accuracy (85%, 95% CI: 0.79, 0.90), as well as improved overall performance (precision 85%, sensitivity 84%, specificity 94%) and being used for subsequent analyses. When applied on real world WGS data, the selected RF model identified 2 missense variants, expected to lead to decreased function proteins and 1 to increased. As expected, a greater number of variants were highlighted when the approach was used on NGS data derived from targeted resequencing of coding regions. Specifically, 71 variants (out of 156 with sufficient annotation information) were classified as to "Decreased function," 41 variants as "No" function proteins, and 1 variant in "Increased function."

CONCLUSION

Overall, the proposed RF-based classification model holds promise to lead to an extremely useful variant prioritization and act as a scoring tool with interesting clinical applications in the fields of pharmacogenomics and personalized medicine.

Variability of Pharmacogenomics Information in Drug Labels Approved by Different Agencies and Its Ethical Implications

AIMS

The aim of this study was to determine if there are discrepancies among various agency-approved labels for the same active ingredient and where the labels approved by the Turkish Medicines and Medical Devices Agency (TMMDA) stand regarding the inclusion of PGx and discuss these ethical implications.

BACKGROUND

The efficacy and safety of drugs can be improved by rational prescription and personalization of medicine for each patient. Pharmacogenomics information (PGx) in drug labels (DL) is one of the important tools for the personalization of medications because genetic differences may affect both drug efficacy and safety. Providing adequate PGx to patients has ethical implications.

OBJECTIVE

To evaluate PGx in the DLs approved by TMMDA and other national agencies provided by the Pharmacogenomics Knowledgebase.

METHODS

DL annotations from the Pharmacogenomics Knowledgebase and DLs approved by the TMMDA were analyzed according to information and action levels, which are "testing required", "testing recommended", "actionable", and "informative".

RESULTS

There are 381 drugs listed in PharmGKB drug label annotations with pharmacogenomics information and 278 of these have biomarkers. A total of 242 (63.5%) drugs are approved and available in Turkey. Of these, 207 (85.5%) contain the same information as in or similar to that in the labels approved by the other agencies. The presence and level of information varied among the DLs approved by different agencies. The inconsistencies may have an important effect on the efficacy and the safety of drugs.

CONCLUSION

These findings suggest a need for the standardization of PGx information globally because it may not only affect the efficacy and safety of medications but also essential ethical rules regarding patient rights by violating not sufficiently sharing all available information.

Efficacy and safety of levetiracetam versus (fos)phenytoin for second-line treatment of epilepticus: a meta-analysis of latest randomized controlled trials

OBJECTIVES

To assess the efficiency and safety profiles of levetiracetam and (fos)phenytoin (phenytoin or fosphenytoin) for second-line treatment of seizures by performing a meta-analysis of RCTs.

METHODS

We systematically searched PubMed, Embase, Cochrane, FDA.gov, and ClinicalTrials.gov for RCTs (published before July 31, 2020; no language restrictions). Two independent reviewers screened abstracts and titles against inclusion and exclusion criteria published previously in the PROSPERO: CRD42020202736. Eleven studies fulfilled the established criteria. We assessed pooled data by using a random-effects model. Quality analysis was performed by using version 2 of the Cochrane risk-of-bias tool (RoB 2). RevMan v.5.3 was used to perform statistical analyses, and publication bias (egger's test) was assessed with Stata MP v.14.0.

RESULTS

Levetiracetam was similar to (fos)phenytoin in seizure termination rate (risk ratio [RR] 0.94; 95% CI 0.87 to 1.01), time of seizure termination (mean difference [MD] 0.44; -0.60 to 1.49), and drug resistance ([RR] 1.12, 0.86 to 1.45). The safety outcome showed a significant statistical difference between fosphenytoin group and levetiracetam group ([RR] 1.44, 1.14 to 1.81), while there was no significant difference observed between phenytoin treatment and levetiracetam treatment ([RR] 1.26, 0.99 to 1.60).

CONCLUSION

Levetiracetam was similar to (fos)phenytoin in cessation rate convulsive status epilepticus, and drug resistance, while it was superior (fos)phenytoin in pooled safety outcome. Further exploration is still needed as to whether it is the first choice for second-line drugs.

Cytogenetic and Biochemical Genetic Techniques for Personalized Drug Therapy in Europe

For many authorized drugs, accumulating scientific evidence supports testing for predictive biomarkers to apply personalized therapy and support preventive measures regarding adverse drug reactions and treatment failure. Here, we review cytogenetic and biochemical genetic testing methods that are available to guide therapy with drugs centrally approved in the European Union (EU). We identified several methods and combinations of techniques registered in the Genetic Testing Registry (GTR), which can be used to guide therapy with drugs for which pharmacogenomic-related information is provided in the European public assessment reports. Although this registry provides information on genetic tests offered worldwide, we identified limitations regarding standard techniques applied in clinical practice and the information on test validity rarely provided in the according sections.

Deliberations about clinical pharmacogenetic testing in pediatric oncology

This article summarizes the background, content and outcomes of a special meeting that was convened among oncologists and scientists to discuss the role of pharmacogenetic (PGx) testing in pediatric clinical oncology practice. This meeting provided an opportunity for what the lead author (AM Issa) refers to as the 'voice of the clinician' dynamic to be amplified in order to better understand how personalized or precision medicine applications such as PGx testing are adopted and incorporated into clinical settings and what we can learn from the experiences of current and ongoing implementation PGx approaches to further the implementation of precision medicine applications in real-world environments. Group dynamics and clinical experience with PGx testing and return of results shaped the discussion.

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.

Pharmacogenetic information in Swiss drug labels - a systematic analysis

Implementation of pharmacogenetics (PGx) and individualization of drug therapy is supposed to obviate adverse drug reactions or therapy failure. Health care professionals (HCPs) use drug labels (DLs) as reliable information about drugs. We analyzed the Swiss DLs to give an overview on the currently available PGx instructions. We screened 4306 DLs applying natural language processing focusing on drug metabolism (pharmacokinetics) and we assigned PGx levels following the classification system of PharmGKB. From 5979 hits, 2564 were classified as PGx-relevant affecting 167 substances. 55% (n = 93) were classified as "actionable PGx". Frequently, PGx information appeared in the pharmacokinetics section and in DLs of the anatomic group "nervous system". Unstandardized wording, appearance of PGx information in different sections and unclear instructions challenge HCPs to identify and interpret PGx information and translate it into practice. HCPs need harmonization and standardization of PGx information in DLs to personalize drug therapies and tailor pharmaceutical care.

Pharmacogenomic Biomarkers and Their Applications in Psychiatry

Realizing the promise of precision medicine in psychiatry is a laudable and beneficial endeavor, since it should markedly reduce morbidity and mortality and, in effect, alleviate the economic and social burden of psychiatric disorders. This review aims to summarize important issues on pharmacogenomics in psychiatry that have laid the foundation towards personalized pharmacotherapy and, in a broader sense, precision medicine. We present major pharmacogenomic biomarkers and their applications in a variety of psychiatric disorders, such as depression, attention-deficit/hyperactivity disorder (ADHD), narcolepsy, schizophrenia, and bipolar disorder. In addition, we extend the scope into epilepsy, since antiepileptic drugs are widely used to treat psychiatric disorders, although epilepsy is conventionally considered to be a neurological disorder.

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.

Bringing Greater Accuracy to Europe's Healthcare Systems: The Unexploited Potential of Biomarker Testing in Oncology

Rapid and continuing advances in biomarker testing are not being matched by take-up in health systems, and this is hampering both patient care and innovation. It also risks costing health systems the opportunity to make their services more efficient and, over time, more economical. This paper sets out the potential of biomarker testing, the unfolding precision and range of possible diagnosis and prediction, and the many obstacles to adoption. It offers case studies of biomarker testing in breast, ovarian, prostate, lung, thyroid and colon cancers, and derives specific lessons as to the potential and actual use of each of them. It also draws lessons about how to improve access and alignment, and to remedy the data deficiencies that impede development. And it suggests solutions to outstanding issues - notably including funding and the tangled web of obtaining reimbursement or equivalent coverage that Europe's fragmented health system implies. It urges a European evolution towards an initial minimum testing scenario, which would guarantee universal access to a suite of biomarker tests for the currently most common conditions, and, further into the future, to an optimum testing scenario in which a much wider range of biomarker tests would be introduced and become part of a more sophisticated health system articulated around personalised medicine. For exploiting genomics to the full, it argues the need for a new policy framework for Europe. Biomarker testing is not an issue that can be treated in isolation, since the purpose of testing is to improve health. Its use is therefore always closely linked to specific health challenges and needs to be viewed in the broader policy context in the EU and more widely. The paper is the result of extensive engagement with experts and decision makers to develop the framework, and consequently represents a wide consensus of views on how healthcare systems should respond from push and pull factors at local, national and cross-border and EU level. It contains strong views and clear recommendations springing from the convictions of patients, clinicians, academics, medicines authorities, HTA bodies, payers, the diagnostic, pharmaceutical and ICT industries, and national policy makers.

Knowledge, Perception, and Application of Pharmacogenomics Among Hospital Pharmacists in Saudi Arabia

Introduction

The accelerated transformation in the healthcare system supported by the Saudi Vision 2030 makes the present the best time to start the real application of pharmacogenomics in Saudi Arabia. The current study aimed to assess the knowledge, perception and the application status of pharmacogenomics among pharmacists in the hospital settings in Saudi Arabia.

Methods

This cross-sectional observational survey was conducted among 206 qualified pharmacists working in Saudi hospitals. A self-administered questionnaire was sent to all participants.

Results

Only 30% of the pharmacists had received any type of formal training on PGx. Of these, only nine participants had actually put the knowledge into practice. Participants showed a moderate to low level of knowledge when responded to the pharmacogenomic knowledge indicators used in the study. The low knowledge and the availability of the pharmacogenetic test are the main barriers for the low adoption of the pharmacogenomics in the clinical practice. Approximately 83% felt the need to know more about pharmacogenomics. Participants show positive perception with high motivation levels to incorporate this technology in practice. For example, 76% stated that pharmacogenetic testing should be applied to pharmacy practice. Around 38% of participants reported that the Saudi government and the Saudi FDA had been promoting the pharmacogenomics. However, 50% of the total participants reported that their hospital management is unaware of the pharmacogenomics importance in clinical practice.

Discussion

This study emphasizes on two needs which can help promote the use and implementation of pharmacogenomics. One is the need to update the pharmacy education and training programs with pharmacogenomic-related areas to raise the pharmacist’s knowledge and practical skill to apply pharmacogenomics in the clinical practice effectively. Another need is to increase the awareness of the decision and policy-makers with the importance of pharmacogenomics for the patient benefit and safety. This preliminary evaluation will provide future insight into the best approach to applying pharmacogenomics in the Saudi healthcare system.

Pharmacogenetic-Pharmacokinetic Interactions in Drug Marketing Authorization Applications via the European Medicines Agency Between 2014 and 2017

This study aimed to determine to which extent data on potential pharmacogenetic-pharmacokinetic (PG-PK) interactions are provided to, and assessed by, the European Medicines Agency (EMA) in novel drug marketing authorization applications (MAAs), and whether regulatory assessment of PG-PK interactions is adequate or could be optimized. For this purpose, we retrospectively analyzed MAAs of small molecule drugs assessed by the EMA between January 2014 and December 2017. As per two key requirements in the EMA's guideline, we analyzed cases where (i) a single functionally polymorphic drug metabolizing enzyme (DME) metabolizes > 25% of the drug, or (ii) the drug's PK shows high interindividual variability not explained by other factors than PG. Results showed that, of 113 drugs analyzed, 53 (47%) had ≥ 1 functionally polymorphic DME accounting for > 25% of the drug's metabolism, yielding 55 gene-drug pairs. For 36 of 53 (68%) of the products, CYP3A4 was the major DME. Compliance with European Union (EU) guidance on PG-PK issues in drug development was notably different for CYP3A4 substrates vs. non-CYP3A4 substrates. Adequate PG-PK data were provided during registration in 89% (16/18) of cases concerning non-CYP3A4 substrates, compared with 32% (12/37) of cases concerning CYP3A4 substrates. Concluding, PG-PK interactions related to non-CYP3A4 substrate drugs were, in general, addressed adequately in EU MAAs. PG-PK information on CYP3A4 substrates was available less frequently, despite some available evidence on the functional relevance of CYP3A4 polymorphisms. A more harmonized approach toward assessment of PG-PK issues in EU MAAs seems warranted, and a discussion on the relevance of CYP3A4 polymorphisms, such as CYP3A4*22, is recommended.

Comparison of unsupervised machine-learning methods to identify metabolomic signatures in patients with localized breast cancer

Genomics and transcriptomics have led to the widely-used molecular classification of breast cancer (BC). However, heterogeneous biological behaviors persist within breast cancer subtypes. Metabolomics is a rapidly-expanding field of study dedicated to cellular metabolisms affected by the environment. The aim of this study was to compare metabolomic signatures of BC obtained by 5 different unsupervised machine learning (ML) methods. Fifty-two consecutive patients with BC with an indication for adjuvant chemotherapy between 2013 and 2016 were retrospectively included. We performed metabolomic profiling of tumor resection samples using liquid chromatography-mass spectrometry. Here, four hundred and forty-nine identified metabolites were selected for further analysis. Clusters obtained using 5 unsupervised ML methods (PCA k-means, sparse k-means, spectral clustering, SIMLR and k-sparse) were compared in terms of clinical and biological characteristics. With an optimal partitioning parameter k = 3, the five methods identified three prognosis groups of patients (favorable, intermediate, unfavorable) with different clinical and biological profiles. SIMLR and K-sparse methods were the most effective techniques in terms of clustering. In-silico survival analysis revealed a significant difference for 5-year predicted OS between the 3 clusters. Further pathway analysis using the 449 selected metabolites showed significant differences in amino acid and glucose metabolism between BC histologic subtypes. Our results provide proof-of-concept for the use of unsupervised ML metabolomics enabling stratification and personalized management of BC patients. The design of novel computational methods incorporating ML and bioinformatics techniques should make available tools particularly suited to improving the outcome of cancer treatment and reducing cancer-related mortalities.

Implementation of pharmacogenomics in product information

Aim: The aim of our study was to analyse the level of implementation of pharmacogenomics (PGx) in product information (PI) of medicinal products approved through national procedures in the EU. Materials & methods: In the analysis, we included nationally approved medicinal products in Croatia if guidelines for relevant substances were published. Results: Overall, 265 marketing authorizations were analyzed. The majority of data included in PI was only informative, while the most frequent PGx biomarkers were genes which code CYP P450. Analysis according to the Anatomical Therapeutic Chemical classification revealed that most substances belonged to the nervous system. Conclusion: Although hindrances in implementation are anticipated, PI should be more specific in terms of when the testing is indicated and should include actionable recommendations according to the results of PGx testing.

Precision Medicine in Non-Communicable Diseases

The increase in life expectancy during the 20th century ranks as one of society's greatest achievements, with massive growth in the numbers and proportion of the elderly, virtually occurring in every country of the world. The burden of chronic diseases is one of the main consequences of this phenomenon, severely hampering the quality of life of elderly people and challenging the efficiency and sustainability of healthcare systems. Non-communicable diseases (NCDs) are considered a global emergency responsible for over 70% of deaths worldwide. NCDs are also the basis for complex and multifactorial diseases such as hypertension, diabetes, and obesity. The epidemics of NCDs are a consequence of a complex interaction between health, economic growth, and development. This interaction includes the individual genome, the microbiome, the metabolome, the immune status, and environmental factors such as nutritional and chemical exposure. To counteract NCDs, it is therefore essential to develop an innovative, personalized, preventative, early care model through the integration of different molecular profiles of individuals to identify both the critical biomarkers of NCD susceptibility and to discover novel therapeutic targets.

Adverse drug reactions in primary care: a scoping review

BACKGROUND

Medication-related adverse events, or adverse drug reactions (ADRs) are harmful events caused by medication. ADRs could have profound effects on the patients' quality of life, as well as creating an increased burden on the healthcare system. ADRs are one of the rising causes of morbidity and mortality internationally, and will continue to be a significant public health issue with the increased complexity in medication, to treat various diseases in an aging society. This scoping review aims to provide a detailed map of the most common adverse drug reactions experienced in primary healthcare setting, the drug classes that are most commonly associated with different levels/types of adverse drug reactions, causes of ADRs, their prevalence and consequences of experiencing ADRs.

METHODS

We systematically reviewed electronic databases Ovid MEDLINE, Embase, CINAHL Plus, Cochrane Central Register of Controlled Trials, PsycINFO and Scopus. In addition, the National Patient Safety Foundation Bibliography and the Agency for Health Care Research and Quality and Patient Safety Net Bibliography were searched. Studies published from 1990 onwards until December 7, 2018 were included as the incidence of reporting drug reactions were not prevalent before 1990. We only include studies published in English.

RESULTS

The final search yielded a total of 19 citations for inclusion published over a 15-year period that primarily focused on investigating the different types of adverse drug reactions in primary healthcare. The most causes of adverse events were related to drug related and allergies. Idiosyncratic adverse reactions were not very commonly reported. The most common adverse drug reactions reported in the studies included in this review were those that are associated with the central nervous system, gastrointestinal system and cardiovascular system. Several classes of medications were reported to be associated with adverse events.

CONCLUSION

This scoping review identified that the most causes of ADRs were drug related and due to allergies. Idiosyncratic adverse reactions were not very commonly reported in the literature. This is mainly because it is hard to predict and these reactions are not associated with drug doses or routes of administration. The most common ADRs reported in the studies included in this review were those that are associated with the central nervous system, gastrointestinal system and cardiovascular system. Several classes of medications were reported to be associated with ADRs.

Pharmacogenomics of Antidepressant and Antipsychotic Treatment: How Far Have We Got and Where Are We Going?

In recent decades, very few new psychiatric drugs have entered the market. Thus, improvement in the use of antidepressant and antipsychotic therapy has to focus mainly on enhanced and more personalized treatment with the currently available drugs. One important aspect of such individualization is emphasizing interindividual differences in genes relevant to treatment, an area that can be termed neuropsychopharmacogenomics. Here, we review previous efforts to identify such critical genetic variants and summarize the results obtained to date. We conclude that most clinically relevant genetic variation is connected to phase I drug metabolism, in particular to genetic polymorphism of CYP2C19 and CYP2D6. To further improve individualized pharmacotherapy, there is a need to take both common and rare relevant mutations into consideration; we discuss the present and future possibilities of using whole genome sequencing to identify patient-specific genetic variation relevant to treatment in psychiatry. Translation of pharmacogenomic knowledge into clinical practice can be considered for specific drugs, but this requires education of clinicians, instructive guidelines, as well as full attention to polypharmacy and other clinically relevant factors. Recent large patient studies (n > 1,000) have replicated previous findings and produced robust evidence warranting the clinical utility of relevant genetic biomarkers. To further judge the clinical and financial benefits of preemptive genotyping in psychiatry, large prospective randomized trials are needed to quantify the value of genetic-based patient stratification in neuropsychopharmacotherapy and to demonstrate the cost-effectiveness of such interventions.

Evaluation of Current Regulation and Guidelines of Pharmacogenomic Drug Labels: Opportunities for Improvements

Pharmacogenomic drug labels in the Summary of Product Characteristics (SmPC) provide an instrument for clinical implementation of pharmacogenomics. We compared pharmacogenomic guidance by Clinical Pharmacogenetics Implementation Consortium (CPIC), Dutch Pharmacogenetics Working Group (DPWG), the US Food and Drug Administration (FDA), and by the European agencies the European Medicines Agency (EMA), College ter Beoordeling van Geneesmiddelen Medicines Evaluation Board (CBG-MEB), and Federal Institute for Drugs and Medical Devices (FIDMD), collectively assigned as EMA/FIDMD+MEB shortened as EMA/FM. Of 54 drugs with an actionable gene-drug interaction in the CPIC and DPWG guidelines, only 50% had actionable pharmacogenomic information in the SmPCs and the agencies were in agreement in only 18% of the cases. We further compared 450 additional drugs, lacking CPIC or DPWG guidance, and found 126 actionable gene-drug labels by the FDA and/or the EMA/FM. Based on these 126 drugs in addition to the 54 above, the consensus of actionable pharmacogenomic labeling between the FDA and the EMA/FM was only 54%. In conclusion, guidelines provided by CPIC/DPWG are only partly implemented into the SmPCs and the implementation of pharmacogenomic drug labels into the clinics would strongly gain from a higher extent of consensus between agencies.

Unveiling the guidance heterogeneity for genome-informed drug treatment interventions among regulatory bodies and research consortia

Pharmacogenomics and personalized medicine interventions hold promise to optimize drug treatment modalities and hence, improve the quality of life of the patients by minimizing the occurrence of adverse drug reactions and/or maximizing drug treatment efficacy. To this end, proper guidance for accurately prescribing the correct drug at the right dose is empowered by major regulatory bodies, namely the U.S. Food and Drug Administration (FDA) and the European Medicine Agency (EMA), and well-recognized research consortia, like the Clinical Pharmacogenetics Implementation Consortium (CPIC), that propose therapeutic recommendations after the thorough evaluation of the existing scientific evidence base. In this context, the consistency of these recommendations is crucial for smoothly integrating pharmacogenomics into the clinic. Here, we collected all of the important and clinically actionable pharmacogenomics information provided by the aforementioned renowned sources and documented it in order to assess potential similarities and, most importantly, differences. Our data show that the level of concordance regarding the guidance provided for the same drug-gene association pairs varies significantly, despite the fact that it all derives from a single evidence base. In particular, apart from the expected similarities in a number of association pairs, especially the ones related to cancer genomics, there are still major discrepancies that create confusion as to which guidance should be followed in order to properly inform drug prescribing. This regulatory deficiency calls for the fruitful engagement of the regulatory agencies involved with the contribution of other experts engaged in the field of pharmacogenomics in an effort to harmonize the existing arsenal of guidance for genome-informed drug prescription. The achievement of harmonization would in turn expedite bringing personalized medicine closer to clinical fruition.

Pharmacogenomic biomarker information differences between drug labels in the United States and Hungary: implementation from medical practitioner view

Pharmacogenomic biomarker availability of Hungarian Summaries of Product Characteristics (SmPC) was assembled and compared with the information in US Food and Drug Administration (FDA) drug labels of the same active substance (July 2019). The level of action of these biomarkers was assessed from The Pharmacogenomics Knowledgebase database. From the identified 264 FDA approved drugs with pharmacogenomic biomarkers in drug label, 195 are available in Hungary. From them, 165 drugs include pharmacogenomic data disposing 222 biomarkers. Most of them are metabolizing enzymes (46%) and pharmacological targets (41%). The most frequent therapeutic area is oncology (37%), followed by infectious diseases (12%) and psychiatry (9%) (p < 0.00001). Most common biomarkers in Hungarian SmPCs are CYP2D6, CYP2C19, estrogen and progesterone hormone receptor (ESR, PGS). Importantly, US labels present more specific pharmacogenomic subheadings, the level of action has a different prominence, and offer more applicable dose modifications than Hungarians (5% vs 3%). However, Hungarian SmPCs are at 9 oncology drugs stricter than FDA, testing is obligatory before treatment. Out of the biomarkers available in US drug labels, 62 are missing completely from Hungarian SmPCs (p < 0.00001). Most of these belong to oncology (42%) and in case of 11% of missing biomarkers testing is required before treatment. In conclusion, more factual, clear, clinically relevant pharmacogenomic information in Hungarian SmPCs would reinforce implementation of pharmacogenetics. Underpinning future perspective is to support regulatory stakeholders to enhance inclusion of pharmacogenomic biomarkers into Hungarian drug labels and consequently enhance personalized medicine in Hungary.

Tadalafil treatment for preeclampsia (medication in preeclampsia; MIE): a multicenter phase II clinical trial

Purpose: To evaluate the effectiveness and safety of tadalafil treatment for hypertensive disorder of pregnancy (HDP).Materials and methods: In an open-label, randomized clinical trial, singleton pregnancies with HDP between 20 and 33 weeks of gestation were randomized to take 20 mg oral tadalafil every day (tadalafil treatment group) or no drug (conventional treatment group). The primary outcome was prolongation of pregnancy from randomization to delivery. However, this article primarily focuses on the safety assessments performed in the tadalafil treatment for HDP population, because the safety of using PDE5 inhibitors as therapeutic agents for fetal growth restriction (FGR) has been a problem worldwide.Results: From October 2016 to March 2018, 28 patients were randomized to each group and two cases were excluded (tadalafil treatment group: 12 cases; conventional treatment group: 14 cases). The significant adverse events related to tadalafil did not occur in the tadalafil treatment group. Among maternal adverse events, specifically with regard to headaches, there were significant differences between the two groups (0% in tadalafil group versus 43% in conventional treatment group; p = .02). There was no difference in the prolongation period of pregnancy that served as primary outcomes in both the groups (17.5 d in tadalafil group versus 16.5 d in conventional group, p = .96). The significant adverse events occurred at the same frequency as between the conventional treatment group and the tadalafil treatment group. And, maternal headache decreased significantly in the tadalafil treatment group.Conclusions: Tadalafil treatment is safe for pregnant women with HDP. Moreover, tadalafil did not prolong the gestational period in pregnant women with HDP.

Effectiveness of a Pharmacogenetic Tool at Improving Treatment Efficacy in Major Depressive Disorder: A Meta-Analysis of Three Clinical Studies

Several pharmacogenetic tests to support drug selection in psychiatric patients have recently become available. The current meta-analysis aimed to assess the clinical utility of a commercial pharmacogenetic-based tool for psychiatry (Neuropharmagen^®) in the treatment management of depressive patients. Random-effects meta-analysis of clinical studies that had examined the effect of this tool on the improvement of depressive patients was performed. Effects were summarized as standardized differences between treatment groups. A total of 450 eligible subjects from three clinical studies were examined. The random effects model estimated a statistically significant effect size for the pharmacogenetic-guided prescription (d = 0.34, 95% CI = 0.11-0.56, p-value = 0.004), which corresponded to approximately a 1.8-fold increase in the odds of clinical response for pharmacogenetic-guided vs. unguided drug selection. After exclusion of patients with mild depression, the pooled estimated effect size increased to 0.42 (95% CI = 0.19-0.65, p-value = 0.004, n = 287), corresponding to an OR = 2.14 (95% CI = 1.40-3.27). These results support the clinical utility of this pharmacogenetic-based tool in the improvement of health outcomes in patients with depression, especially those with moderate-severe depression. Additional pragmatic RCTs are warranted to consolidate these findings in other patient populations.

Identification of a key candidate gene‑phenotype network mediated by glycyrrhizic acid using pharmacogenomic analysis

Glycyrrhizic acid (GA) is primarily used as an anti-inflammatory agent in cases of chronic hepatitis. However, its underlying mechanisms in diverse biological processes and its reported benefits are yet to be fully elucidated. In the current study, an analytical method based on pharmacogenomics was established to mine disease-modulatory activities mediated by GA. Five primary protein targets and 138 functional partners were identified for GA by querying open-source databases, including Drugbank and STRING. Subsequently, GA-associated primary and secondary protein targets were integrated into Cytoscape to construct a protein-protein interaction network to establish connectivity. GA-associated target genes were then clustered based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. The tumor necrosis factor axis was revealed to be a primary module regulated by GA-associated targets. Furthermore, 12 hub genes were queried to assess their potential anti-cancer effects using cBioPortal. The results indicated that pharmacogenomics-based analysis improved understanding of the underlying drug-target events of GA and provided predictive and definitive leads for future studies.

Targeted next generation sequencing as a tool for precision medicine

BACKGROUND

Targeted next-generation sequencing (NGS) enables rapid identification of common and rare genetic variation. The detection of variants contributing to therapeutic drug response or adverse effects is essential for implementation of individualized pharmacotherapy. Successful application of short-read based NGS to pharmacogenes with high sequence homology, nearby pseudogenes and complex structure has been previously shown despite anticipated technical challenges. However, little is known regarding the utility of such panels to detect copy number variation (CNV) in the highly polymorphic cytochrome P450 (CYP) 2D6 gene, or to identify the promoter (TA)₇ TAA repeat polymorphism UDP glucuronosyltransferase (UGT) 1A1*28. Here we developed and validated PGxSeq, a targeted exome panel for pharmacogenes pertinent to drug disposition and/or response.

METHODS

A panel of capture probes was generated to assess 422 kb of total coding region in 100 pharmacogenes. NGS was carried out in 235 subjects, and sequencing performance and accuracy of variant discovery validated in clinically relevant pharmacogenes. CYP2D6 CNV was determined using the bioinformatics tool CNV caller (VarSeq). Identified SNVs were assessed in terms of population allele frequency and predicted functional effects through in silico algorithms.

RESULTS

Adequate performance of the PGxSeq panel was demonstrated with a depth-of-coverage (DOC) ≥ 20× for at least 94% of the target sequence. We showed accurate detection of 39 clinically relevant gene variants compared to standard genotyping techniques (99.9% concordance), including CYP2D6 CNV and UGT1A1*28. Allele frequency of rare or novel variants and predicted function in 235 subjects mirrored findings from large genomic datasets. A large proportion of patients (78%, 183 out of 235) were identified as homozygous carriers of at least one variant necessitating altered pharmacotherapy.

CONCLUSIONS

PGxSeq can serve as a comprehensive, rapid, and reliable approach for the detection of common and novel SNVs in pharmacogenes benefiting the emerging field of precision medicine.

Regulatory sciences and translational pharmacogenetics: amitriptyline as a case in point

Regulatory developments and clinical implementation, or the lack thereof, are primary clinchers, in the enduring endeavors to realize the translational quality of pharmacogenetics. Here, we present the case of amitriptyline, an established drug with pharmacogenetic implications. The integration of pharmacogenetic information in the official product literature and throughout the evaluation of safety concerns is considered. In our opinion, apart from emboldening genomic research in drug development and the valid pursuit towards global harmonization in the field, it is rational to look into the applicability of the data we have today.

Novel genetic and epigenetic factors of importance for inter-individual differences in drug disposition, response and toxicity

Individuals differ substantially in their response to pharmacological treatment. Personalized medicine aspires to embrace these inter-individual differences and customize therapy by taking a wealth of patient-specific data into account. Pharmacogenomic constitutes a cornerstone of personalized medicine that provides therapeutic guidance based on the genomic profile of a given patient. Pharmacogenomics already has applications in the clinics, particularly in oncology, whereas future development in this area is needed in order to establish pharmacogenomic biomarkers as useful clinical tools. In this review we present an updated overview of current and emerging pharmacogenomic biomarkers in different therapeutic areas and critically discuss their potential to transform clinical care. Furthermore, we discuss opportunities of technological, methodological and institutional advances to improve biomarker discovery. We also summarize recent progress in our understanding of epigenetic effects on drug disposition and response, including a discussion of the only few pharmacogenomic biomarkers implemented into routine care. We anticipate, in part due to exciting rapid developments in Next Generation Sequencing technologies, machine learning methods and national biobanks, that the field will make great advances in the upcoming years towards unlocking the full potential of genomic data.

Integrating Next-Generation Sequencing in the Clinical Pharmacogenomics Workflow

Pharmacogenomics has been recognized as a fundamental tool in the era of personalized medicine with up to 266 drug labels, approved by major regulatory bodies, currently containing pharmacogenomics information. Next-generation sequencing analysis assumes a critical role in personalized medicine, providing a comprehensive profile of an individual's variome, particularly that of clinical relevance, comprising of pathogenic variants and pharmacogenomic biomarkers. Here, we propose a strategy to integrate next-generation sequencing into the current clinical pharmacogenomics workflow from deep resequencing to pharmacogenomics consultation, according to the existing guidelines and recommendations.

Translating Pharmacogenetics and Pharmacogenomics to the Clinic: Progress in Human and Veterinary Medicine

As targeted personalized therapy becomes more widely used in human medicine, clients will expect the veterinary clinician to be able to implement an evidence-based strategy regarding both the prescribing of medicines and also recognition of the potential for adverse drug reactions (ADR) for their pet, at breed and individual level. This review aims to provide an overview of current developments and challenges in pharmacogenetics in medicine for a veterinary audience and to map these to developments in veterinary pharmacogenetics. Pharmacogenetics has been in development over the past 100 years but has been revolutionized following the publication of the human, and then veterinary species genomes. Genetic biomarkers called pharmacogenes have been identified as specific genetic loci on chromosomes which are associated with either positive or adverse drug responses. Pharmacogene variation may be classified according to the associated drug response, such as a change in (1) the pharmacokinetics; (2) the pharmacodynamics; (3) genes in the downstream pathway of the drug or (4) the effect of “off-target” genes resulting in a response that is unrelated to the intended target. There are many barriers to translation of pharmacogenetic information to the clinic, however, in human medicine, international initiatives are promising real change in the delivery of personalized medicine by 2025. We argue that for effective translation into the veterinary clinic, clinicians, international experts, and stakeholders must collaborate to ensure quality assurance and genetic test validation so that animals may also benefit from this genomics revolution.