Pharmacogenomics in early-phase clinical development

Implementing pharmacogenetics in clinical trials: considerations about current methodological, ethical, and regulatory challenges

INTRODUCTION

The implementation of pharmacogenetic analysis within clinical trials faces methodological, ethical, and regulatory challenges, as well as tackling the difficulty in obtaining actionable information with a sufficient level of evidence to enable its integration into routine clinical practice.

AREAS COVERED

We discuss the current status of pharmacogenetics integration in clinical trials, underscore the associated challenges, and make some suggestions on the aspects to address in any clinical trial including a pharmacogenetic evaluation. We conducted a literature review, thoroughly reviewed the applicable regulations and available guidelines, and assessed the application dossiers submitted for evaluation to the Ethics committee of Hospital La Paz (Madrid, Spain) to extract information related to inclusion of pharmacogenetics evaluations.

EXPERT OPINION

The integration of pharmacogenetics into clinical trials is becoming increasingly common. However, several regulatory, methodological and ethical aspects involved are insufficiently addressed. There is a need for specific and transparent guidelines that establish unified and compliant criteria for methodology, proper handling of samples in compliance with regulations, and the protection of data privacy and confidentiality. Participants should receive complete and appropriate information regarding the purpose, handling, storage, and transfer of their samples and data, and should have the right to decide about their processing.

Pharmacogenomics in clinical trials: an overview

With the trend towards promoting personalised medicine (PM), the application of pharmacogenetics and pharmacogenomics (PGx) is of growing importance. For the purposes of clinical trials, the inclusion of PGx is an additional tool that should be considered for improving our knowledge about the effectiveness and safety of new drugs. A search of available clinical trials containing pharmacogenetic and PGx information was conducted on ClinicalTrials.gov. The results show there has been an increase in the number of trials containing PGx information since the 2000 s, with particular relevance in the areas of Oncology (28.43%) and Mental Health (10.66%). Most of the clinical trials focus on treatment as their primary purpose. In those clinical trials entries where the specific genes considered for study are detailed, the most frequently explored genes are CYP2D6 (especially in Mental Health and Pain), CYP2C9 (in Hematology), CYP2C19 (in Cardiology and Mental Health) and ABCB1 and CYP3A5 (particularly prominent in Transplantation and Cardiology), among others. Researchers and clinicans should be trained in pharmacogenetics and PGx in order to be able to make a proper interpretation of this data, contributing to better prescribing decisions and an improvement in patients' care, which would lead to the performance of PM.

In-silico mining to glean SNPs of pharmaco-clinical importance: an investigation with reference to the Indian populated SNPs

Drugs pharmacology is defined by pharmacokinetics and pharmacodynamics and both of them are affected by genetic variability. Genetic variability varies from population to population, and sometimes even within the population, it exists. Single nucleotide polymorphisms (SNPs) are one of the major genetic variability factors which are found to be associated with the pharmacokinetics and pharmacodynamics process of a drug and are responsible for variable drug response and clinical phenotypes. Studies of SNPs can help to perform genome-wide association studies for their association with pharmacological and clinical events, at the same time; their information can direct genome-wide association studies for their use as biomarkers. With the aim to mine and characterize Indian populated SNPs of pharmacological and clinical importance. Two hundred six candidate SNPs belonging to 43 genes were retrieved from Indian Genome Variation Database. The distribution pattern of considered SNPs was observed against all five world super-populations (AFR, AMR, EAS, EUR, and SAS). Further, their annotation was done through SNP-nexus by considering Human genome reference builds - hg38, pharmacological and clinical information was supplemented by PharmGKB and ClinVar database. At last, to find out the association between SNPs linkage disequilibrium was observed in terms of r2. Overall, the study reported 53 pharmaco-clinical active SNPs and found 24 SNP-pairs as potential markers, and recommended their clinical and experimental validation.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00154-4.

Pharmacometabolomics-Based Translational Biomarkers: How to Navigate the Data Ocean

Metabolome is the end point of the genome-environment interplay, and enables an important holistic overview of individual adaptability and host responses to environmental, ecological, as well as endogenous changes such as disease. Pharmacometabolomics is the application of metabolome knowledge to decipher the mechanisms of interindividual and intraindividual variations in drug efficacy and safety. Pharmacometabolomics also contributes to prediction of drug treatment outcomes on the basis of baseline (predose) and postdose metabotypes through mathematical modeling. Thus, pharmacometabolomics is a strong asset for a diverse community of stakeholders interested in theory and practice of evidence-based and precision/personalized medicine: academic researchers, public health scholars, health professionals, pharmaceutical, diagnostics, and biotechnology industries, among others. In this expert review, we discuss pharmacometabolomics in four contexts: (1) an interdisciplinary omics tool and field to map the mechanisms and scale of interindividual variability in drug effects, (2) discovery and development of translational biomarkers, (3) advance digital biomarkers, and (4) empower drug repurposing, a field that is increasingly proving useful in the current era of Covid-19. As the applications of pharmacometabolomics are growing rapidly in the current postgenome era, next-generation proteomics and metabolomics follow the example of next-generation sequencing analyses. Pharmacometabolomics can also empower data reliability and reproducibility through multiomics integration strategies, which use each data layer to correct, connect with, and inform each other. Finally, we underscore here that contextual data remain crucial for precision medicine and drug development that stand the test of time and clinical relevance.

Mendelian randomization in pharmacogenomics: The unforeseen potentials

Mendelian randomization (MR) is an epidemiological method that uses genetic variants to proxy an exposure predicting its causal association with an outcome. It occupies a valuable niche between observational studies and randomized trials. MR applications expanded lately, facilitated by the availability of big data, to include disease risk causation prediction, supporting evidence of prior observational data, identifying new drug targets, and drug repurposing. Concurrently, the last decade witnessed the growth of pharmacogenomics (PGx) research as a cornerstone in precision medicine. PGx research, conducted at discovery and implementation levels, resulted in validated PGx biomarkers and tests. Despite many clinically relevant PGx associations that could be translated into clinical applications, worldwide implementation is lagging far behind. The current review examines the intersection zones between MR and PGx research. MR can provide supporting evidence that allows generalizing PGx findings supporting its implementation. Interchangeability, PGx research can fuel MR studies with libraries of genetic variants of validated biological relevance. Furthermore, PGx and MR exhibit a synergistic relationship in drug discovery that can accelerate identifying new targets and repurposing old drugs. Interdisciplinary research applied by PGx researchers, epidemiologists with MR experience, and data scientists' collaborations can unlock unforeseen opportunities in accelerating precision medicine acquisition.

PharmGKB, an Integrated Resource of Pharmacogenomic Knowledge

The Pharmacogenomics Knowledgebase (PharmGKB) is an integrated online knowledge resource for the understanding of how genetic variation contributes to variation in drug response. Our focus includes not only pharmacogenomic information useful for clinical implementation (e.g., drug dosing guidelines and annotated drug labels), but also information to catalyze scientific research and drug discovery (e.g., variant-drug annotations and drug-centered pathways). As of April 2021, the annotated content of PharmGKB spans 715 drugs, 1761 genes, 227 diseases, 165 clinical guidelines, and 784 drug labels. We have manually curated data from more than 9000 published papers to generate the content of PharmGKB. Recently, we have also implemented an automated natural language processing (NLP) tool to broaden our coverage of the pharmacogenomic literature. This article contains a basic protocol describing how to navigate the PharmGKB website to retrieve information on how genes and genetic variations affect drug efficacy and toxicity. It also includes a protocol on how to use PharmGKB to facilitate interpretation of findings for a pharmacogenomic variant genotype or metabolizer phenotype. PharmGKB is freely available at http://www.pharmgkb.org. © 2021 Wiley Periodicals LLC. Basic Protocol 1: Navigating the homepage of PharmGKB and searching by drug Basic Protocol 2: Using PharmGKB to facilitate interpretation of pharmacogenomic variant genotypes or metabolizer phenotypes.

Genome-based therapeutic interventions for β-type hemoglobinopathies

For decades, various strategies have been proposed to solve the enigma of hemoglobinopathies, especially severe cases. However, most of them seem to be lagging in terms of effectiveness and safety. So far, the most prevalent and promising treatment options for patients with β-types hemoglobinopathies, among others, predominantly include drug treatment and gene therapy. Despite the significant improvements of such interventions to the patient's quality of life, a variable response has been demonstrated among different groups of patients and populations. This is essentially due to the complexity of the disease and other genetic factors. In recent years, a more in-depth understanding of the molecular basis of the β-type hemoglobinopathies has led to significant upgrades to the current technologies, as well as the addition of new ones attempting to elucidate these barriers. Therefore, the purpose of this article is to shed light on pharmacogenomics, gene addition, and genome editing technologies, and consequently, their potential use as direct and indirect genome-based interventions, in different strategies, referring to drug and gene therapy. Furthermore, all the latest progress, updates, and scientific achievements for patients with β-type hemoglobinopathies will be described in detail.

Pharmacogenomics in the era of next generation sequencing - from byte to bedside

Pharmacogenetic research has resulted in the identification of a multitude of genetic variants that impact drug response or toxicity. These polymorphisms are mostly common and have been included as actionable information in the labels of numerous drugs. In addition to common variants, recent advances in Next Generation Sequencing (NGS) technologies have resulted in the identification of a plethora of rare and population-specific pharmacogenetic variations with unclear functional consequences that are not accessible by conventional forward genetics strategies. In this review, we discuss how comprehensive sequencing information can be translated into personalized pharmacogenomic advice in the age of NGS. Specifically, we provide an update of the functional impacts of rare pharmacogenetic variability and how this information can be leveraged to improve pharmacogenetic guidance. Furthermore, we critically discuss the current status of implementation of pharmacogenetic testing across drug development and layers of care. We identify major gaps and provide perspectives on how these can be minimized to optimize the utilization of NGS data for personalized clinical decision-support.

Attitudes of healthy volunteers to genetic testing in phase 1 clinical trials

Background: Genetic testing in clinical trials introduces several ethical and logistical issues to discuss with potential participants when taking informed consent. The aim of this study was to explore the attitudes of healthy volunteers in phase 1 studies to the topics of genetic security, genetic privacy and incidental genetic findings.

Methods: Healthy volunteers presenting for screening appointments at a phase 1 clinical trial unit (CMAX Clinical Research, Adelaide, Australia) took an anonymous paper survey about genetic testing.

Results: There were 275 respondents to the survey. The mean age was 27 years (range 18-73); 54% were male and 53% were of North/Western European ethnicity. Just over half the healthy volunteers thought genetic security (56%) and genetic privacy (57%) were “important” or “very important”. However, the security of their genetic information was ranked less important than other personal information, including mobile phone number, internet browser search history and email address. Two-thirds of respondents would trade genetic privacy for re-identifiability if information relevant to their health were discovered by genetic testing. Healthy volunteers favoured the return of incidental genetic findings (90% indicated this was “important” or “very important”). A level of risk (10 to 90%) for developing a serious medical condition that would “trigger” the return of incidental genetic findings to participants was not identified.

Conclusions: Healthy volunteers screening for phase 1 clinical trials have mixed views about the importance of genetic security and genetic privacy, but they strongly favour the return of incidental genetic findings that could affect their health. These issues should be discussed with potential participants during informed consent for phase 1 clinical trials with genetic testing.

Pharmacogenomic Biomarkers in US FDA-Approved Drug Labels (2000-2020)

Pharmacogenomics (PGx) is a key subset of precision medicine that relates genomic variation to individual response to pharmacotherapy. We assessed longitudinal trends in US FDA approval of new drugs labeled with PGx information. Drug labels containing PGx information were obtained from Drugs@FDA and guidelines from PharmGKB were used to compare the actionability of PGx information in drug labels across therapeutic areas. The annual proportion of new drug approvals with PGx labeling has increased by nearly threefold from 10.3% (n = 3) in 2000 to 28.2% (n = 11) in 2020. Inclusion of PGx information in drug labels has increased for all clinical areas over the last two decades but most prominently for cancer therapies, which comprise the largest proportion (75.5%) of biomarker–drug pairs for which PGx testing is required. Clinically actionable information was more frequently observed in biomarker–drug pairs associated with cancer drugs compared to those for other therapeutic areas (n = 92 (59.7%) vs. n = 62 (40.3%), p < 0.0051). These results suggest that further evidence is needed to support the clinical adoption of pharmacogenomics in non-cancer therapeutic areas.

COVID19 Drug Repository: text-mining the literature in search of putative COVID19 therapeutics

The recent outbreak of COVID-19 has generated an enormous amount of Big Data. To date, the COVID-19 Open Research Dataset (CORD-19), lists ∼130,000 articles from the WHO COVID-19 database, PubMed Central, medRxiv, and bioRxiv, as collected by Semantic Scholar. According to LitCovid (11 August 2020), ∼40,300 COVID19-related articles are currently listed in PubMed. It has been shown in clinical settings that the analysis of past research results and the mining of available data can provide novel opportunities for the successful application of currently approved therapeutics and their combinations for the treatment of conditions caused by a novel SARS-CoV-2 infection. As such, effective responses to the pandemic require the development of efficient applications, methods and algorithms for data navigation, text-mining, clustering, classification, analysis, and reasoning. Thus, our COVID19 Drug Repository represents a modular platform for drug data navigation and analysis, with an emphasis on COVID-19-related information currently being reported. The COVID19 Drug Repository enables users to focus on different levels of complexity, starting from general information about (FDA-) approved drugs, PubMed references, clinical trials, recipes as well as the descriptions of molecular mechanisms of drugs' action. Our COVID19 drug repository provide a most updated world-wide collection of drugs that has been repurposed for COVID19 treatments around the world.

Metabolomics in Radiation Biodosimetry: Current Approaches and Advances

Triage and medical intervention strategies for unanticipated exposure during a radiation incident benefit from the early, rapid and accurate assessment of dose level. Radiation exposure results in complex and persistent molecular and cellular responses that ultimately alter the levels of many biological markers, including the metabolomic phenotype. Metabolomics is an emerging field that promises the determination of radiation exposure by the qualitative and quantitative measurements of small molecules in a biological sample. This review highlights the current role of metabolomics in assessing radiation injury, as well as considerations for the diverse range of bioanalytical and sampling technologies that are being used to detect these changes. The authors also address the influence of the physiological status of an individual, the animal models studied, the technology and analysis employed in interrogating response to the radiation insult, and variables that factor into discovery and development of robust biomarker signatures. Furthermore, available databases for these studies have been reviewed, and existing regulatory guidance for metabolomics are discussed, with the ultimate goal of providing both context for this area of radiation research and the consideration of pathways for continued development.

Factors Influencing Participation in Biospecimen Research among Parents of Youth with Mental Health Conditions

INTRODUCTION

Biospecimens are tools that have the potential to improve early identification and treatment for autism spectrum disorders (ASD) and bipolar disorders (BPD). Unfortunately, most biobanks lack racial/ethnic diversity. One challenge to including a diverse sample of youth is recruiting and engaging families.

OBJECTIVE

We sought to better understand facilitators and barriers to participation in biospecimen research among a diverse group of parents of youth with ASD and BPD.

METHODS

The current study involved 3 Mental Health Research Network sites. At each site, parents participated in an interview that explored attitudes and beliefs about genetic research. Interviews were audio-recorded, and audio files were transcribed and coded using content analysis.

RESULTS

A total of 58 interviews were conducted. Four challenges emerged: (1) contacting and engaging potential research participants, (2) motivating potential participants to read recruitment and consent materials, (3) motivating participation in research, in general, and (4) motivating participation in research involving biospecimen donation, specifically.

CONCLUSIONS

Participants were eager to participate as long as the research process involved trust, clarity, and flexibility. Future research involving youth with mental health conditions would benefit from implementing multimodal strategies for recruitment and data collection and sharing knowledge gained by the research with study participants.

Precision Dosing Priority Criteria: Drug, Disease, and Patient Population Variables

The administered dose of a drug modulates whether patients will experience optimal effectiveness, toxicity including death, or no effect at all. Dosing is particularly important for diseases and/or drugs where the drug can decrease severe morbidity or prolong life. Likewise, dosing is important where the drug can cause death or severe morbidity. Since we believe there are many examples where more precise dosing could benefit patients, it is worthwhile to consider how to prioritize drug–disease targets. One key consideration is the quality of information available from which more precise dosing recommendations can be constructed. When a new more precise dosing scheme is created and differs significantly from the approved label, it is important to consider the level of proof necessary to either change the label and/or change clinical practice. The cost and effort needed to provide this proof should also be considered in prioritizing drug–disease precision dosing targets. Although precision dosing is being promoted and has great promise, it is underutilized in many drugs and disease states. Therefore, we believe it is important to consider how more precise dosing is going to be delivered to high priority patients in a timely manner. If better dosing schemes do not change clinical practice resulting in better patient outcomes, then what is the use? This review paper discusses variables to consider when prioritizing precision dosing candidates while highlighting key examples of precision dosing that have been successfully used to improve patient care.

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

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

Current Concepts in Pharmacometabolomics, Biomarker Discovery, and Precision Medicine

Pharmacometabolomics (PMx) studies use information contained in metabolic profiles (or metabolome) to inform about how a subject will respond to drug treatment. Genome, gut microbiome, sex, nutrition, age, stress, health status, and other factors can impact the metabolic profile of an individual. Some of these factors are known to influence the individual response to pharmaceutical compounds. An individual’s metabolic profile has been referred to as his or her “metabotype.” As such, metabolomic profiles obtained prior to, during, or after drug treatment could provide insights about drug mechanism of action and variation of response to treatment. Furthermore, there are several types of PMx studies that are used to discover and inform patterns associated with varied drug responses (i.e., responders vs. non-responders; slow or fast metabolizers). The PMx efforts could simultaneously provide information related to an individual’s pharmacokinetic response during clinical trials and be used to predict patient response to drugs making pharmacometabolomic clinical research valuable for precision medicine. PMx biomarkers can also be discovered and validated during FDA clinical trials. Using biomarkers during medical development is described in US Law under the 21st Century Cures Act. Information on how to submit biomarkers to the FDA and their context of use is defined herein.

Drug-Placebo Additivity in Randomized Clinical Trials

In randomized clinical trials (RCTs), it is assumed that nonspecific effects beyond action of pharmacological agents are roughly equivalent in drug and placebo treatment groups. Hence, since the inception of RCTs, drug efficacy is determined by comparing outcomes in active to those in placebo control arms. However, quantitation of efficacy is based on an unproven assumption, that drug and placebo responses are always additive. Response to treatment in RCTs can be differentially influenced by the perturbing effects of patient expectations, side effects, and pharmacogenomic interactions in both drug and placebo arms. Ability to control for these effects requires understanding of when and where they arise, how to mitigate, analyze, and even leverage their impact. Here, we examine three factors that influence additivity: expectation, side effects, and pharmacogenomics. Furthermore, to provide novel insights into nonadditivity and solutions for managing it, we introduce systems pharmacogenomics, a network approach to integrating and analyzing the effects of the numerous interacting perturbations to which a patient is exposed in RCTs.

Population-scale genomics-Enabling precision public health

The current excitement for affordable genomics technologies and national precision medicine initiatives marks a turning point in worldwide healthcare practices. The last decade of global population sequencing efforts has defined the enormous extent of genetic variation in the human population resulting in insights into differential disease burden and response to therapy within and between populations. Population-scale pharmacogenomics helps to provide insights into the choice of optimal therapies and an opportunity to estimate, predict and minimize adverse events. Such an approach can potentially empower countries to formulate national selection and dosing policies for therapeutic agents thereby promoting public health with precision. We review the breadth and depth of worldwide population-scale sequencing efforts and its implications for the implementation of clinical pharmacogenetics toward making precision medicine a reality.

Influence of Transporter Polymorphisms on Drug Disposition and Response: A Perspective From the International Transporter Consortium

Advances in genomic technologies have led to a wealth of information identifying genetic polymorphisms in membrane transporters, specifically how these polymorphisms affect drug disposition and response. This review describes the current perspective of the International Transporter Consortium (ITC) on clinically important polymorphisms in membrane transporters. ITC suggests that, in addition to previously recommended polymorphisms in ABCG2 (BCRP) and SLCO1B1 (OATP1B1), polymorphisms in the emerging transporter, SLC22A1 (OCT1), be considered during drug development. Collectively, polymorphisms in these transporters are important determinants of interindividual differences in the levels, toxicities, and response to many drugs.

Intra-Target Microdosing - A Novel Drug Development Approach: Proof of Concept, Safety, and Feasibility Study in Humans

Intra‐Target Microdosing (ITM) is a novel drug development approach aimed at increasing the efficiency of first‐in‐human (FIH) testing of new molecular entities (NMEs). ITM combines intra‐target drug delivery and “microdosing,” the subpharmacological systemic exposure. We hypothesized that when the target tissue is small (about 1/100th of total body mass), ITM can lead to target therapeutic‐level exposure with minimal (microdose) systemic exposure. Each of five healthy male volunteers received insulin microdose into the radial artery or full therapeutic dose intravenously in separate visits. Insulin and glucose levels were similar between systemic administration and ITM administration in the ipsilateral hand, and glucose levels demonstrated a reduction in the ipsilateral hand but not in the contralateral hand. Positron emission tomography (PET) imaging of ¹⁸F‐fluorodeoxyglucose (FDG) uptake demonstrated differences between the ipsilateral and contralateral arms. The procedures were safe and well‐tolerated. Results are consistent with ITM proof‐of‐concept (POC) and demonstrate the ethical, regulatory, and logistical feasibility of the approach.

The Burden of the "False-Negatives" in Clinical Development: Analyses of Current and Alternative Scenarios and Corrective Measures

The “false‐negatives” of clinical development are the effective treatments wrongly determined ineffective. Statistical errors leading to “false‐negatives” are larger than those leading to “false‐positives,” especially in typically underpowered early‐phase trials. In addition, “false‐negatives” are usually eliminated from further testing, thereby limiting the information available on them. We simulated the impact of early‐phase power on economic productivity in three developmental scenarios. Scenario 1, representing the current status quo, assumed 50% statistical power at phase II and 90% at phase III. Scenario 2 assumed increased power (80%), and Scenario 3, increased stringency of alpha (1%) at phase II. Scenario 2 led, on average, to a 60.4% increase in productivity and 52.4% increase in profit. Scenario 3 had no meaningful advantages. Our results suggest that additional costs incurred by increasing the power of phase II studies are offset by the increase in productivity. We discuss the implications of our results and propose corrective measures.

Integrating Pharmacoproteomics into Early-Phase Clinical Development: State-of-the-Art, Challenges, and Recommendations

Pharmacoproteomics is the study of disease-modifying and toxicity parameters associated with therapeutic drug administration, using analysis of quantitative and temporal changes to specific, predetermined, and select proteins, or to the proteome as a whole. Pharmacoproteomics is a rapidly evolving field, with progress in analytic technologies enabling processing of complex interactions of large number of unique proteins and effective use in clinical trials. Nevertheless, our analysis of clinicaltrials.gov and PubMed shows that the application of proteomics in early-phase clinical development is minimal and limited to few therapeutic areas, with oncology predominating. We review the history, technologies, current usage, challenges, and potential for future use, and conclude with recommendations for integration of pharmacoproteomic in early-phase drug development.

Pharmacogenetics of cancer therapy: breakthroughs from beyond?

‘Pharmacogenetics or Pharmacogenomics’ (PG) is one of the most practiced cancer therapeutic strategies, tailored for individualized patients. Despite its popularity and rapid advancements in the field, many obstacles for cancer therapy PG still need to be overcome. By borrowing scientific systems from other disciplines such as cancer diagnosis, and therapeutic information from the diversity of tumor origins, categories and stages, cancer therapy PG may hopefully be improved. Furthermore, to quickly acquire genetic and pathologic information and seek therapeutic interventions, possible breakthroughs may come from beyond – changing the cancer therapeutic landscapes. The next generations of PG protocols and hospital routines for searching deadly cancer pathogenic pathways versus drug-targeting predictions are of great clinical significance for the future. Yet, progress of cancer therapy PG is entering into a bottleneck stage owing to simple model of relevant techniques and routines. Promoting or even innovating present PG modular is very necessary. This perspective highlights this issue by introducing new initiatives and ideas.

Pharmacogenomics of antimicrobial agents

Antimicrobial efficacy and toxicity varies between individuals owing to multiple factors. Genetic variants that affect drug-metabolizing enzymes may influence antimicrobial pharmacokinetics and pharmacodynamics, thereby determining efficacy and/or toxicity. In addition, many severe immune-mediated reactions have been associated with HLA class I and class II genes. In the last two decades, understanding of pharmacogenomic factors that influence antimicrobial efficacy and toxicity has rapidly evolved, leading to translational success such as the routine use of HLA-B*57:01 screening to prevent abacavir hypersensitivity reactions. This article examines recent advances in the field of antimicrobial pharmacogenomics that potentially affect treatment efficacy and toxicity, and challenges that exist between pharmacogenomic discovery and translation into clinical use.

An index of barriers for the implementation of personalised medicine and pharmacogenomics in Europe

BACKGROUND

Personalised medicine (PM) is an innovative way to produce better patient outcomes by using an individualised or stratified approach to disease and treatment rather than a collective treatment approach for patients. Despite its tangible advantages, the complex process to translate PM into the member states and European healthcare systems has delayed its uptake. The aim of this study is to identify relevant barriers represented by an index to summarise challenging areas for the implementation of PM in Europe.

METHODS

A systematic literature review was conducted, and a gaps-and-needs assessment together with a strengths-weaknesses-opportunities-and-threats analysis were applied to review strategic reports and conduct interviews with key stakeholders. Furthermore, surveys were sent out to representatives of stakeholder groups. The index was constructed based on the priorisation of relevant factors by stakeholders.

RESULTS

A need for stakeholder-agreed standards at all levels of implementation of PM exists, from validating biomarkers to definitions of 'informed consent'. The barriers to implement PM are identified in 7 areas, namely, stakeholder involvement, standardisation, interoperable infrastructure, European-level policy making, funding, data and research, and healthcare systems.

CONCLUSIONS

Challenges in the above-mentioned areas can and must be successfully tackled if we are to create a healthier Europe through PM. In order to create an environment in which PM can thrive for the patients' best outcomes, there is an urgent need for systematic actions to remove as many barriers as possible.

An update on the pharmacogenetics of treating hypertension

Hypertension is a leading cause of cardiovascular mortality, but only one third of patients achieve blood pressure goals despite antihypertensive therapy. Genetic polymorphisms may partially account for the interindividual variability and abnormal response to antihypertensive drugs. Candidate gene and genome-wide approaches have identified common genetic variants associated with response to antihypertensive drugs. However, there is no currently available pharmacogenetic test to guide hypertension treatment in clinical practice. In this review, we aimed to summarize the recent findings on pharmacogenetics of the most commonly used antihypertensive drugs in clinical practice, including diuretics, angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers, beta-blockers and calcium channel blockers. Notably, only a small percentage of the genetic variability on response to antihypertensive drugs has been explained, and the vast majority of the genetic variants associated with antihypertensives efficacy and toxicity remains to be identified. Despite some genetic variants with evidence of association with the variable response related to these most commonly used antihypertensive drug classes, further replication is needed to confirm these associations in different populations. Further studies on epigenetics and regulatory pathways involved in the responsiveness to antihypertensive drugs might provide a deeper understanding of the physiology of hypertension, which may favor the identification of new targets for hypertension treatment and genetic predictors of antihypertensive response.

Implementation and utilization of genetic testing in personalized medicine

Clinical genetic testing began over 30 years ago with the availability of mutation detection for sickle cell disease diagnosis. Since then, the field has dramatically transformed to include gene sequencing, high-throughput targeted genotyping, prenatal mutation detection, preimplantation genetic diagnosis, population-based carrier screening, and now genome-wide analyses using microarrays and next-generation sequencing. Despite these significant advances in molecular technologies and testing capabilities, clinical genetics laboratories historically have been centered on mutation detection for Mendelian disorders. However, the ongoing identification of deoxyribonucleic acid (DNA) sequence variants associated with common diseases prompted the availability of testing for personal disease risk estimation, and created commercial opportunities for direct-to-consumer genetic testing companies that assay these variants. This germline genetic risk, in conjunction with other clinical, family, and demographic variables, are the key components of the personalized medicine paradigm, which aims to apply personal genomic and other relevant data into a patient’s clinical assessment to more precisely guide medical management. However, genetic testing for disease risk estimation is an ongoing topic of debate, largely due to inconsistencies in the results, concerns over clinical validity and utility, and the variable mode of delivery when returning genetic results to patients in the absence of traditional counseling. A related class of genetic testing with analogous issues of clinical utility and acceptance is pharmacogenetic testing, which interrogates sequence variants implicated in interindividual drug response variability. Although clinical pharmacogenetic testing has not previously been widely adopted, advances in rapid turnaround time genetic testing technology and the recent implementation of preemptive genotyping programs at selected medical centers suggest that personalized medicine through pharmacogenetics is now a reality. This review aims to summarize the current state of implementing genetic testing for personalized medicine, with an emphasis on clinical pharmacogenetic testing.

Promise of pharmacogenomics for drug discovery, treatment and prevention of Parkinson's disease. A perspective

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by a heterogeneous array of motor and non-motor features. Anti-PD drugs that are in use target only the motor symptoms, may lose efficacy over time, and can cause serious adverse effects such as dyskinesia and psychosis. There are currently no preventative or disease modifying treatments. All attempts to develop disease modifying drugs have failed. Pharmacogenomics (PGx) has the potential to change the way new drugs are developed and the way drugs are prescribed. By using genetic markers that correlate with, and can therefore predict drug response, clinical trials can be designed to be enriched with individuals who are most likely to benefit from the drug, maximizing drug's efficacy, minimizing its adverse effects, and boosting the odds of successful drug discovery. Clinical application of PGx will help physicians to quickly and accurately determine the right drugs and the right doses for individuals, avoiding the lengthy trial and error approaches and adverse effects. In combination with known protective factors such as nicotine and caffeine, PGx may enable development of personalized methods for PD prevention and, by extension, care.