Pharmacogenomics at the center of precision medicine: challenges and perspective in an era of Big Data

Precision medicine in pharmacy: assessing pharmacogenomics competence among pharmacists and pharmacy students

Background

Pharmacogenomics, a key component of precision medicine, aims to improve healthcare outcomes. As pharmacists play a pivotal role in this evolving field, an assessment of their preparedness to apply pharmacogenomics is imperative.

Methods

In this cross-sectional study, a validated questionnaire (Content Validity Ratio > 0.741, p < 0.05) that demonstrated reliability (Cronbach's alpha for all scales > 0.7) gathered data on demographics, knowledge, attitudes, barriers, and confidence in pharmacogenomics among pharmacists and pharmacy students in Jordan. Statistical analysis assessed associations and their strength within the collected data and variables.

Results

This study included 514 pharmacists and pharmacy students. Knowledge scores were moderate and correlated with academic level and pharmacy school attended. Most participants were open to providing pharmacogenomics testing and interpretation through pharmacy services, but the majority demonstrated concerns about potential misinterpretation of test results and the resulting patients' anxiety. Students cited limited accessibility, while pharmacists identified the lack of standardised guidelines as the main roadblock.

Conclusion

This study highlights the need for education to prepare pharmacists for their role in pharmacogenomics. Despite positive attitudes from pharmacists, addressing knowledge gaps, the low confidence in recommending pharmacogenomics tests, and concerns about implementation are essential.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

Pharmacogenomics - a minor rather than major force in clinical medicine

INTRODUCTION

Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making.

AREAS COVERED

Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides.

EXPERT OPINION

Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.

Antihypertensives associated adverse events: a review of mechanisms and pharmacogenomic biomarkers available evidence in multi-ethnic populations

Hypertension remains a significant health burden worldwide, re-emphasizing the outstanding need for more effective and safer antihypertensive therapeutic approaches. Genetic variation contributes significantly to interindividual variability in treatment response and adverse events, suggesting pharmacogenomics as a major approach to optimize such therapy. This review examines the molecular mechanisms underlying antihypertensives-associated adverse events and surveys existing research on pharmacogenomic biomarkers associated with these events. The current literature revealed limited conclusive evidence supporting the use of genetic variants as reliable indicators of antihypertensive adverse events. However, several noteworthy associations have emerged, such as 1) the role of ACE variants in increasing the risk of multiple adverse events, 2) the bradykinin pathway's involvement in cough induced by ACE inhibitors, and 3) the impact of CYP2D6 variants on metoprolol-induced bradycardia. Nonetheless, challenges persist in identifying biomarkers for adverse events across different antihypertensive classes, sometimes due to the rarity of certain events, such as ACE inhibitors-induced angioedema. We also highlight the main limitations of previous studies that warrant attention, including using a targeted gene approach with a limited number of tested variants, small sample sizes, and design issues such as overlooking doses or the time between starting treatment and the onset of adverse events. Addressing these challenges requires collaborative efforts and the integration of technological advancements, such as next-generation sequencing, which can significantly enhance research outcomes and provide the needed evidence. Furthermore, the potential combination of genomic biomarker identification and machine learning is a promising approach for tailoring antihypertensive therapy to individual patients, thereby mitigating the risk of developing adverse events. In conclusion, a deeper understanding of the mechanisms and the pharmacogenomics of adverse events in antihypertensive therapy will likely pave the way for more personalized treatment strategies to improve patient outcomes.

Population Pharmacogenomics in Croatia: Evaluating the PGx Allele Frequency and the Impact of Treatment Efficiency

BACKGROUND

Adverse drug reactions (ADRs) are a significant cause of mortality, and pharmacogenomics (PGx) offers the potential to optimize therapeutic efficacy while minimizing ADRs. However, there is a lack of data on the Croatian population, highlighting the need for investigating the most common alleles, genotypes, and phenotypes to establish national guidelines for drug use.

METHODS

A single-center retrospective cross-sectional study was performed to examine the allele, genotype, and phenotype frequencies of drug-metabolizing enzymes, receptors, and other proteins in a random sample of 522 patients from Croatia using a 28-gene PGx panel.

RESULTS

Allele frequencies, genotypes, and phenotypes for the investigated genes were determined. No statistically significant differences were found between the Croatian and European populations for most analyzed genes. The most common genotypes observed in the patients resulted in normal metabolism rates. However, some genes showed higher frequencies of altered metabolism rates.

CONCLUSIONS

This study provides insights into the allele, genotype, and phenotype frequencies of drug-metabolizing enzymes, receptors, and other associated proteins in the Croatian population. The findings contribute to optimizing drug use guidelines, potentially reducing ADRs, and improving therapeutic efficacy. Further research is needed to tailor population-specific interventions based on these findings and their long-term benefits.

The impact of genomic variants on patient response to inhaled bronchodilators: a comprehensive update

INTRODUCTION

The bronchodilator response (BDR) depends on many factors, including genetic ones. Numerous single nucleotide polymorphisms (SNPs) influencing BDR have been identified. However, despite several studies in this field, genetic variations are not currently being utilized to support the use of bronchodilators.

AREAS COVERED

In this narrative review, the possible impact of genetic variants on BDR is discussed.

EXPERT OPINION

Pharmacogenetic studies of β₂-agonists have mainly focused on ADRB2 gene. Three SNPs, A46G, C79G, and C491T, have functional significance. However, other uncommon variants may contribute to individual variability in salbutamol response. SNPs haplotypes in ADRB2 may have a role. Many variants in genes coding for muscarinic ACh receptor (mAChR) have been reported, particularly in the M₂ and, to a lesser degree, M₃ mAChRs, but no consistent evidence for a pharmacological relevance of these SNPs has been reported. Moreover, there is a link between SNPs and ethnic and/or age profiles regarding BDR. Nevertheless, replication of pharmacogenetic results is limited and often, BDR is dissociated from what is expected based on SNP identification. Pharmacogenetic studies on bronchodilators must continue. However, they must integrate data derived from a multi-omics approach with epigenetic factors that may modify BDR.

A personalized pharmaco-epistatic network model of precision medicine

Precision medicine, the utilization of targeted treatments to address an individual's disease, relies on knowledge about the genetic cause of that individual's drug response. Here, we present a functional graph (FunGraph) theory to chart comprehensive pharmacogenetic architecture for each and every patient. FunGraph is the combination of functional mapping - a dynamic model for genetic mapping and evolutionary game theory guiding interactive strategies. It coalesces all pharmacogenetic factors into multilayer and multiplex networks that fully capture bidirectional, signed and weighted epistasis. It can visualize and interrogate how epistasis moves in the cell and how this movement leads to patient- and context-specific genetic architecture in response to organismic physiology. We discuss the future implementation of FunGraph to achieve precision medicine. Teaser: We present a functional graph (FunGraph) theory to draw a complete picture of pharmacogenetic architecture underlying interindividual variability in drug response. FunGraph can characterize how each gene acts and interacts with every other gene to mediate therapeutic response.

An Integrated Multidisciplinary Circuit Led by Hospital and Community Pharmacists to Implement Clopidogrel Pharmacogenetics in Clinical Practice

The use of pharmacogenetics to optimize pharmacotherapy is growing rapidly. This study evaluates the feasibility and operability of a collaborative circuit involving hospital and community pharmacists to implement clopidogrel pharmacogenetics in Barcelona, Catalonia, Spain. We aimed to enroll patients with a clopidogrel prescription from cardiologists at the collaborating hospital. Community pharmacists collected patients' pharmacotherapeutic profiles and saliva samples, which were then sent to the hospital for CYP2C19 genotyping. Hospital pharmacists collated the obtained data with patients' clinical records. Data were analyzed jointly with a cardiologist to assess the suitability of clopidogrel. The provincial pharmacists' association coordinated the project and provided IT and logistic support. The study began in January 2020. However, it was suspended in March 2020 due to the COVID-19 pandemic. At that moment, 120 patients had been assessed, 16 of whom met the inclusion criteria and were enrolled in the study. The processing of samples obtained before the pandemic had an average delay of 13.8 ± 5.4 days. A total of 37.5% patients were intermediate metabolizers and 18.8% were ultrarapid metabolizers. No poor metabolizers were detected. Pharmacists rated their experience with a 7.3 ± 2.7 likelihood of recommending that fellow pharmacists participate. The net promoter score among participating pharmacists was +10%. Our results show that the circuit is feasible and operable for further initiatives.

Pharmacogenomics implementation in cardiovascular disease in a highly diverse population: initial findings and lessons learned from a pilot study in United Arab Emirates

Background

Pharmacogenomic (PGx) testing has proved its utility and cost-effectiveness for some commonly prescribed cardiovascular disease (CVD) medications. In addition, PGx-guided dosing guidelines are now available for multiple CVD drugs, including clopidogrel, warfarin, and statins. The United Arab Emirates (UAE) population is diverse and multiethnic, with over 150 nationalities residing in the country. PGx-testing is not part of the standard of care in most global healthcare settings, including the UAE healthcare system. The first pharmacogenomic implementation clinical study in CVD has been approved recently, but multiple considerations needed evaluation before commencing. The current report appraises the PGx-clinical implementation procedure and the potential benefits of pursuing PGx-implementation initiatives in the UAE with global implications.

Methods

Patients prescribed one or more of the following drugs: clopidogrel, atorvastatin, rosuvastatin, and warfarin, were recruited. Genotyping selected genetic variants at genes interacting with the study drugs was performed by real-time PCR.

Results

For the current pilot study, 160 patients were recruited. The genotypes and inferred haplotypes, diplotypes, and predicted phenotypes revealed that 11.9% of the participants were poor CYP2C19 metabolizers, 35% intermediate metabolizers, 28.1% normal metabolizers, and 25% rapid or ultrarapid metabolizers. Notably, 46.9% of our cohort should receive a recommendation to avoid using clopidogrel or consider an alternative medication. Regarding warfarin, only 20% of the participants exhibited reference alleles at VKORC1-1639G > A, CYP2C9*2, and CYP2C9*3, leaving 80% with alternative genotypes at any of the two genes that can be integrated into the warfarin dosing algorithms and can be used whenever the patient receives a warfarin prescription. For statins, 31.5% of patients carried at least one allele at the genotyped SLCO1B1 variant (rs4149056), increasing their risk of developing myopathy. 96% of our cohort received at least one PGx-generated clinical recommendation for the studied drugs.

Conclusion

The current pilot analysis verified the feasibility of PGx-testing and the unforeseen high frequencies of patients currently treated with suboptimal drug regimens, which may potentially benefit from PGx testing.

Cathelicidins and defensins antimicrobial host defense peptides in the treatment of TB and HIV: Pharmacogenomic and nanomedicine approaches towards improved therapeutic outcomes

Tuberculosis (TB) and human immunodeficiency virus (HIV) represent a significant burden of disease on a global scale. Despite improvements in the global epidemic status, largely facilitated by increased access to pharmacotherapeutic interventions, slow progress in the development of new clinical interventions coupled with growing antimicrobial resistance to existing therapies represents a global health crisis. There is an urgent need to expand the armamentarium of TB and HIV therapeutic strategies. Host mediated immune responses represent an untapped reservoir of novel approaches for TB and HIV. Antimicrobial peptides (AMPs) are an essential aspect of the immune system. Cathelicidins and defensins AMPs have been studied for their potential applications in TB and HIV therapeutic interventions. Genetic polymorphism across different population groups may affect endogenous expression or activity of AMPs, potentially influencing therapeutic outcomes. However, certain genetic polymorphisms in autophagy pathways may alter the downstream effects of nano-delivery of cathelicidin. On the other hand, certain genetic polymorphisms in beta-defensins may provide a protective role in reducing HIV-1 mother-to-child-transmission. Pharmaceutical development of cathelicidins and defensins is disadvantaged with complex challenges. Nanoparticle formulations improve pharmacokinetics and biocompatibility while facilitating targeted drug delivery, potentially minimising the risk of immunogenicity or non-specific haemolytic activity. This review aims to explore the potential viability of using cathelicidins and defensins as novel pharmacotherapy in the management of TB and HIV, highlight potential pharmacogenomic implications in host mediated immunity and AMP therapeutic applications, as well as propose novel drug delivery strategies represented by nanomedicine for AMPs.

Venture financing risk assessment and risk control algorithm for small and medium-sized enterprises in the era of big data

The existing risk assessment and control methods of enterprise risk financing have a large error in mobile data, which leads to inaccurate risk assessment results and low-risk optimization control efficiency. In order to improve the accuracy of risk financing risk assessment for small and medium-sized enterprises (SMEs) and risk control optimization efficiency, this article proposes risk assessment and risk control algorithms for SMEs in the era of big data. Through verifying the information of the loan application and supplementing the data during the loan period, invoke the existing enterprise financing risk database, establish the SME venture financing risk assessment model; build the risk evaluation index system according to the characteristics of the enterprise production organization, process characteristics, and the development of the socioeconomic and technical environment; apply the GA–PSO algorithm to the design of the SME risk financing risk control scheme, and complete the SME risk financing risk assessment and risk control. The experimental results show that the risk optimization control efficiency of the control algorithm reaches more than 70%, and the risk assessment accuracy of SMEs reaches over 95%, and the runtime less than 80 ms, with good convergence performance of risk assessment and control, strong risk optimization control ability, and accurate evaluation effect.

Pharmacist and physician perception of pharmacogenetic testing

OBJECTIVES

To assess the perception of pharmacists and physicians towards pharmacogenetic testing.

METHODS

A self-administered questionnaire was developed, validated, tested for reliability and disseminated to pharmacists and physicians in Malta.

KEY FINDINGS

The study population consisted of 292 participants; 61% pharmacists (64% female, 38% practicing >10 years) and 39% physicians (50% female, 54% practicing >10 years). Pharmacists and physicians felt they lack sufficient competence in the area (95.0% and 97.4%, respectively; P > 0.05) and agreed that further training is required (92.7% and 91.2%, respectively; P > 0.05).

CONCLUSIONS

The need for further training was identified by the participants to support competency development and sustain confidence on the topic, hence facilitating the clinical implementation of pharmacogenetic testing.

Role of Precision Oncology in Type II Endometrial and Prostate Cancers in the African Population: Global Cancer Genomics Disparities

Precision oncology can be defined as molecular profiling of tumors to identify targetable alterations. Emerging research reports the high mortality rates associated with type II endometrial cancer in black women and with prostate cancer in men of African ancestry. The lack of adequate genetic reference information from the African genome is one of the major obstacles in exploring the benefits of precision oncology in the African context. Whilst external factors such as the geography, environment, health-care access and socio-economic status may contribute greatly towards the disparities observed in type II endometrial and prostate cancers in black populations compared to Caucasians, the contribution of African ancestry to the contribution of genetics to the etiology of these cancers cannot be ignored. Non-coding RNAs (ncRNAs) continue to emerge as important regulators of gene expression and the key molecular pathways involved in tumorigenesis. Particular attention is focused on activated/repressed genes and associated pathways, while the redundant pathways (pathways that have the same outcome or activate the same downstream effectors) are often ignored. However, comprehensive evidence to understand the relationship between type II endometrial cancer, prostate cancer and African ancestry remains poorly understood. The sub-Saharan African (SSA) region has both the highest incidence and mortality of both type II endometrial and prostate cancers. Understanding how the entire transcriptomic landscape of these two reproductive cancers is regulated by ncRNAs in an African cohort may help elucidate the relationship between race and pathological disparities of these two diseases. This review focuses on global disparities in medicine, PCa and ECa. The role of precision oncology in PCa and ECa in the African population will also be discussed.

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

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

Application of Big Data and Artificial Intelligence in COVID-19 Prevention, Diagnosis, Treatment and Management Decisions in China

COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread rapidly and affected most of the world since its outbreak in Wuhan, China, which presents a major challenge to the emergency response mechanism for sudden public health events and epidemic prevention and control in all countries. In the face of the severe situation of epidemic prevention and control and the arduous task of social management, the tremendous power of science and technology in prevention and control has emerged. The new generation of information technology, represented by big data and artificial intelligence (AI) technology, has been widely used in the prevention, diagnosis, treatment and management of COVID-19 as an important basic support. Although the technology has developed, there are still challenges with respect to epidemic surveillance, accurate prevention and control, effective diagnosis and treatment, and timely judgement. The prevention and control of sudden infectious diseases usually depend on the control of infection sources, interruption of transmission channels and vaccine development. Big data and AI are effective technologies to identify the source of infection and have an irreplaceable role in distinguishing close contacts and suspicious populations. Advanced computational analysis is beneficial to accelerate the speed of vaccine research and development and to improve the quality of vaccines. AI provides support in automatically processing relevant data from medical images and clinical features, tests and examination findings; predicting disease progression and prognosis; and even recommending treatment plans and strategies. This paper reviews the application of big data and AI in the COVID-19 prevention, diagnosis, treatment and management decisions in China to explain how to apply big data and AI technology to address the common problems in the COVID-19 pandemic. Although the findings regarding the application of big data and AI technologies in sudden public health events lack validation of repeatability and universality, current studies in China have shown that the application of big data and AI is feasible in response to the COVID-19 pandemic. These studies concluded that the application of big data and AI technology can contribute to prevention, diagnosis, treatment and management decision making regarding sudden public health events in the future.

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

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

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

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

Comprehensive Review of Knee Osteoarthritis Pharmacological Treatment and the Latest Professional Societies' Guidelines

Osteoarthritis is the most common musculoskeletal progressive disease, with the knee as the most commonly affected joint in the human body. While several new medications are still under research, many symptomatic therapy options, such as analgesics (opioid and non-opioid), nonsteroid anti-inflammatory drugs, symptomatic slow-acting drugs in osteoarthritis, and preparations for topical administration, are being used, with a diverse clinical response and inconsistent conclusions across various professional societies guidelines. The concept of pharmacogenomic-guided therapy, which lies on principles of the right medication for the right patient in the right dose at the right time, can significantly increase the patient’s response to symptom relief therapy in knee osteoarthritis. Corticosteroid intra-articular injections and hyaluronic acid injections provoke numerous discussions and disagreements among different guidelines, even though they are currently used in daily clinical practice. Biological options, such as platelet-rich plasma and mesenchymal stem cell injections, have shown good results in the treatment of osteoarthritis symptoms, greatly increasing the patient’s quality of life, especially when combined with other therapeutic options. Non-inclusion of the latter therapies in the guidelines, and their inconsistent stance on numerous therapy options, requires larger and well-designed studies to examine the true effects of these therapies and update the existing guidelines.