Personalized pharmacogenomics: predicting efficacy and adverse drug reactions

Characterizing the genetic architecture of drug response using gene-context interaction methods

Identifying factors that affect treatment response is a central objective of clinical research, yet the role of common genetic variation remains largely unknown. Here, we develop a framework to study the genetic architecture of response to commonly prescribed drugs in large biobanks. We quantify treatment response heritability for statins, metformin, warfarin, and methotrexate in the UK Biobank. We find that genetic variation modifies the primary effect of statins on LDL cholesterol (9% heritable) as well as their side effects on hemoglobin A1c and blood glucose (10% and 11% heritable, respectively). We identify dozens of genes that modify drug response, which we replicate in a retrospective pharmacogenomic study. Finally, we find that polygenic score (PGS) accuracy varies up to 2-fold depending on treatment status, showing that standard PGSs are likely to underperform in clinical contexts.

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.

PGxDB: an interactive web-platform for pharmacogenomics research

Pharmacogenomics, the study of how an individual's genetic makeup influences their response to medications, is a rapidly evolving field with significant implications for personalized medicine. As researchers and healthcare professionals face challenges in exploring the intricate relationships between genetic profiles and therapeutic outcomes, the demand for effective and user-friendly tools to access and analyze genetic data related to drug responses continues to grow. To address these challenges, we have developed PGxDB, an interactive, web-based platform specifically designed for comprehensive pharmacogenomics research. PGxDB enables the analysis across a wide range of genetic and drug response data types - informing cell-based validations and translational treatment strategies. We developed a pipeline that uniquely combines the relationship between medications indexed with Anatomical Therapeutic Chemical (ATC) codes with molecular target profiles with their genetic variability and predicted variant effects. This enables scientists from diverse backgrounds - including molecular scientists and clinicians - to link genetic variability to curated drug response variability and investigate indication or treatment associations in a single resource. With PGxDB, we aim to catalyze innovations in pharmacogenomics research, empower drug discovery, support clinical decision-making, and pave the way for more effective treatment regimens. PGxDB is a freely accessible database available at https://pgx-db.org/.

Scoping review of enablers and challenges of implementing pharmacogenomics testing in the primary care settings

INTRODUCTION

Pharmacogenomic testing (PGx) plays a crucial role in improving patient medication safety, yet ethical concerns and limitations impede its clinical implementation in the primary care settings.

AIMS

To systematically review the current state of PGx in the primary care settings and determine the enablers and challenges of its implementation.

DESIGN

A scoping review was carried out by adhering to Arksey and O'Malley's 6-stage methodological framework and the 2020 Joanna Briggs Institute and Levac et al. DATA SOURCES: Cochrane Library, EMBASE, Global Health, MEDLINE and PubMed were searched up to 17 July 2023.

ELIGIBILITY CRITERIA

All peer-reviewed studies in English, reporting the enablers and the challenges of implementing PGx in the primary care settings were included.

DATE EXTRACTION AND SYNTHESIS

Two independent reviewers extracted the data. Information was synthesised based on the reported enablers and the challenges of implementing PGx testing in the primary care settings. Information was then presented to stakeholders for their inputs.

RESULTS

78 studies discussing the implementation of PGx testing are included, of which 57% were published between 2019 and 2023. 68% of the studies discussed PGx testing in the primary care setting as a disease-specific themes. Healthcare professionals were the major stakeholders, with primary care physicians (55%) being the most represented. Enablers encompassed various advantages such as diagnostic and therapeutic benefits, cost reduction and the empowerment of healthcare professionals. Challenges included the absence of sufficient scientific evidence, insufficient training for healthcare professionals, ethical and legal aspects of PGx data, low patient awareness and acceptance and the high costs linked to PGx testing.

CONCLUSION

PGx testing integration in primary care requires increased consumer awareness, comprehensive healthcare provider training on legal and ethical aspects and global feasibility studies to better understand its implementation challenges. Managing high costs entails streamlining processes, advocating for reimbursement policies and investing in research on innovation and affordability research to improve life expectancy.

The Role of Pharmacogenomics Studies for Precision Medicine Among Ethiopian Patients and Their Clinical Implications: A Scoping Review

Background

Pharmacogenomics research is currently revolutionizing treatment optimization by discovering molecular markers. Medicines are the cornerstone of treatment for both acute and chronic diseases. Pharmacogenomics associated treatment response varies from 20% to 95%, resulting in from lack of efficacy to serious toxicity. Pharmacogenomics has emerged as a useful tool for therapy optimization and plays a bigger role in clinical care going forward. However, in Africa, in particular in Ethiopia, such studies are scanty and not generalizing. Therefore, the objective of this review was to outline such studies, generating comprehensive evidence and identify studied variants' association with treatment responses in Ethiopian patients.

Methods

The Joanna Briggs Institute's updated 2020 methodological guidelines for conducting and guidance for scoping reviews were used. We meticulously adhered to the systemic review reporting items checklist and scoping review meta-analyses extension.

Results

Two hundred twenty-nine possibly relevant studies were searched. These include: 64, 54, 21, 48 and 42 from PubMed, Scopus, Google Scholar, EMBASE, and manual search, respectively. Seventy-seven duplicate studies were removed. Thirty-nine papers were rejected with justification, whereas 58 studies were qualified for full-text screening. Finally 19 studies were examined. The primary pharmacogene that was found to have a significant influence on the pharmacokinetics of efavirenz was CYP2B6. Drug-induced liver injury has frequently identified toxicity among studied medications.

Conclusion and Future Perspectives

Pharmacogenomics studies in Ethiopian populations are less abundant. The studies conducted focused on infectious diseases, specifically on HAART commonly efavirenz and backbone first-line anti-tuberculosis drugs. There is a high need for further pharmacogenomics research to verify the discrepancies among the studies and for guiding precision medicine. Systematic review and meta-analysis are also recommended for pooled effects of different parameters in pharmacogenomics studies.

Integrating population genetics, stem cell biology and cellular genomics to study complex human diseases

Human pluripotent stem (hPS) cells can, in theory, be differentiated into any cell type, making them a powerful in vitro model for human biology. Recent technological advances have facilitated large-scale hPS cell studies that allow investigation of the genetic regulation of molecular phenotypes and their contribution to high-order phenotypes such as human disease. Integrating hPS cells with single-cell sequencing makes identifying context-dependent genetic effects during cell development or upon experimental manipulation possible. Here we discuss how the intersection of stem cell biology, population genetics and cellular genomics can help resolve the functional consequences of human genetic variation. We examine the critical challenges of integrating these fields and approaches to scaling them cost-effectively and practically. We highlight two areas of human biology that can particularly benefit from population-scale hPS cell studies, elucidating mechanisms underlying complex disease risk loci and evaluating relationships between common genetic variation and pharmacotherapeutic phenotypes.

Very important pharmacogenetic variants landscape and potential clinical relevance in the Zhuang population from Yunnan province

The gradual evolution of pharmacogenomics has shed light on the genetic basis for inter-individual drug response variations across diverse populations. This study aimed to identify pharmacogenomic variants that differ in Zhuang population compared with other populations and investigate their potential clinical relevance in gene-drug and genotypic-phenotypic associations. A total of 48 variants from 24 genes were genotyped in 200 Zhuang subjects using the Agena MassARRAY platform. The allele frequencies and genotype distribution data of 26 populations were obtained from the 1000 Genomes Project, followed by a comparison and statistical analysis. After Bonferroni correction, significant differences in genotype frequencies were observed of CYP3A5 (rs776746), ACE (rs4291), KCNH2 (rs1805123), and CYP2D6 (rs1065852) between the Zhuang population and the other 26 populations. It was also found that the Chinese Dai in Xishuangbanna, China, Han Chinese in Beijing, China, and Southern Han Chinese, China showed least deviation from the Zhuang population. The Esan in Nigeria, Gambian in Western Division, The Gambia, and Yoruba in Ibadan, Nigeria exhibited the largest differences. This was also proved by structural analysis, Fst analysis and phylogenetic tree. Furthermore, these differential variants may be associated with the pharmacological efficacy and toxicity of Captopril, Amlodipine, Lisinopril, metoclopramide, and alpha-hydroxymetoprolol in the Zhuang population. Our study has filled the gap of pharmacogenomic information in the Zhuang population and has provided a theoretical framework for the secure administration of drugs in the Zhuang population.

Addressing Ancestry and Sex Bias in Pharmacogenomics

The association of an individual's genetic makeup with their response to drugs is referred to as pharmacogenomics. By understanding the relationship between genetic variants and drug efficacy or toxicity, we are able to optimize pharmacological therapy according to an individual's genotype. Pharmacogenomics research has historically suffered from bias and underrepresentation of people from certain ancestry groups and of the female sex. These biases can arise from factors such as drugs and indications studied, selection of study participants, and methods used to collect and analyze data. To examine the representation of biogeographical populations in pharmacogenomic data sets, we describe individuals involved in gene-drug response studies from PharmGKB, a leading repository of drug-gene annotations, and showcaseCYP2D6, a gene that metabolizes approximately 25% of all prescribed drugs. We also show how the historical underrepresentation of females in clinical trials has led to significantly more adverse drug reactions in females than in males.

Optimisation of warfarin-dosing algorithms for Han Chinese patients with CYP2C9*13 variants

BACKGROUND

Existing pharmacogenetic algorithms cannot fully explain warfarin dose variability in all patients. CYP2C9*13 is an important allelic variant in the Han Chinese population. However, adjustment of warfarin dosing in CYP2C9*13 variant carriers remains unclear. To the best of our knowledge, this study is the first to assess the effects of adjusting warfarin dosages in Han Chinese patients harbouring CYP2C9*13 variants.

METHODS

In total, 971 warfarin-treated Han Chinese patients with atrial fibrillation were enrolled in this study. Clinical data were collected, and CYP2C9*2, *3, *13 and VKORC1-1639 G > A variants were genotyped. We quantitatively analysed the effect of CYP2C9*13 on warfarin maintenance dose and provided multiplicative adjustments for CYP2C9*13 using validated pharmacogenetic algorithms.

RESULTS

Approximately 0.6% of the Han Chinese population carried CYP2C9*13 variant, and the genotype frequency was between those of CYP2C9*2 and CYP2C9*3. The warfarin maintenance doses were significantly reduced in CYP2C9*13 carriers. When CYP2C9*13 variants were not considered, the pharmacogenetic algorithms overestimated warfarin maintenance doses by 1.03-1.16 mg/d on average. The actual warfarin dose in CYP2C9*13 variant carriers was approximately 40% lower than the algorithm-predicted dose. Adjusting the warfarin-dosing algorithm according to the CYP2C9*13 allele could reduce the dose prediction error.

CONCLUSION

Our study showed that the algorithm-predicted doses should be lowered for CYP2C9*13 carriers. Inclusion of the CYP2C9*13 variant in the warfarin-dosing algorithm tends to predict the warfarin maintenance dose more accurately and improves the efficacy and safety of warfarin administration in Han Chinese patients.

Polygenic risk scores in pharmacogenomics: opportunities and challenges-a mini review

Pharmacogenomics (PGx) aims at tailoring drug therapy by considering patient genetic makeup. While drug dosage guidelines have been extensively based on single gene mutations (single nucleotide polymorphisms) over the last decade, polygenic risk scores (PRS) have emerged in the past years as a promising tool to account for the complex interplay and polygenic nature of patients' genetic predisposition affecting drug response. Even though PRS research has demonstrated convincing evidence in disease risk prediction, the clinical utility and its implementation in daily care has yet to be demonstrated, and pharmacogenomics is no exception; usual endpoints include drug efficacy or toxicity. Here, we review the general pipeline in PRS calculation, and we discuss some of the remaining barriers and challenges that must be undertaken to bring PRS research in PGx closer to patient care. Besides the need in following reporting guidelines and larger PGx patient cohorts, PRS integration will require close collaboration between bioinformatician, treating physicians and genetic consultants to ensure a transparent, generalizable, and trustful implementation of PRS results in real-world medical decisions.

Can Kidney Organoid Xenografts Accelerate Therapeutic Development for Genetic Kidney Disorders?

A number of genetic kidney diseases can now be replicated experimentally, using kidney organoids generated from human pluripotent stem cells. This methodology holds great potential for drug discovery. Under in vitro conditions, however, kidney organoids remain developmentally immature, develop scarce vasculature, and may contain undesired off-target cell types. Those critical deficiencies limit their potential as disease-modeling tools. Orthotopic transplantation under the kidney capsule improves the anatomic maturity and vascularization of kidney organoids, while reducing off-target cell content. The improvements can translate into more accurate representations of disease phenotypes and mechanisms in vivo . Recent studies using kidney organoid xenografts highlighted the unique potential of this novel methodology for elucidating molecular mechanisms driving monogenic kidney disorders and for the development ofnovel pharmacotherapies.

Allergic and other adverse reactions to drugs used in anesthesia and surgery

The list of drugs patients may be exposed to during the perioperative and postoperative periods is potentially extensive. It includes induction agents, neuromuscular blocking drugs (NMBDs), opioids, antibiotics, sugammadex, colloids, local anesthetics, polypeptides, antifibrinolytic agents, heparin and related anticoagulants, blue dyes, chlorhexidine, and a range of other agents depending on several factors related to individual patients’ clinical condition and progress in the postoperative recovery period. To avoid poor or ultrarapid metabolizers to a particular drug (for example tramadol and codeine) or possible adverse drug reactions (ADRs), some drugs may need to be avoided during or after surgery. This will be the case for patients with a history of anaphylaxis or other adverse events/intolerances to a known drug. Other drugs may be ceased for a period before surgery, e.g., anticoagulants that increase the chance of bleeding; diuretics for patients with acute renal failure; antihypertensives relative to kidney injury after major vascular surgery; and serotonergic drugs that together with some opioids may rarely induce serotonin toxicity. Studies of germline variations shown by genotyping and phenotyping to identify a predisposition of genetic factors to ADRs offer an increasingly important approach to individualize drug therapy. Studies of associations of human leukocyte antigen (HLA) genes with some serious delayed immune-mediated reactions are ongoing and variations of drug-metabolizing cytochrome CYP450 enzymes, P-glycoprotein, and catechol-O -methyltransferase show promise for the assessment of ADRs and non-responses to drugs, particularly opioids and other analgesics. Surveys of ADRs from an increasing number of institutions often cover small numbers of patients, are retrospective in nature, fail to clearly identify culprit drugs, and do not adequately distinguish immune-mediated from non-immune-mediated anaphylactoid reactions. From the many surveys undertaken, the large list of agents identified during and after anesthesia and surgery are examined for their ADR involvement. Drugs are classified into those most often involved, (NMBD and antibiotics); drugs that are becoming more frequently implicated, namely antibiotics (particularly teicoplanin), and blue dyes; those becoming less frequently involved; and drugs more rarely involved in perioperative, and postoperative adverse reactions but still important and necessary to keep in mind for the occasional potential sensitive patient. Clinicians should be aware of the similarities between drug-induced true allergic type I IgE/FcεRI- and pseudoallergic MRGPRX2-mediated ADRs, the clinical features of each, and their distinguishing characteristics. Procedures for identifying MRGPRX2 agonists and diagnosing and distinguishing pseudoallergic from allergic reaction mechanisms are discussed.

Joint Analysis of Phenotypic and Genomic Diversity Sheds Light on the Evolution of Xenobiotic Metabolism in Humans

Variation in genes involved in the absorption, distribution, metabolism, and excretion of drugs (ADME) can influence individual response to a therapeutic treatment. The study of ADME genetic diversity in human populations has led to evolutionary hypotheses of adaptation to distinct chemical environments. Population differentiation in measured drug metabolism phenotypes is, however, scarcely documented, often indirectly estimated via genotype-predicted phenotypes. We administered seven probe compounds devised to target six cytochrome P450 enzymes and the P-glycoprotein (P-gp) activity to assess phenotypic variation in four populations along a latitudinal transect spanning over Africa, the Middle East, and Europe (349 healthy Ethiopian, Omani, Greek, and Czech volunteers). We demonstrate significant population differentiation for all phenotypes except the one measuring CYP2D6 activity. Genome-wide association studies (GWAS) evidenced that the variability of phenotypes measuring CYP2B6, CYP2C9, CYP2C19, and CYP2D6 activity was associated with genetic variants linked to the corresponding encoding genes, and additional genes for the latter three. Instead, GWAS did not indicate any association between genetic diversity and the phenotypes measuring CYP1A2, CYP3A4, and P-gp activity. Genome scans of selection highlighted multiple candidate regions, a few of which included ADME genes, but none overlapped with the GWAS candidates. Our results suggest that different mechanisms have been shaping the evolution of these phenotypes, including phenotypic plasticity, and possibly some form of balancing selection. We discuss how these contrasting results highlight the diverse evolutionary trajectories of ADME genes and proteins, consistent with the wide spectrum of both endogenous and exogenous molecules that are their substrates.

"It's what makes us unique": Indigenous Australian perspectives on genetics research to improve comorbid mental and chronic disease outcomes

BACKGROUND

The role of personalized treatment approaches, including those based on genetic testing, are increasingly enabling informed decision-making to improve health outcomes. Research involving Indigenous Australians has been lagging behind, although this population experiences a higher prevalence of chronic disease and mental health disorders.

METHODS

Using community-based participatory research principles, this study purposefully interviewed participants with a diagnosed common mental disorder and a comorbid chronic disease condition. This was an inductive thematic analysis on semi-structured interviews with consenting participants (n = 48). Common themes and analytical domains were identified that provided a semantic understanding shared by participants.

RESULTS

Five emerging themes were identified, primarily focusing on: (1) The perceptions and understanding of genetics research; (2) culturally appropriate conduct of genetics research; (3) the role of indigenous-led genetics research; (4) future prospects of genetics research; and (5) the importance of genetics research for patients with mental and physical health comorbidities.

CONCLUSION

Indigenous Australians are under-represented in pharmacogenomics research despite well-documented epidemiological research demonstrating that Indigenous people globally experience greater risk of developing certain chronic diseases and more severe disease progression. Positive outcomes from this study highlight the importance of not only involving Indigenous participants, but providing leadership and governance opportunities for future genetics research.

Cost-Effectiveness of Pharmacogenomics-Guided Prescribing to Prevent Gene-Drug-Related Deaths: A Decision-Analytic Model

Aim: Prospective studies support the clinical impact of pharmacogenomics (PGx)-guided prescribing to reduce severe and potentially fatal adverse effects. Drug-gene interactions (DGIs) preventing potential drug-related deaths have been categorized as “essential” by the Dutch Pharmacogenetics Working Group (DPWG). The collective clinical impact and cost-effectiveness of this sub-set is yet undetermined. Therefore, we aim to assess impact and cost-effectiveness of “essential” PGx tests for prevention of gene-drug-related deaths, when adopted nation-wide.

Methods: We used a decision-analytic model to quantify the number and cost per gene-drug-related death prevented, from a 1-year Dutch healthcare perspective. The modelled intervention is a single gene PGx-test for CYP2C19, DPYD, TPMT or UGT1A1 to guide prescribing based on the DPWG recommendations among patients in the Netherlands initiating interacting drugs (clopidogrel, capecitabine, systemic fluorouracil, azathioprine, mercaptopurine, tioguanine or irinotecan).

Results: For 148,128 patients initiating one of seven drugs in a given year, costs for PGx-testing, interpretation, and drugs would increase by €21.4 million. Of these drug initiators, 35,762 (24.1%) would require an alternative dose or drug. PGx-guided prescribing would relatively reduce gene-drug related mortality by 10.6% (range per DGI: 8.1–14.5%) and prevent 419 (0.3% of initiators) deaths a year. Cost-effectiveness is estimated at €51,000 per prevented gene-drug-related death (range per DGI: €-752,000–€633,000).

Conclusion: Adoption of PGx-guided prescribing for “essential” DGIs potentially saves the lives of 0.3% of drug initiators, at reasonable costs.

Ethnic Diversity and Warfarin Pharmacogenomics

Warfarin has remained the most commonly prescribed vitamin K oral anticoagulant worldwide since its approval in 1954. Dosing challenges including having a narrow therapeutic window and a wide interpatient variability in dosing requirements have contributed to making it the most studied drug in terms of genotype-phenotype relationships. However, most of these studies have been conducted in Whites or Asians which means the current pharmacogenomics evidence-base does not reflect ethnic diversity. Due to differences in minor allele frequencies of key genetic variants, studies conducted in Whites/Asians may not be applicable to underrepresented populations such as Blacks, Hispanics/Latinos, American Indians/Alaska Natives and Native Hawaiians/other Pacific Islanders. This may exacerbate health inequalities when Whites/Asians have better anticoagulation profiles due to the existence of validated pharmacogenomic dosing algorithms which fail to perform similarly in the underrepresented populations. To examine the extent to which individual races/ethnicities are represented in the existing body of pharmacogenomic evidence, we review evidence pertaining to published pharmacogenomic dosing algorithms, including clinical utility studies, cost-effectiveness studies and clinical implementation guidelines that have been published in the warfarin field.

A population study of clinically actionable genetic variation affecting drug response from the Middle East

Clinical implementation of pharmacogenomics will help in personalizing drug prescriptions and alleviate the personal and financial burden due to inefficacy and adverse reactions to drugs. However, such implementation is lagging in many parts of the world, including the Middle East, mainly due to the lack of data on the distribution of actionable pharmacogenomic variation in these ethnicities. We analyzed 6,045 whole genomes from the Qatari population for the distribution of allele frequencies of 2,629 variants in 1,026 genes known to affect 559 drugs or classes of drugs. We also performed a focused analysis of genotypes or diplotypes of 15 genes affecting 46 drugs, which have guidelines for clinical implementation and predicted their phenotypic impact. The allele frequencies of 1,320 variants in 703 genes affecting 299 drugs or class of drugs were significantly different between the Qatari population and other world populations. On average, Qataris carry 3.6 actionable genotypes/diplotypes, affecting 13 drugs with guidelines for clinical implementation, and 99.5% of the individuals had at least one clinically actionable genotype/diplotype. Increased risk of simvastatin-induced myopathy could be predicted in ~32% of Qataris from the diplotypes of SLCO1B1, which is higher compared to many other populations, while fewer Qataris may need tacrolimus dosage adjustments for achieving immunosuppression based on the CYP3A5 diplotypes compared to other world populations. Distinct distribution of actionable pharmacogenomic variation was also observed among the Qatari subpopulations. Our comprehensive study of the distribution of actionable genetic variation affecting drugs in a Middle Eastern population has potential implications for preemptive pharmacogenomic implementation in the region and beyond.

Genetic variation of pharmacogenomic VIP variants in the Chinese Li population: an updated research

Previous studies have shown that the frequency of very important pharmacogenomic (VIP) genes varies in different populations which leads to the diversities in drug efficacy, safety, and the risk associated with adverse drug reactions (ADRs). The purpose of this study was to identify the distribution differences of VIP variants between the Li population and the other 13 populations. Based on the Pharmacogenomics Knowledgebase database (PhamGKB), we successfully genotyped 52 VIP variants within 27 genes in 200 unrelated Li population. χ² test was used to evaluate the significant differences of genotype and allele frequencies between the Li and the other 13 populations from 1000 Genomes Project. Our study showed that the genotype frequencies of single nucleotide polymorphisms (SNPs) on KCNH2, ACE, CYP4F2, and CYP2E1 were considerably different between Li and the other 13 populations, especially in rs1805123 (KCNH2), rs4291 (ACE), rs3093105 (CYP4F2), and rs6413432 (CYP2E1) loci. Meanwhile, we found several VIP variants that might alter the drug metabolism of cisplatin-cyclophosphamide (CYP2E1), vitamin E (CYP4F2), asthma amlodipine, chlorthalidone, and lisinopril (ACE) through PharmGKB. We also identified other variants which were associated with adverse effects in isoniazid and rifampicin (CYP2E1; hepatotoxicity). The four loci rs1805123 (KCNH2), rs4291 (ACE), rs3093105 (CYP4F2), and rs6413432 (CYP2E1) provided a reliable basis for the prediction of the efficacy of certain drugs. The study complemented the existed pharmacogenomics information, which could provide theoretical basis for predicting the efficacy of certain drugs in the Li population.

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.

Application of long-read sequencing to elucidate complex pharmacogenomic regions: a proof of principle

The use of pharmacogenomics in clinical practice is becoming standard of care. However, due to the complex genetic makeup of pharmacogenes, not all genetic variation is currently accounted for. Here, we show the utility of long-read sequencing to resolve complex pharmacogenes by analyzing a well-characterised sample. This data consists of long reads that were processed to resolve phased haploblocks. 73% of pharmacogenes were fully covered in one phased haploblock, including 9/15 genes that are 100% complex. Variant calling accuracy in the pharmacogenes was high, with 99.8% recall and 100% precision for SNVs and 98.7% precision and 98.0% recall for Indels. For the majority of gene-drug interactions in the DPWG and CPIC guidelines, the associated genes could be fully resolved (62% and 63% respectively). Together, these findings suggest that long-read sequencing data offers promising opportunities in elucidating complex pharmacogenes and haplotype phasing while maintaining accurate variant calling.

Pharmacogenomics of Alzheimer's Disease: Novel Strategies for Drug Utilization and Development

Alzheimer's disease (AD) is a priority health problem in developed countries with a high cost to society. Approximately 20% of direct costs are associated with pharmacological treatment. Over 90% of patients require multifactorial treatments, with risk of adverse drug reactions (ADRs) and drug-drug interactions (DDIs) for the treatment of concomitant diseases such as hypertension (>25%), obesity (>70%), diabetes mellitus type 2 (>25%), hypercholesterolemia (40%), hypertriglyceridemia (20%), metabolic syndrome (20%), hepatobiliary disorder (15%), endocrine/metabolic disorders (>20%), cardiovascular disorder (40%), cerebrovascular disorder (60-90%), neuropsychiatric disorders (60-90%), and cancer (10%).For the past decades, pharmacological studies in search of potential treatments for AD focused on the following categories: neurotransmitter enhancers (11.38%), multitarget drugs (2.45%), anti-amyloid agents (13.30%), anti-tau agents (2.03%), natural products and derivatives (25.58%), novel synthetic drugs (8.13%), novel targets (5.66%), repository drugs (11.77%), anti-inflammatory drugs (1.20%), neuroprotective peptides (1.25%), stem cell therapy (1.85%), nanocarriers/nanotherapeutics (1.52%), and other compounds (<1%).Pharmacogenetic studies have shown that the therapeutic response to drugs in AD is genotype-specific in close association with the gene clusters that constitute the pharmacogenetic machinery (pathogenic, mechanistic, metabolic, transporter, pleiotropic genes) under the regulatory control of epigenetic mechanisms (DNA methylation, histone/chromatin remodeling, microRNA regulation). Most AD patients (>60%) are carriers of over ten pathogenic genes. The genes that most frequently (>50%) accumulate pathogenic variants in the same AD case are A2M (54.38%), ACE (78.94%), BIN1 (57.89%), CLU (63.15%), CPZ (63.15%), LHFPL6 (52.63%), MS4A4E (50.87%), MS4A6A (63.15%), PICALM (54.38%), PRNP (80.7059), and PSEN1 (77.19%). There is also an accumulation of 15 to 26 defective pharmagenes in approximately 85% of AD patients. About 50% of AD patients are carriers of at least 20 mutant pharmagenes, and over 80% are deficient metabolizers for the most common drugs, which are metabolized via the CYP2D6, CYP2C9, CYP2C19, and CYP3A4/5 enzymes.The implementation of pharmacogenetics can help optimize drug development and the limited therapeutic resources available to treat AD, and personalize the use of anti-dementia drugs in combination with other medications for the treatment of concomitant disorders.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Genophenotypic Factors and Pharmacogenomics in Adverse Drug Reactions

Adverse drug reactions (ADRs) rank as one of the top 10 leading causes of death and illness in developed countries. ADRs show differential features depending upon genotype, age, sex, race, pathology, drug category, route of administration, and drug–drug interactions. Pharmacogenomics (PGx) provides the physician effective clues for optimizing drug efficacy and safety in major problems of health such as cardiovascular disease and associated disorders, cancer and brain disorders. Important aspects to be considered are also the impact of immunopharmacogenomics in cutaneous ADRs as well as the influence of genomic factors associated with COVID-19 and vaccination strategies. Major limitations for the routine use of PGx procedures for ADRs prevention are the lack of education and training in physicians and pharmacists, poor characterization of drug-related PGx, unspecific biomarkers of drug efficacy and toxicity, cost-effectiveness, administrative problems in health organizations, and insufficient regulation for the generalized use of PGx in the clinical setting. The implementation of PGx requires: (i) education of physicians and all other parties involved in the use and benefits of PGx; (ii) prospective studies to demonstrate the benefits of PGx genotyping; (iii) standardization of PGx procedures and development of clinical guidelines; (iv) NGS and microarrays to cover genes with high PGx potential; and (v) new regulations for PGx-related drug development and PGx drug labelling.

Genome-Wide Association Study of Lithium-Induced Dry Mouth in Bipolar I Disorder

Dry mouth is a rather common unpleasant adverse drug reaction (ADR) to lithium treatment in bipolar disorders that often lead to poor adherence or early dropout. The aim of this study was to identify the genetic variants of dry mouth associated with lithium treatment in patients with bipolar I (BPI) disorder. In total, 1242 BPI patients who had ever received lithium treatment were identified by the Taiwan Bipolar Consortium for this study. The proportions of patients who experienced impaired drug compliance during lithium medication were comparable between those only with dry mouth and those with any other ADR (86% and 93%, respectively). Dry mouth appeared to be the most prevalent (47.3%) ADR induced by lithium treatment. From the study patients, 921 were included in a genome-wide association study (GWAS), and replication was conducted in the remaining 321 patients. The SNP rs10135918, located in the immunoglobulin heavy chain locus (IGH), showed the strongest associations in the GWAS (p = 2.12 × 10⁻³⁷) and replication groups (p = 6.36 × 10⁻¹³) (dominant model) for dry mouth with a sensitivity of 84.9% in predicting dry mouth induced by lithium. Our results may be translated into clinical recommendation to help identify at-risk individuals for early identification and management of dry mouth, which will improve medication adherence.

Development and Implementation of In-House Pharmacogenomic Testing Program at a Major Academic Health System

Pharmacogenomics (PGx) studies how a person's genes affect the response to medications and is quickly becoming a significant part of precision medicine. The clinical application of PGx principles has consistently been cited as a major opportunity for improving therapeutic outcomes. Several recent studies have demonstrated that most individuals (> 90%) harbor PGx variants that would be clinically actionable if prescribed a medication relevant to that gene. In multiple well-conducted studies, the results of PGx testing have been shown to guide therapy choice and dosing modifications which improve treatment efficacy and reduce the incidence of adverse drug reactions (ADRs). Although the value of PGx testing is evident, its successful implementation in a clinical setting presents a number of challenges to molecular diagnostic laboratories, healthcare systems, providers and patients. Different molecular methods can be applied to identify PGx variants and the design of the assay is therefore extremely important. Once the genotyping results are available the biggest technical challenge lies in turning this complex genetic information into phenotypes and actionable recommendations that a busy clinician can effectively utilize to provide better medical care, in a cost-effective, efficient and reliable manner. In this paper we describe a successful and highly collaborative implementation of the PGx testing program at the University of Minnesota and MHealth Fairview Molecular Diagnostic Laboratory and selected Pharmacies and Clinics. We offer detailed descriptions of the necessary components of the pharmacogenomic testing implementation, the development and technical validation of the in-house SNP based multiplex PCR based assay targeting 20 genes and 48 SNPs as well as a separate CYP2D6 copy number assay along with the process of PGx report design, results of the provider and pharmacists usability studies, and the development of the software tool for genotype-phenotype translation and gene-phenotype-drug CPIC-based recommendations. Finally, we outline the process of developing the clinical workflow that connects the providers with the PGx experts within the Molecular Diagnostic Laboratory and the Pharmacy.

Data-Enriched Edible Pharmaceuticals (DEEP) with Bespoke Design, Dose and Drug Release

Data-enriched edible pharmaceuticals (DEEP) is an approach to obtain personalized medicine, in terms of flexible and precise drug doses, while at the same time containing data, embedded in quick response (QR) codes at a single dosage unit level. The aim of this study was to fabricate DEEP with a patient-tailored dose, modify drug release and design to meet patients' preferences. It also aimed to investigate physical stability in terms of the readability of QR code patterns of DEEP during storage. Cannabinoids, namely, cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC), were used as the model active pharmaceutical ingredients (APIs). Three different substrates and two colorants for the ink were tested for their suitability to fabricate DEEP by desktop inkjet printing. Flexible doses and customizable designs of DEEP were obtained by manipulating the digital design of the QR code, particularly, by exploring different pattern types, embedded images and the physical size of the QR code pattern. Modification of the release of both APIs from DEEP was achieved by applying a hydroxypropyl cellulose (HPC) polymer coating. The appearance and readability of uncoated and polymer-coated DEEP did not change on storage in cold and dry conditions; however, the HPC polymer layer was insufficient in preserving the readability of the QR code pattern in the extreme storage condition (40 °C and 75% relative humidity). To sum up, the DEEP concept provides opportunities for the personalization of medicines, considering also patients' preferences.

Safety of medicines and vaccines - building next generation capability

The systematic safety surveillance of real-world use of medicinal products and related activities (pharmacovigilance) started in earnest as a scientific field only in the 1960s. While developments have occurred over the past 50 years, adding to its complexity and sophistication, the extent to which some of these advances have positively impacted the capability for ensuring patient safety is questionable. We review how the conduct of safety surveillance has changed, highlight recent scientific advances, and argue how they need to be harnessed to enhance pharmacovigilance in the future. Specifically, we describe five changes that we believe should and will need to happen globally in the coming years: (i) better, more diverse data used for safety; (ii) the switch from manual activities to automation; (iii) removal of limited value, extraneous transactional activities and replacement with sharpened focus on scientific efforts to improve patient safety; (iv) patient-involved and focussed safety; and (v) personalised safety.

The Transporter-Mediated Cellular Uptake and Efflux of Pharmaceutical Drugs and Biotechnology Products: How and Why Phospholipid Bilayer Transport Is Negligible in Real Biomembranes

Over the years, my colleagues and I have come to realise that the likelihood of pharmaceutical drugs being able to diffuse through whatever unhindered phospholipid bilayer may exist in intact biological membranes in vivo is vanishingly low. This is because (i) most real biomembranes are mostly protein, not lipid, (ii) unlike purely lipid bilayers that can form transient aqueous channels, the high concentrations of proteins serve to stop such activity, (iii) natural evolution long ago selected against transport methods that just let any undesirable products enter a cell, (iv) transporters have now been identified for all kinds of molecules (even water) that were once thought not to require them, (v) many experiments show a massive variation in the uptake of drugs between different cells, tissues, and organisms, that cannot be explained if lipid bilayer transport is significant or if efflux were the only differentiator, and (vi) many experiments that manipulate the expression level of individual transporters as an independent variable demonstrate their role in drug and nutrient uptake (including in cytotoxicity or adverse drug reactions). This makes such transporters valuable both as a means of targeting drugs (not least anti-infectives) to selected cells or tissues and also as drug targets. The same considerations apply to the exploitation of substrate uptake and product efflux transporters in biotechnology. We are also beginning to recognise that transporters are more promiscuous, and antiporter activity is much more widespread, than had been realised, and that such processes are adaptive (i.e., were selected by natural evolution). The purpose of the present review is to summarise the above, and to rehearse and update readers on recent developments. These developments lead us to retain and indeed to strengthen our contention that for transmembrane pharmaceutical drug transport "phospholipid bilayer transport is negligible".

Pharmacogenomic testing to support prescribing in primary care: a structured review of implementation models

The application of pharmacogenomics could meaningfully contribute toward medicines optimization within primary care. This review identified 13 studies describing eight implementation models utilizing a multi-gene pharmacogenomic panel within a primary care or community setting. These were small feasibility studies (n <200). They demonstrated importance and feasibility of pre-test counseling, the role of the pharmacist, data integration into the electronic medical record and point-of-care clinical decision support systems (CDSS). Findings were considered alongside existing primary care prescribing practices and implementation frameworks to demonstrate how issues may be addressed by existing nationalized healthcare and primary care infrastructure. Development of point-of-care CDSS should be prioritized; establishing clinical leadership, education programs, defining practitioner roles and responsibilities and addressing commissioning issues will also be crucial.

Translational Pharmacogenomics: Discovery, Evidence Synthesis and Delivery of Race-Conscious Medicine

Response to medications, the principal treatment modality for acute and chronic diseases, is highly variable, with 40-70% of patients exhibiting lack of efficacy or adverse drug reactions. With ~ 15-30% of this variability explained by genetic variants, pharmacogenomics has become a valuable tool in our armamentarium for optimizing treatments and is poised to play an increasing role in clinical care. This review presents the progress made toward elucidating genetic underpinnings of drug response including discovery of race/ancestry-specific pharmacogenetic variants and discusses the current evidence and evidence framework for actionability. The review is framed in the context of changing demographics and evolving views related to race and ancestry. Finally, it highlights the vital role played by cohort studies in elucidating genetic differences in drug response across race and ancestry and the informal collaborations that have enabled the field to bridge the "bench to bedside" translational gap.

Evaluation of Bleeding Rate and Time in Therapeutic Range in Patients Using Warfarin Before and During the COVID-19 Pandemic-Warfarin Treatment in COVID-19

The treatment process of patients using warfarin is expected to be hindered during the COVID-19 pandemic. Therefore we investigated whether the time in therapeutic range (TTR) and bleeding complications were affected during the COVID-19 pandemic. 355 patients using warfarin were included between March 2019 to March 2021. Demographic parameters, INR (international normalized ratio), and bleeding rates were recorded retrospectively. The TTR value was calculated using Rosendaal’s method. The mean age of the patients was 61 ± 12 years and 55% of them were female. The mean TTR value during the COVID-19 pandemic was lower than the pre-COVID-19 period (56 ± 21 vs 68 ± 21, P < 0.001). Among the patients, 41% had a lack of outpatient INR control. During the COVID-19 pandemic, 71 (20%) patients using VKA suffered bleeding. Among patients with bleeding, approximately 60% did not seek medical help and 6% of patients performed self-reduction of the VKA dose. During the COVID-19 pandemic, TTR values have decreased with the lack of monitoring. Furthermore, the majority of patients did not seek medical help even in case of bleeding.

Cytochrome P450 2C19 enzyme, Cytochrome P450 2C9 enzyme, and Cytochrome P450 2D6 enzyme allelic variants and its possible effect on drug metabolism: A retrospective study

ABSTRACT

The objective of the present study was to assess the allelic variations of Cytochrome P450 (CYP) enzymes Cytochrome P450 2C19 (CYP2C19), Cytochrome P450 2C9 (CYP2C9), and Cytochrome P450 2D6 (CYP2D6) as they play a major role in drug metabolism. The interindividual genetic variabilities of these enzymes can account for different responsiveness as well as concentration fluctuations for a particular drug.During the period of 2017 to 2018 a total of 54 patients have received pharmacogenetic testing at the Department of Genetics and Molecular Medicine at Kaunas Clinics. According to the genotype-metabolic phenotypes of CYP2C19, CYP2D6, CYP2C9 enzymes patients were classified according to the guidelines by Clinical Pharmacogenetics Implementation Consortium (CPIC): normal metabolizers (NMs), intermediate metabolizers (IMs), rapid metabolizers (RMs), ultrarapid metabolizers (UMs), and poor metabolizers (PMs).CYP2C19 enzyme allelic distribution: 18 patients (33.33%) with ∗1/∗1 genotype were NMs; 14 patients (25.93%) with ∗1/∗2; ∗2/∗17 genotypes were classified as IMs; 15 patients (27.78%) possessed ∗1/∗17 genotype and were RMs; 4 patients (7.4%) had ∗17/∗17 genotype with increased enzyme activity compared with RMs, were classified as UMs; 3 patients (5.56%) had ∗2/∗2 genotype and were marked as PMs. CYP2D6 enzyme allelic distribution: 26 patients (48.148%) contained ∗1/∗1,∗2/∗2,∗1/∗2,∗1/∗41,∗2/∗41 genotypes with normal enzymatic function so were accounted as NMs; 21 patients (38.89%) with ∗1/∗5, ∗2/∗4, ∗10/∗41, ∗1/∗4, ∗1/∗3, ∗2/∗5, ∗2/∗4, ∗2/∗6 genotypes were accounted as IMs; 2 patients (3.7%) possessed ∗2XN genotype and were accounted as UMs and 5 patients (9.26%) possessed ∗4/∗5,∗4/∗10,∗4/∗9,∗4/∗41 genotypes and had non-functional enzymatic activity so were accounted as PMs; CYP2C9 enzyme allelic distribution: 44 patients (81.48%) with∗1/∗1 genotype were NMs; 10 patients (18.52%) with ∗1/∗2;∗1/∗3 genotypes were IMs.The results of our study indicate that deviations from the normal enzymatic activity is common amongst Lithuanian people and combinatory genotyping of CYP2D6, CYP2C9, and CYP2C19 has to be promoted as an advanced method because of most commonly prescribed medicines like analgesics, antihypertensive, antidepressants are metabolized by multiple pathways involving enzymes in the CYP450 family.

Prediction of adverse drug reactions using drug convolutional neural networks

Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standard process of introduction of a new drug into a market involves a lot of clinical trials and tests. This is a tedious and time consuming process and also involves a lot of monetary resources. The faster approval of a drug helps the patients who are in need of the drug. The in silico prediction of Adverse Drug Reactions can help speed up the aforementioned process. The challenges involved are lack of negative data present and predicting ADR from just the chemical structure. Although many models are already available to predict ADR, most of the models use biological activities identifiers, chemical and physical properties in addition to chemical structures of the drugs. But for most of the new drugs to be tested, only chemical structures will be available. The performance of the existing models predicting ADR only using chemical structures is not efficient. Therefore, an efficient prediction of ADRs from just the chemical structure has been proposed in this paper. The proposed method involves a separate model for each ADR, making it a binary classification problem. This paper presents a novel CNN model called Drug Convolutional Neural Network (DCNN) to predict ADRs using chemical structures of the drugs. The performance is measured using the metrics such as Accuracy, Recall, Precision, Specificity, F1 score, AUROC and MCC. The results obtained by the proposed DCNN model outperform the competing models on the SIDER4.1 database in terms of all the metrics. A case study has been performed on a COVID-19 recommended drugs, where the proposed model predicted the ADRs that are well aligned with the observations made by medical professionals using conventional methods.

Progress in Nanorobotics for Advancing Biomedicine

Nanorobotics, which has long been a fantasy in the realm of science fiction, is now a reality due to the considerable developments in diverse fields including chemistry, materials, physics, information and nanotechnology in the past decades. Not only different prototypes of nanorobots whose sizes are nanoscale are invented for various biomedical applications, but also robotic nanomanipulators which are able to handle nano-objects obtain substantial achievements for applications in biomedicine. The outstanding achievements in nanorobotics have significantly expanded the field of medical robotics and yielded novel insights into the underlying mechanisms guiding life activities, remarkably showing an emerging and promising way for advancing the diagnosis & treatment level in the coming era of personalized precision medicine. In this review, the recent advances in nanorobotics (nanorobots, nanorobotic manipulations) for biomedical applications are summarized from several facets (including molecular machines, nanomotors, DNA nanorobotics, and robotic nanomanipulators), and the future perspectives are also presented.

Therapeutic Characteristics, Chemotherapy-Related Toxicities and Survivorship in Colorectal Cancer Patients

Background

Colorectal Cancer (CRC) is a major health problem around the globe. In Morocco, the disease ranks third after breast and lung cancers. This study is the first in Morocco to investigate epidemiological, clinical and therapeutic features while exhaustively describing toxic side-effects to chemotherapy of CRC and studying the 3-years survivorship.

Methods

This is a descriptive and analytical retrospective study of about 290 patients with CRC enrolled during the period of January-December 2013. Statistical analysis was performed to correlate clinicopathological data with chemotherapy toxicity and survivorship in patients, by Chi² test. Overall Survival (OS) rate has been calculated by the Kaplan-Meier method and compared using Log-rank test.

Results

Fifty-five percent had a tumor localized in rectum, and 42,8% in colon. Mean age of these patients at diagnosis was 56,16 ± 14,6. incidence rate of adverse events (grade I to IV) was 85,6%. Diarrhea was the predominant toxicity (4.6%) occurring at a high grade (grade III–IV).

The 3-years OS rate of patients with CRC was 71%. OS decreased by age, and patients with age subgroup between 40 to 59 years had a better OS than the other age subgroups (60 to 79 years and >80 years) with a p-value of 0.0001. Occurence of toxicity (all grades and types) was linked to a higher survival rates compared to the group who had no toxicity noticed (p-value of 0.001).

Conclusion

Our study shows that patients who had a polychemotherapy had a better OS than those who had monotherapy (p-value of 0.002).

Effects of rare CYP2C9 alleles on stable warfarin doses in Chinese Han patients with atrial fibrillation

Aim: Gene polymorphisms are critical in warfarin dosing variation. Here, the role of rare CYP2C9 alleles on warfarin doses in Chinese Han patients was investigated. Methods: A retrospective study recruited 681 warfarin treated atrial fibrillation patients. The genetic and clinical data were collected. Dose-related variables were selected by univariate analyses and the warfarin-dosing algorithm was derived by multivariate regression analysis. Results: Three rare CYP2C9 alleles (CYP2C9*13, *16 and *60) were associated with lower stable doses. Inclusion of the rare CYP2C9 alleles in the prediction model added an extra 3.7% warfarin dose predictive power. Conclusion: CYP2C9*13, *16 and *60 was associated with lower stable warfarin doses in Chinese patients. The algorithm including rare CYP2C9 alleles tends to more accurately predict stable warfarin doses.

Generating evidence for precision medicine: considerations made by the Ubiquitous Pharmacogenomics Consortium when designing and operationalizing the PREPARE study

OBJECTIVES

Pharmacogenetic panel-based testing represents a new model for precision medicine. A sufficiently powered prospective study assessing the (cost-)effectiveness of a panel-based pharmacogenomics approach to guide pharmacotherapy is lacking. Therefore, the Ubiquitous Pharmacogenomics Consortium initiated the PREemptive Pharmacogenomic testing for prevention of Adverse drug Reactions (PREPARE) study. Here, we provide an overview of considerations made to mitigate multiple methodological challenges that emerged during the design.

METHODS

An evaluation of considerations made when designing the PREPARE study across six domains: study aims and design, primary endpoint definition and collection of adverse drug events, inclusion and exclusion criteria, target population, pharmacogenomics intervention strategy, and statistical analyses.

RESULTS

Challenges and respective solutions included: (1) defining and operationalizing a composite primary endpoint enabling measurement of the anticipated effect, by including only severe, causal, and drug genotype-associated adverse drug reactions; (2) avoiding overrepresentation of frequently prescribed drugs within the patient sample while maintaining external validity, by capping drugs of enrolment; (3) designing the pharmacogenomics intervention strategy to be applicable across ethnicities and healthcare settings; and (4) designing a statistical analysis plan to avoid dilution of effect by initially excluding patients without a gene-drug interaction in a gatekeeping analysis.

CONCLUSION

Our design considerations will enable quantification of the collective clinical utility of a panel of pharmacogenomics-markers within one trial as a proof-of-concept for pharmacogenomics-guided pharmacotherapy across multiple actionable gene-drug interactions. These considerations may prove useful to other investigators aiming to generate evidence for precision medicine.

Toxicogenetic analysis of Δ9-THC-metabolizing enzymes

While the impact of genetic polymorphisms on the metabolism of various pharmaceuticals is well known, more data are needed to better understand the specific influence of pharmacogenetics on the metabolism of delta 9-tetrahydocannabinol (Δ9-THC). Therefore, the aim of the study was to analyze the potential impact of variations in genes coding for phase I enzymes of the Δ9-THC metabolism. First, a multiplex assay for genotyping different variants of genes coding for phase I enzymes was developed and applied to 66 Δ9-THC-positive blood samples obtained in cases of driving under the influence of drugs (DUID). Genetic and demographic data as well as plasma concentrations of Δ9-THC, 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-Δ9-THC), and 11-nor-9-carboxy-Δ9-THC (Δ9-THC-COOH) were combined and statistically investigated. For cytochrome P450 2C19 (CYP2C19) variants, no differences in analyzed cannabinoid concentrations were found. There were also no differences in the concentrations of Δ9-THC and 11-OH-Δ9-THC for the different allelic CPY2C9 status. We recognized significantly lower Δ9-THC-COOH concentrations for CYP2C9*3 (p = 0.001) and a trend of lower Δ9-THC-COOH concentrations for CYP2C9*2 which did not reach statistical significance (p = 0.068). In addition, this study showed significantly higher values in the ratio of Δ9-THC/Δ9-THC-COOH for the carriers of the CYP2C9 variants CYP2C9*2 and CYP2C9*3 compared with the carriers of the corresponding wild-type alleles. Therefore, an impact of variations of the CYP2C9 gene on the interpretation of cannabinoid plasma concentrations in DUID cases should be considered.

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

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

Assessing the Implementation of Pharmacogenomic Panel-Testing in Primary Care in the Netherlands Utilizing a Theoretical Framework

Despite overcoming many implementation barriers, pharmacogenomic (PGx) panel-testing is not routine practice in the Netherlands. Therefore, we aim to study pharmacists' perceived enablers and barriers for PGx panel-testing among pharmacists participating in a PGx implementation study. Here, pharmacists identify primary care patients, initiating one of 39 drugs with a Dutch Pharmacogenetic Working Group (DPWG) recommendation and subsequently utilizing the results of a 12 gene PGx panel test to guide dose and drug selection. Pharmacists were invited for a general survey and a semi-structured interview based on the Tailored Implementation for Chronic Diseases (TICD) framework, aiming to identify implementation enablers and barriers, if they had managed at least two patients with actionable PGx results. In total, 15 semi-structured interviews were performed before saturation point was reached. Of these, five barrier themes emerged: (1) unclear procedures, (2) undetermined reimbursement for PGx test and consult, (3) insufficient evidence of clinical utility for PGx panel-testing, (4) infrastructure inefficiencies, and (5) HCP PGx knowledge and awareness; and two enabler themes: (1) pharmacist perceived role in delivering PGx, and (2) believed clinical utility of PGx. Despite a strong belief in the beneficial effects of PGx, pharmacists' barriers remain, an these hinder implementation in primary care.

Integration analysis of metabolites and single nucleotide polymorphisms improves the prediction of drug response of celecoxib

INTRODUCTION

Pharmacogenetics and pharmacometabolomics are the common methods for personalized medicine, either genetic or metabolic biomarkers have limited predictive power for drug response.

OBJECTIVES

In order to better predict drug response, the study attempted to integrate genetic and metabolic biomarkers for drug pharmacokinetics prediction.

METHODS

The study chose celecoxib as study object, the pharmacokinetic behavior of celecoxib was assessed in 48 healthy volunteers based on UPLC-MS/MS platform, and celecoxib related single nucleotide polymorphisms (SNPs) were also detected. Three mathematic models were constructed for celecoxib pharmacokinetics prediction, the first one was mainly based on celecoxib-related SNPs; the second was based on the metabolites selected from a pharmacometabolomic analysis by using GC-MS/MS method, the last model was based on the combination of the celecoxib-related SNPs and metabolites above.

RESULTS

The result proved that the last model showed an improved prediction power, the integration model could explain 71.0% AUC variation and predict 62.3% AUC variation. To facilitate clinical application, ten potential celecoxib-related biomarkers were further screened, which could explain 68.3% and predict 54.6% AUC variation, the predicted AUC was well correlated with the measured values (r = 0.838).

CONCLUSION

This study provides a new route for personalized medicine, the integration of genetic and metabolic biomarkers can predict drug response with a higher accuracy.

Effect of Environmental Exposure and Pharmacogenomics on Drug Metabolism

BACKGROUND

Pesticides are major xenobiotic compounds and environmental pollutants, which are able to alter drug-metabolizing enzyme as well as pharmacokinetics of drugs. Subsequent to the release of the human genome project, genetic variations (polymorphism) become an integral part of drug development due to their influence on disease susceptibility/ progression of the disease and their impact on drug absorption, distribution, metabolism of active metabolites and finally excretion of the drug. Genetic polymorphisms crucially regulate pharmacokinetics and pharmacodynamics of drugs under the influence of physiological condition, lifestyle, as well as pathological conditions collectively.

OBJECTIVE

To review all the evidence concerning the effect of environmental exposure on drug metabolism with reference to pharmacogenomics.

METHODS

Scientific data search and review of basic, epidemiological, pharmacogenomics and pharmacokinetics studies were undertaken to evaluate the influence of environmental contaminants on drug metabolism.

RESULTS

Various environmental contaminants like pesticides effectively alter drug metabolism at various levels under the influence of pharmacogenomics, which interferes with pharmacokinetics of drug metabolism. Genetic polymorphism of phase I and phase II xenobiotic-metabolizing enzymes remarkably alters disease susceptibility as well as the progression of disease under the influence of various environmental contaminants at various levels.

CONCLUSION

Individual specific drug response may be attributed to a large variety of factors alone or in combination ranging from genetic variations (SNP, insertion, deletion, duplication etc.) to physiological setting (gender, age, body size, and ethnicity), environmental or lifestyle factors (radiation exposure, smoking, alcohol, nutrition, exposure to toxins, etc.); and pathological conditions (obesity, diabetes, liver and renal function).

Latent variable mixture modelling and individual treatment prediction

Understanding which groups of patients are more or less likely to benefit from specific treatments has important implications for healthcare. Many personalised medicine approaches in mental health employ variable-centred approaches to predicting treatment response, yet person-centred approaches that identify clinical profiles of patients can provide information on the likelihood of a range of important outcomes. In this paper, we discuss the use of latent variable mixture modelling and demonstrate its use in the application of a patient profiling algorithm using routinely collected patient data to predict outcomes from psychological treatments. This validation study analysed data from two services, which included n = 44,905 patients entering treatment. There were different patterns of reliable recovery, improvement and clinical deterioration from therapy, across the eight profiles which were consistent over time. Outcomes varied between different types of therapy within the profiles: there were significantly higher odds of reliable recovery with High Intensity therapies in two profiles (32.5% of patients) and of reliable improvement in three profiles (32.2% of patients) compared with Low Intensity treatments. In three profiles (37.4% of patients) reliable recovery was significantly more likely if patients had CBT vs Counselling. The developments and potential application of latent variable mixture approaches are further discussed.

GRIN2A -Related Severe Epileptic Encephalopathy Treated with Memantine: An Example of Precision Medicine

Epileptic spasm (ES) is one of the seizure types which is difficult to treat. Next-generation sequencing has facilitated rapid gene discovery that is linked to ES and GRIN2A being one of them. Genotype-driven precision medicine is on the horizon and is a targeted treatment approach toward the precise molecular cause of the disease. GRIN2A gene encodes for a subunit of N-methyl-D-aspartate (NMDA) receptor and it has been suggested from in vitro studies and few case reports that memantine, a NMDA receptor antagonist, was shown to reduce seizures in patients with GRIN2A mutations. Here, we describe a patient with a novel GRIN2A mutation and severe drug-resistant ES who became seizure free with memantine.

Copy number variation profiling in pharmacogenes using panel-based exome resequencing and correlation to human liver expression

Structural variants including copy number variations (CNV) have gained widespread attention, especially in pharmacogenomics but for several genes functional relevance and clinical evidence are still lacking. Detection of CNVs in next-generation sequencing data is challenging but offers widespread applications. We developed a cohort-based CNV detection workflow to extract CNVs from read counts of targeted NGS of 340 genes involved in absorption, distribution, metabolism and excretion (ADME) of drugs. We applied our method to 150 human liver tissue samples and correlated identified CNVs to mRNA expression levels. In total, we identified 445 deletions (73%) and 167 duplications (27%) in 36 pharmacogenes including all well-known CNVs of CYPs, GSTs, SULTs, UGTs, numerous described rare CNVs of CYP2E1, SLC16A3 or UGT2B15 as well as novel observations, e.g., for SLC22A12, SLC22A17 and GPS2 (G Protein Pathway Suppressor 2). We were able to fine-map complex CNVs of CYP2A6 and CYP2D6 with exon resolution. Correlation analysis confirmed known expression patterns for common CNVs and suggested an influence on expression variability for some rare CNVs. Our straightforward CNV detection workflow can be easily applied to any NGS coverage data and helped to analyze CNVs in an ADME-NGS panel of 340 pharmacogenes to improve genotype-phenotype correlations.

Towards precision medicine: interrogating the human genome to identify drug pathways associated with potentially functional, population-differentiated polymorphisms

Drug response variations amongst different individuals/populations are influenced by several factors including allele frequency differences of single nucleotide polymorphisms (SNPs) that functionally affect drug-response genes. Here, we aim to identify drugs that potentially exhibit population differences in response using SNP data mining and analytics. Ninety-one pairwise-comparisons of >22,000,000 SNPs from the 1000 Genomes Project, across 14 different populations, were performed to identify ‘population-differentiated’ SNPs (pdSNPs). Potentially-functional pdSNPs (pf-pdSNPs) were then selected, mapped into genes, and integrated with drug–gene databases to identify ‘population-differentiated’ drugs enriched with genes carrying pf-pdSNPs. 1191 clinically-approved drugs were found to be significantly enriched (Z > 2.58) with genes carrying SNPs that were differentiated in one or more population-pair comparisons. Thirteen drugs were found to be enriched with such differentiated genes across all 91 population-pairs. Notably, 82% of drugs, which were previously reported in the literature to exhibit population differences in response were also found by this method to contain a significant enrichment of population specific differentiated SNPs. Furthermore, drugs with genetic testing labels, or those suspected to cause adverse reactions, contained a significantly larger number (P < 0.01) of population-pairs with enriched pf-pdSNPs compared with those without these labels. This pioneering effort at harnessing big-data pharmacogenomics to identify ‘population differentiated’ drugs could help to facilitate data-driven decision-making for a more personalized medicine.

Opportunities and Challenges in Cardiovascular Pharmacogenomics: From Discovery to Implementation

This review will provide an overview of the principles of pharmacogenomics from basic discovery to implementation, encompassing application of tools of contemporary genome science to the field (including areas of apparent divergence from disease-based genomics), a summary of lessons learned from the extensively studied drugs clopidogrel and warfarin, the current status of implementing pharmacogenetic testing in practice, the role of genomics and related tools in the drug development process, and a summary of future opportunities and challenges.