Pharmacogenomics and patient care: one size does not fit all

Trend of pharmaceuticals 3D printing in the Middle East and North Africa (MENA) region: An overview, regulatory perspective and future outlook

The traditional method of producing medicine using the "one-size fits all" model is becoming a major issue for pharmaceutical manufacturers due to its inability to produce customizable medicines for individuals' needs. Three-dimensional (3D) printing is a new disruptive technology that offers many benefits to the pharmaceutical industry by revolutionizing the way pharmaceuticals are developed and manufactured. 3D printing technology enables the on-demand production of personalized medicine with tailored dosage, shape and release characteristics. Despite the lack of clear regulatory guidance, there is substantial interest in adopting 3D printing technology in the large-scale manufacturing of medicine. This review aims to evaluate the research efforts of 3D printing technology in the Middle East and North Africa (MENA) region, with a particular emphasis on pharmaceutical research and development. Our analysis indicates an upsurge in the overall research activity of 3D printing technology but there is limited progress in pharmaceuticals research and development. While the MENA region still lags, there is evidence of the regional interest in expanding the 3D printing technology applications in different sectors including pharmaceuticals. 3D printing holds great promise for pharmaceutical development within the MENA region and its advancement will require a strong collaboration between academic researchers and industry partners in parallel with drafting detailed guidelines from regulatory authorities.

Deciphering genetic causes for sex differences in human health through drug metabolism and transporter genes

Sex differences have been widely observed in human health. However, little is known about the underlying mechanism behind these observed sex differences. We hypothesize that sex-differentiated genetic effects are contributors of these phenotypic differences. Focusing on a collection of drug metabolism enzymes and transporters (DMET) genes, we discover sex-differentiated genetic regulatory mechanisms between these genes and human complex traits. Here, we show that sex-differentiated genetic effects were present at genome-level and at DMET gene regions for many human complex traits. These sex-differentiated regulatory mechanisms are reflected in the levels of gene expression and endogenous serum biomarkers. Through Mendelian Randomization analysis, we identify putative sex-differentiated causal effects in each sex separately. Furthermore, we identify and validate sex differential gene expression of a subset of DMET genes in human liver samples. We observe higher protein abundance and enzyme activity of CYP1A2 in male-derived liver microsomes, which leads to higher level of an active metabolite formation of clozapine, a commonly prescribed antipsychotic drug. Taken together, our results demonstrate the presence of sex-differentiated genetic effects on DMET gene regulation, which manifest in various phenotypic traits including disease risks and drug responses.

The role of OATP1B1 and OATP1B3 transporter polymorphisms in drug disposition and response to anticancer drugs: a review of the recent literature

INTRODUCTION

Members of the solute carrier family of organic anion transporting polypeptides are responsible for the cellular uptake of a broad range of endogenous compounds and xenobiotics in multiple tissues. In particular, the polymorphic transporters OATP1B1 and OATP1B3 are highly expressed in the liver and have been identified as critical regulators of hepatic eliminaton. As these transporters are also expressed in cancer cells, the function alteration of these proteins have important consequences for an individual's susceptibility to certain drug-induced side effects, drug-drug interactions, and treatment efficacy.

AREAS COVERED

In this mini-review, we provide an update of this rapidly emerging field, with specific emphasis on the direct contribution of genetic variants in OATP1B1 and OATP1B3 to the transport of anticancer drugs, the role of these carriers in regulation of their disposition and toxicity profiles, and recent advances in attempts to integrate information on transport function in patients to derive individualized treatment strategies.

EXPERT OPINION

Based on currently available data, it appears imperative that different aspects of disease, physiology, and drugs of relevance should be evaluated along with an individual's genetic signature, and that tools such as biomarker levels can be implemented to achieve the most reliable prediction of clinically relevant pharmacodynamic endpoints.

Recent Advances in Cancer Drug Discovery Through the Use of Phenotypic Reporter Systems, Connectivity Mapping, and Pooled CRISPR Screening

Multi-omic approaches offer an unprecedented overview of the development, plasticity, and resistance of cancer. However, the translation from anti-cancer compounds identified in vitro to clinically active drugs have a notoriously low success rate. Here, we review how technical advances in cell culture, robotics, computational biology, and development of reporter systems have transformed drug discovery, enabling screening approaches tailored to clinically relevant functional readouts (e.g., bypassing drug resistance). Illustrating with selected examples of “success stories,” we describe the process of phenotype-based high-throughput drug screening to target malignant cells or the immune system. Second, we describe computational approaches that link transcriptomic profiling of cancers with existing pharmaceutical compounds to accelerate drug repurposing. Finally, we review how CRISPR-based screening can be applied for the discovery of mechanisms of drug resistance and sensitization. Overall, we explore how the complementary strengths of each of these approaches allow them to transform the paradigm of pre-clinical drug development.

In Vitro and In Vivo Inhibition of MATE1 by Tyrosine Kinase Inhibitors

The membrane transport of many cationic prescription drugs depends on facilitated transport by organic cation transporters of which several members, including OCT2 (SLC22A2), are sensitive to inhibition by select tyrosine kinase inhibitors (TKIs). We hypothesized that TKIs may differentially interact with the renal transporter MATE1 (SLC47A1) and influence the elimination and toxicity of the MATE1 substrate oxaliplatin. Interactions with FDA-approved TKIs were evaluated in transfected HEK293 cells, and in vivo pharmacokinetic studies were performed in wild-type, MATE1-deficient, and OCT2/MATE1-deficient mice. Of 57 TKIs evaluated, 37 potently inhibited MATE1 function by >80% through a non-competitive, reversible, substrate-independent mechanism. The urinary excretion of oxaliplatin was reduced by about 2-fold in mice with a deficiency of MATE1 or both OCT2 and MATE1 (p < 0.05), without impacting markers of acute renal injury. In addition, genetic or pharmacological inhibition of MATE1 did not significantly alter plasma levels of oxaliplatin, suggesting that MATE1 inhibitors are unlikely to influence the safety or drug-drug interaction liability of oxaliplatin-based chemotherapy.

Navigating Multi-Scale Cancer Systems Biology Towards Model-Driven Clinical Oncology and Its Applications in Personalized Therapeutics

Rapid advancements in high-throughput omics technologies and experimental protocols have led to the generation of vast amounts of scale-specific biomolecular data on cancer that now populates several online databases and resources. Cancer systems biology models built using this data have the potential to provide specific insights into complex multifactorial aberrations underpinning tumor initiation, development, and metastasis. Furthermore, the annotation of these single- and multi-scale models with patient data can additionally assist in designing personalized therapeutic interventions as well as aid in clinical decision-making. Here, we have systematically reviewed the emergence and evolution of (i) repositories with scale-specific and multi-scale biomolecular cancer data, (ii) systems biology models developed using this data, (iii) associated simulation software for the development of personalized cancer therapeutics, and (iv) translational attempts to pipeline multi-scale panomics data for data-driven in silico clinical oncology. The review concludes that the absence of a generic, zero-code, panomics-based multi-scale modeling pipeline and associated software framework, impedes the development and seamless deployment of personalized in silico multi-scale models in clinical settings.

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.

Pharmacokinetics of Tenofovir Alafenamide Fumarate and Tenofovir in the Chinese People: Effects of Non-Genetic Factors and Genetic Variations

Background

Tenofovir alafenamide fumarate (TAF) was approved for HBV treatment in China in 2018. Despite higher antiviral efficacy and less impact on renal function and bone mineral density, the pharmacokinetic profiles of TAF are highly variable. The objectives of this study were to investigate the pharmacokinetics of TAF in the Chinese population and explore the associations between TAF and genetic polymorphisms and non-genetic factors.

Patients and Methods

A total of 64 healthy Chinese subjects aged 18~65 years old were planned to enroll. According to the dietary intake status, the subjects were divided into two groups (n = 32 per group). The concentrations of TAF and tenofovir were measured by HPLC-MS/MS, and the single-nucleotide polymorphisms were analyzed by MALDI-TOF MS.

Results

All the enrolled participants (18–35 years) completed the clinical trial study. Similar to the results reported in other ethnic populations, the pharmacokinetic profiles of TAF and tenofovir were highly variable in the Chinese people, and the HFHC diet can significantly increase the systemic exposure of TAF. We determined both HFHC diet and rs7311358 (SLCO1B3) genotypes were independently associated with TAF AUC_0-t, while HFHC diet, age and rs3740066 (ABCC2) variants were predictive of t_1/2 of tenofovir (P < 0.05). The subjects with the AA genotype in rs7311358 had significantly higher TAF AUC_0-t values (1.15 times) than those with a G allele, and the t_1/2 of tenofovir in the rs3740066 TT genotype group was 1.23 times longer than that of CC genotype group. Furthermore, there was a trend of higher TAF AUC and shorter tenofovir t_1/2 for the rs2032582 (ABCB1) T allele and rs3742106 (ABCC4) CC variant, respectively, although not statistically significant in the multiple linear regression analysis.

Conclusion

This study provided new evidence to suggest a critical link between both genetic and non-genetic factors and TAF pharmacokinetics in the Chinese people.

Inter-Individual Variation and Cardioprotection in Anthracycline-Induced Heart Failure

Anthracyclines are one of the most widely used and effective chemotherapies in oncology, but their most important side effect is the cumulative, dose-related cardiotoxicity leading to congestive heart failure in ~5% of individuals. Methodology and pharmacogenetic studies for predicting which individuals are at high risk and subsequently the development of targeted and individualized cardioprotective plans are beginning to make progress. Here, we review current putative risk genes and variants, the strength of evidence for each genetic association and the interaction between risk genes, in the context of known clinical risk factors and potential novel cardioprotective strategies.

Implementing Pharmacogenomics Testing: Single Center Experience at Arkansas Children's Hospital

Pharmacogenomics (PGx) is a growing field within precision medicine. Testing can help predict adverse events and sub-therapeutic response risks of certain medications. To date, the US FDA lists over 280 drugs which provide biomarker-based dosing guidance for adults and children. At Arkansas Children’s Hospital (ACH), a clinical PGx laboratory-based test was developed and implemented to provide guidance on 66 pediatric medications for genotype-guided dosing. This PGx test consists of 174 single nucleotide polymorphisms (SNPs) targeting 23 clinically actionable PGx genes or gene variants. Individual genotypes are processed to provide per-gene discrete results in star-allele and phenotype format. These results are then integrated into EPIC- EHR. Genomic indicators built into EPIC-EHR provide the source for clinical decision support (CDS) for clinicians, providing genotype-guided dosing.

Influence of YES1 Kinase and Tyrosine Phosphorylation on the Activity of OCT1

Organic cation transporter 1 (OCT1) is a transporter that regulates the hepatic uptake and subsequent elimination of diverse cationic compounds. Although OCT1 has been involved in drug-drug interactions and causes pharmacokinetic variability of many prescription drugs, details of the molecular mechanisms that regulate the activity of OCT1 remain incompletely understood. Based on an unbiased phospho-proteomics screen, we identified OCT1 as a tyrosine-phosphorylated transporter, and functional validation studies using genetic and pharmacological approaches revealed that OCT1 is highly sensitive to small molecules that target the protein kinase YES1, such as dasatinib. In addition, we found that dasatinib can inhibit hepatic OCT1 function in mice as evidenced from its ability to modulate levels of isobutyryl L-carnitine, a hepatic OCT1 biomarker identified from a targeted metabolomics analysis. These findings provide novel insight into the post-translational regulation of OCT1 and suggest that caution is warranted with polypharmacy regimes involving the combined use of OCT1 substrates and kinase inhibitors that target YES1.

Model-Informed Precision Dosing: Background, Requirements, Validation, Implementation, and Forward Trajectory of Individualizing Drug Therapy

Model-informed precision dosing (MIPD) has become synonymous with modern approaches for individualizing drug therapy, in which the characteristics of each patient are considered as opposed to applying a one-size-fits-all alternative. This review provides a brief account of the current knowledge, practices, and opinions on MIPD while defining an achievable vision for MIPD in clinical care based on available evidence. We begin with a historical perspective on variability in dose requirements and then discuss technical aspects of MIPD, including the need for clinical decision support tools, practical validation, and implementation of MIPD in health care. We also discuss novel ways to characterize patient variability beyond the common perceptions of genetic control. Finally, we address current debates on MIPD from the perspectives of the new drug development, health economics, and drug regulations.

Being Precise About Precision Medicine: What Should Value Frameworks Incorporate to Address Precision Medicine? A Report of the Personalized Precision Medicine Special Interest Group

Precision medicine is a dynamic area embracing a diverse and increasing type of approaches that allow the targeting of new medicines, screening programs or preventive healthcare strategies, which include the use of biologic markers or complex tests driven by algorithms also potentially taking account of patient preferences. The International Society for Pharmacoeconomics and Outcome Research expanded its current work around precision medicine to (1) describe the evolving paradigm of precision medicine with examples of current and evolving applications, (2) describe key stakeholders perspectives on the value of precision medicine in their respective domains, and (3) define the core factors that should be considered in a value assessment framework for precision medicine. With the ultimate goal of improving health of well-defined patient groups, precision medicine will affect all stakeholders in the healthcare system at multiple levels spanning the individual perspective to the societal perspective. For an efficient, timely and practical precision medicine value assessment framework, it will be important to address these multiple perspectives through building consensus among the stakeholders for robust procedures and measures of value aspects, including performance of precision mechanism; aligned reimbursement processes of precision mechanism and subsequent treatment; transparent expectations for evidence requirements and study designs adequately matched to the intended use of the precision mechanism and to the smaller target patient populations; recognizing the potential range of value-generation such as ruling-in and ruling-out decisions.

Variant discovery using next-generation sequencing and its future role in pharmacogenetics

Next-generation sequencing (NGS) has enabled the discovery of a multitude of novel and mostly rare variants in pharmacogenes that may alter a patient’s therapeutic response to drugs. In addition to single nucleotide variants, structural variation affecting the number of copies of whole genes or parts of genes can be detected. While current guidelines concerning clinical implementation mostly act upon well-documented, common single nucleotide variants to guide dosing or drug selection, in silico and large-scale functional assessment of rare variant effects on protein function are at the forefront of pharmacogenetic research to facilitate their clinical integration. Here, we discuss the role of NGS in variant discovery, paving the way for more comprehensive genotype-guided pharmacotherapy that can translate to improved clinical care.

Sequential third-year medical student quality assurance (QA) clerkship projects appear to introduce a culture of continuous quality improvement across New Jersey family medicine practices

Background

In recent years, Rutgers New Jersey Medical School Department of Family Medicine has integrated a quality assurance (QA) project as a required component of their 5-week medical student clerkship. This project requires each student to conduct a QA study at an assigned family practice and discuss the results with their preceptor. The aim of this study was to determine if sequential medical student QA projects impact physician readiness to improve guideline adherence over time.

Methods

A retrospective analysis of student reports was conducted to determine if physician readiness to improve compliance improved post implementation of the QA project using James Prochaska’s Transtheoretical Model of Behavioral Change. Fisher’s exact test or the χ² test were used as applicable to compare the change in results.

Results

In academic year 2015–2016, there were 11 (6%) instances where physicians were precontemplating on change, 43 (24%) instances where physicians were contemplating, 101 (57%) instances where physicians were preparing to make change, 18 (10%) instances where physicians were acting, and 4 (2%) of instances where a physician were maintaining previous changes. The following year, the numbers were: 15 (8%), 38 (21%), 82 (46%), 34 (19%) and 11 (6%), respectively. There were increases of physicians in stages of precontemplation (p=0.047), action (p=0.02) and maintenance (p=0.047), a decrease in physicians that were in the stage of preparation (p=0.05) and no significant change in the instances they were in a stage of contemplation (p=0.60).

Conclusion

Student QA projects appear to leverage physician readiness to improve guideline adherence. Future studies will determine if raising awareness through these clerkship projects results in practice behavioural change.

Solute Carrier Transportome in Chemotherapy-Induced Adverse Drug Reactions

Members of the solute carrier (SLC) family of transporters are responsible for the cellular influx of a broad range of endogenous compounds and xenobiotics. These proteins are highly expressed in the gastrointestinal tract and eliminating organs such as the liver and kidney, and are considered to be of particular importance in governing drug absorption and elimination. Many of the same transporters are also expressed in a wide variety of organs targeted by clinically important anticancer drugs, directly affect cellular sensitivity to these agents, and indirectly influence treatment-related side effects. Furthermore, targeted intervention strategies involving the use of transport inhibitors have been recently developed, and have provided promising lead candidates for combinatorial therapies associated with decreased toxicity. Gaining a better understanding of the complex interplay between transporter-mediated on-target and off-target drug disposition will help guide the further development of these novel treatment strategies to prevent drug accumulation in toxicity-associated organs, and improve the safety of currently available treatment modalities. In this report, we provide an update on this rapidly emerging field with particular emphasis on anticancer drugs belonging to the classes of taxanes, platinum derivatives, nucleoside analogs, and anthracyclines.

[The design of the software system for the interpretation and guidance of drug locus related to drug treatment]

Based on the pharmacogenomics theory, this study developed a software system for interpretation of drug gene loci and guidance on clinical safe medication with the purpose of providing clinical guidance on the safety and effectiveness of drug use through accurate and efficient detection and interpretation of drug gene loci. The system infrastructure was built on a service-oriented architecture (SOA) design and Docker container virtualization approach to achieve a rapid and automatic interpretation of genetic results and best available drugs. The front end was established on HTML5 and JavaScript to realize visualization of analysis results and user interaction. The system was tested and validated to show robust performance which is reliable in clinical use. It will show high impact on the development of pharmacogenomics and clinical practice of patients with personalized medicine.

Whole genome sequencing identifies high-impact variants in well-known pharmacogenomic genes

More than 1100 genetic loci have been correlated with drug response outcomes but disproportionately few have been translated into clinical practice. One explanation for the low rate of clinical implementation is that the majority of associated variants may be in linkage disequilibrium (LD) with the causal variants, which are often elusive. This study aims to identify and characterize likely causal variants within well-established pharmacogenomic genes using next-generation sequencing data from the 1000 Genomes Project. We identified 69,319 genetic variations within 160 pharmacogenomic genes, of which 8207 variants are in strong LD (r2>0.8) with known pharmacogenomic variants. Of the latter, eight are coding or structural variants predicted to have high impact, with 19 additional missense variants that are predicted to have moderate impact. In conclusion, we identified putatively functional variants within known pharmacogenomics loci that could account for the association signals and represent the missing causative variants underlying drug response phenotypes.

Genomic Interventions in Medicine

Lately, the term "genomics" has become ubiquitous in many scientific articles. It is a rapidly growing aspect of the biomedical sciences that studies the genome. The human genome contains a torrent of information that gives clues about human origin, evolution, biological function, and diseases. In a bid to demystify the workings of the genome, the Human Genome Project (HGP) was initiated in 1990, with the chief goal of sequencing the approximately 3 billion nucleotide base pairs of the human DNA. Since its completion in 2003, the HGP has opened new avenues for the application of genomics in clinical practice. This review attempts to overview some milestone discoveries that paved way for the initiation of the HGP, remarkable revelations from the HGP, and how genomics is influencing a paradigm shift in routine clinical practice. It further highlights the challenges facing the implementation of genomic medicine, particularly in Africa. Possible solutions are also discussed.

Pharmacogenomics: Precision Medicine and Drug Response

Pharmacogenomics is the use of genomic and other "omic" information to individualize drug selection and drug use to avoid adverse drug reactions and to maximize drug efficacy. The science underlying pharmacogenomics has evolved rapidly over the 50 years since it was first suggested that genetics might influence drug response phenotypes. That process has occurred in parallel with advances in DNA sequencing and other molecular technologies, with striking increases in our understanding of the human genome. There are now many validated examples of the clinical utility of pharmacogenomics, and this type of clinical genomic information is increasingly being generated in clinical laboratories, incorporated into electronic health records, and used to "tailor" or individualize drug therapy. This review will survey the origins and development of pharmacogenomics; it will address some of the challenges associated with the clinical implementation of pharmacogenomics; and it will attempt to foresee future advances in this important genomic discipline, one that almost certainly will be among the earliest and most widely adopted aspects of clinical genomics.

Within and beyond the communal turn to informed consent in industry-sponsored pharmacogenetics research: merits and challenges of community advisory boards

The one-size-fits-all paradigm of drug development fails to address inter-individual variability in drug response. Pharmacogenetics research aims at studying the role of genotypic differences in drug response. Recently, the pharmaceutical industry has shown interest to embed pharmacogenetics studies in the process of drug development. Nevertheless, population-based and commercial aspects of such future-oriented studies pose challenges for individually based informed consent (IC). As an exemplar of the communal turn to IC procedures, community advisory boards (CABs) have been integrated into different types of medical research. CABs hold the promise of organizing the relationship between participants and researchers in a more reciprocal and participatory way, offering possible means of overcoming the lapses of individualistic IC. However, the involvement of CABs with pharmacogenetics research might be rife with difficulties, uncertainties, and challenges. The current study first reviews the existing literature to discuss added values and challenges of relying on CABs as a supplement to individually based IC. Then, the particular moral and regulatory landscape of pharmacogenetics research will be delineated to argue that community engagement is both necessary and promising beyond the communal turn to IC processes. Three main features of the landscape include (1) new supportive stances that some regulatory bodies have adopted toward pharmacogenetics research, (2) the motivation of the industry to draw reception and trust from the subpopulations, and (3) the important role of the society in generating and embedding pharmacogenetics knowledge. Finally, some points to consider will be discussed to contextualize relying on CABs within this landscape.

Monoclonal antibodies for treating gastric cancer: promises and pitfalls

INTRODUCTION

Gastric cancer (GC) presents dismal prognosis when diagnosed at advanced stages, standard chemotherapy having shown little efficacy. Introduction of biotherapies interfering with novel targets and signaling pathways is currently an emerging strategy.

AREAS COVERED

Only two monoclonal antibodies (trastuzumab and ramucirumab) have been approved, mostly in association with cytotoxics. Conversely, testing other promising biotherapies (panitumumab, cetuximab, bevacizumab, rilotumumab) have yielded conflicting results, since encouraging early clinical trials have failed to be confirmed in larger phase-III studies. Empirical and underpowered strategies when designing combinational studies, lack of comprehensive knowledge of pharmacokinetics/pharmacodynamics (PK/PD) relationships, and underestimation of the large inter-patient variability in drug exposure levels with monoclonal antibodies, could explain the failures in developing biotherapies in gastric cancer. This review covers the achievements and limits of monoclonal antibodies in gastric cancer and proposes clues to overcome current failures.

EXPERT OPINION

Trastuzumab efficacy could be improved thanks to its combination with triplet chemotherapy or with another anti-HER2 agents or in continuation during second-line chemotherapy. Concerning ramucirumab, further studies are necessary to prove its interest in first line treatment of advanced GC, to use the optimal dose in each patient-given the large inter-patients variability, and to find predictive biomarkers of efficacy.

A phosphotyrosine switch regulates organic cation transporters

Membrane transporters are key determinants of therapeutic outcomes. They regulate systemic and cellular drug levels influencing efficacy as well as toxicities. Here we report a unique phosphorylation-dependent interaction between drug transporters and tyrosine kinase inhibitors (TKIs), which has uncovered widespread phosphotyrosine-mediated regulation of drug transporters. We initially found that organic cation transporters (OCTs), uptake carriers of metformin and oxaliplatin, were inhibited by several clinically used TKIs. Mechanistic studies showed that these TKIs inhibit the Src family kinase Yes1, which was found to be essential for OCT2 tyrosine phosphorylation and function. Yes1 inhibition in vivo diminished OCT2 activity, significantly mitigating oxaliplatin-induced acute sensory neuropathy. Along with OCT2, other SLC-family drug transporters are potentially part of an extensive 'transporter-phosphoproteome' with unique susceptibility to TKIs. On the basis of these findings we propose that TKIs, an important and rapidly expanding class of therapeutics, can functionally modulate pharmacologically important proteins by inhibiting protein kinases essential for their post-translational regulation.

Determination of genotypes using a fully automated molecular detection system

CONTEXT

Although the value of pharmacogenomics to improve patient outcomes has become increasingly clear, adoption in medical practice has been slow, which can be attributed to several factors, including complicated and expensive testing procedures and required equipment, lack of training by private practice physicians, and reluctance of both private and commercial payers to reimburse for such testing.

OBJECTIVES

To evaluate a fully automated molecular detection system for human genotyping assays, starting with anticoagulated whole blood samples, and to perform all sample preparation, assay, and analysis steps automatically with actionable results reported by the system's software.

DESIGN

The genotypes of 254 random individuals were determined by performing bidirectional DNA sequencing, and that information was used to statistically train the imaging software of the automated molecular detection system to distinguish the 3 possible genotypes (ie, homozygous wild type, heterozygous, and homozygous mutant) at each of 3 different loci (CYP2C9*2, CYP2C9*3, and VKORC1).

RESULTS

The resulting software algorithm was able to correctly identify the genotypes of all 254 individuals (100%) evaluated without any further user analysis.

CONCLUSIONS

The EncompassMDx workstation (Rheonix, Inc, Ithaca, New York) is a molecular detection system that can automatically determine the genotypes of individuals in an unattended manner. Considerably less technical expertise was required to achieve results identical to those obtained using more complex, time-consuming, and expensive bidirectional DNA sequencing. This optimized system may dramatically simplify and reduce the costs of pharmacogenomics testing, thus leading to more-widespread use.

Using quantitative systems pharmacology for novel drug discovery

INTRODUCTION

Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology.

AREAS COVERED

This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects.

EXPERT OPINION

The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.

Pharmacogenomic variants have larger effect sizes than genetic variants associated with other dichotomous complex traits

It has been suggested that pharmacogenomic phenotypes are influenced by genetic variants with larger effect sizes than other phenotypes, such as complex disease risk. This is presumed to reflect the fact that relevant environmental factors (drug exposure) are appropriately measured and taken into account. To test this hypothesis, we performed a systematic comparison of effect sizes between pharmacogenomic and non-pharmacogenomic phenotypes across all genome-wide association studies (GWAS) reported in the NHGRI GWAS catalog. We found significantly larger effect sizes for studies focused on pharmacogenomic phenotypes, as compared to complex disease risk, morphological phenotypes, and endophenotypes. We found no significant differences in effect sizes between pharmacogenomic studies focused on adverse events versus those focused on drug efficacy. Furthermore, we found that this pattern persists among sample size-matched studies, suggesting that this pattern does not reflect over-estimation of effect sizes due to smaller sample sizes in pharmacogenomic studies.

Inherited NUDT15 variant is a genetic determinant of mercaptopurine intolerance in children with acute lymphoblastic leukemia

PURPOSE

Mercaptopurine (MP) is the mainstay of curative therapy for acute lymphoblastic leukemia (ALL). We performed a genome-wide association study (GWAS) to identify comprehensively the genetic basis of MP intolerance in children with ALL.

PATIENTS AND METHODS

The discovery GWAS and replication cohorts included 657 and 371 children from two prospective clinical trials. MP dose intensity was a marker for drug tolerance and toxicities and was defined as prescribed dose divided by the planned protocol dose during maintenance therapy; its association with genotype was evaluated using a linear mixed-effects model.

RESULTS

MP dose intensity varied by race and ethnicity and was negatively correlated with East Asian genetic ancestry (P < .001). The GWAS revealed two genome-wide significant loci associated with dose intensity: rs1142345 in TPMT (Tyr240Cys, present in *3A and *3C variants; P = 8.6 × 10(-9)) and rs116855232 in NUDT15 (P = 8.8 × 10(-9)), with independent replication. Patients with TT genotype at rs116855232 were exquisitely sensitive to MP, with an average dose intensity of 8.3%, compared with those with TC and CC genotypes, who tolerated 63% and 83.5% of the planned dose, respectively. The NUDT15 variant was most common in East Asians and Hispanics, rare in Europeans, and not observed in Africans, contributing to ancestry-related differences in MP tolerance. Of children homozygous for either TPMT or NUDT15 variants or heterozygous for both, 100% required ≥ 50% MP dose reduction, compared with only 7.7% of others.

CONCLUSION

We describe a germline variant in NUDT15 strongly associated with MP intolerance in childhood ALL, which may have implications for treatment individualization in this disease.

Genomics and Pharmacogenomics of Salt-sensitive Hypertension

Salt sensitivity is estimated to be present in 51% of the hypertensive and 26% of the normotensive populations. The individual blood pressure response to salt is heterogeneous and possibly related to inherited susceptibility. Although the mechanisms underlying salt sensitivity are complex and not well understood, genetics can help to determine the blood response to salt intake. So far only a few genes have been found to be associated with salt-sensitive hypertension using candidate gene association studies. The kidney is critical to overall fluid and electrolyte balance and long-term regulation of blood pressure. Thus, the pathogenesis of salt sensitivity must involve a derangement in renal NaCl handling: an inability to decrease renal sodium transport and increase sodium excretion in the face of an increase in NaCl load that could be caused by aberrant counter-regulatory natriuretic/antinatriuretic pathways. We review here the literature regarding the gene variants associated with salt-sensitive hypertension and how the presence of these gene variants influences the response to antihypertensive therapy.

Genomics and pharmacogenomics of salt-sensitive hypertension Minireview

Salt sensitivity is estimated to be present in 51% of the hypertensive and 26% of the normotensive populations. The individual blood pressure response to salt is heterogeneous and possibly related to inherited susceptibility. Although the mechanisms underlying salt sensitivity are complex and not well understood, genetics can help to determine the blood response to salt intake. So far only a few genes have been found to be associated with salt-sensitive hypertension using candidate gene association studies. The kidney is critical to overall fluid and electrolyte balance and long-term regulation of blood pressure. Thus, the pathogenesis of salt sensitivity must involve a derangement in renal NaCl handling: an inability to decrease renal sodium transport and increase sodium excretion in the face of an increase in NaCl load that could be caused by aberrant counter-regulatory natriuretic/antinatriuretic pathways. We review here the literature regarding the gene variants associated with salt-sensitive hypertension and how the presence of these gene variants influences the response to antihypertensive therapy.

How drugs get into cells: tested and testable predictions to help discriminate between transporter-mediated uptake and lipoidal bilayer diffusion

One approach to experimental science involves creating hypotheses, then testing them by varying one or more independent variables, and assessing the effects of this variation on the processes of interest. We use this strategy to compare the intellectual status and available evidence for two models or views of mechanisms of transmembrane drug transport into intact biological cells. One (BDII) asserts that lipoidal phospholipid Bilayer Diffusion Is Important, while a second (PBIN) proposes that in normal intact cells Phospholipid Bilayer diffusion Is Negligible (i.e., may be neglected quantitatively), because evolution selected against it, and with transmembrane drug transport being effected by genetically encoded proteinaceous carriers or pores, whose “natural” biological roles, and substrates are based in intermediary metabolism. Despite a recent review elsewhere, we can find no evidence able to support BDII as we can find no experiments in intact cells in which phospholipid bilayer diffusion was either varied independently or measured directly (although there are many papers where it was inferred by seeing a covariation of other dependent variables). By contrast, we find an abundance of evidence showing cases in which changes in the activities of named and genetically identified transporters led to measurable changes in the rate or extent of drug uptake. PBIN also has considerable predictive power, and accounts readily for the large differences in drug uptake between tissues, cells and species, in accounting for the metabolite-likeness of marketed drugs, in pharmacogenomics, and in providing a straightforward explanation for the late-stage appearance of toxicity and of lack of efficacy during drug discovery programmes despite macroscopically adequate pharmacokinetics. Consequently, the view that Phospholipid Bilayer diffusion Is Negligible (PBIN) provides a starting hypothesis for assessing cellular drug uptake that is much better supported by the available evidence, and is both more productive and more predictive.

Expression quantitative trait analyses to identify causal genetic variants for type 2 diabetes susceptibility

Type 2 diabetes (T2D) is a common metabolic disorder which is caused by multiple genetic perturbations affecting different biological pathways. Identifying genetic factors modulating the susceptibility of this complex heterogeneous metabolic phenotype in different ethnic and racial groups remains challenging. Despite recent success, the functional role of the T2D susceptibility variants implicated by genome-wide association studies (GWAS) remains largely unknown. Genetic dissection of transcript abundance or expression quantitative trait (eQTL) analysis unravels the genomic architecture of regulatory variants. Availability of eQTL information from tissues relevant for glucose homeostasis in humans opens a new avenue to prioritize GWAS-implicated variants that may be involved in triggering a causal chain of events leading to T2D. In this article, we review the progress made in the field of eQTL research and knowledge gained from those studies in understanding transcription regulatory mechanisms in human subjects. We highlight several novel approaches that can integrate eQTL analysis with multiple layers of biological information to identify ethnic-specific causal variants and gene-environment interactions relevant to T2D pathogenesis. Finally, we discuss how the eQTL analysis mediated search for “missing heritability” may lead us to novel biological and molecular mechanisms involved in susceptibility to T2D.

Cytochrome P450 pharmacogenetics in African populations: implications for public health

INTRODUCTION

Africa harbors a disproportionate burden of disease when taking into account the triple challenge caused by HIV/AIDS, tuberculosis (TB) and malaria, against a backdrop of an increasing burden of noncommunicable diseases. More than 80% of therapeutic drugs used in the management of these diseases/conditions are metabolized by CYP enzymes that exhibit genetic polymorphisms.

AREAS COVERED

There is variability in the expression and activities of CYPs resulting in interindividual differences in the response to standard doses of therapeutic drugs, due to genetic polymorphisms, which exhibit both quantitative and qualitative differences between racial and between ethnic groups. The review aims to evaluate the implications of the genetic variation in CYPs on the public health of Africans. The CYPs reviewed here metabolize most of the commonly used therapeutic drugs and include CYP1A2, 2A6, 2B6, 2C8, 2C9, 2C19, 2D6, 3A4 and 3A5. Allele frequencies are compared between African ethnic groups and among populations of African, Asian and European origin. Data are obtained from our own studies and literature.

EXPERT OPINION

The variability in the pattern of genetic variation between populations translates into differences in drug response. Understanding CYP variability improves rational drug use and has public health significance.

Pharmacogenomics in early-phase clinical development

Pharmacogenomics (PGx) offers the promise of utilizing genetic fingerprints to predict individual responses to drugs in terms of safety, efficacy and pharmacokinetics. Early-phase clinical trial PGx applications can identify human genome variations that are meaningful to study design, selection of participants, allocation of resources and clinical research ethics. Results can inform later-phase study design and pipeline developmental decisions. Nevertheless, our review of the clinicaltrials.gov database demonstrates that PGx is rarely used by drug developers. Of the total 323 trials that included PGx as an outcome, 80% have been conducted by academic institutions after initial regulatory approval. Barriers for the application of PGx are discussed. We propose a framework for the role of PGx in early-phase drug development and recommend PGx be universally considered in study design, result interpretation and hypothesis generation for later-phase studies, but PGx results from underpowered studies should not be used by themselves to terminate drug-development programs.

Pharmacogenetics in the cancer clinic: from candidate gene studies to next-generation sequencing

Genetics has significantly added to our understanding of variability in drug response, especially in cancer treatment. Pharmacogenetics, aimed at predicting a patient's chance for effective and safe drug treatment by interrogating germ line genetic variants, has moved from investigating a monogenetic candidate gene to examining complex phenotype-based genome-wide approaches. With the rapid advances in sequencing technologies, decline in costs, and swift turnaround times, large-scale genomic information will become available in the clinical setting, facilitating implementation of pharmacogenetics.

Efficacy versus safety concerns for aerosol chemotherapy in non-small-cell lung cancer: a future dilemma for micro-oncology

Inhaled chemotherapy was first used more than 30 years ago. Since then, numerous chemotherapeutic agents have been used in either in vitro or in vivo studies. Several aspects of the methodology of the drug administration have been thoroughly demonstrated and explained. However, the safety concerns of these studies were not thoroughly investigated and different results regarding the same drug formulations have been reported. There are cases where the studies failed to demonstrate the long-term effects of the chemotherapeutic drug formulations to the lung parenchyma. Acute and latent effects observed in a small number of human trial studies are still under investigation of inhaled chemotherapy administration. This review provides data regarding all up-to-date inhaled chemotherapy studies and presents the methodological parameters of the safety measures incorporated. In addition, a commentary regarding the safety concerns for the medical staff participating in these studies will be presented.

Seeking Genomic Knowledge: The Case for Clinical Restraint

Genome sequencing technology provides new and promising tests for clinical practice, including whole genome sequencing, which measures an individual's complete DNA sequence, and whole exome sequencing, which measures the DNA for all genes coding for proteins. These technologies make it possible to test for multiple genes in a single test, which increases the efficiency of genetic testing. However, they can also produce large amounts of information that cannot be interpreted or is of limited clinical utility. This additional information could be distracting for patients and clinicians, and contribute to unnecessary healthcare costs. The potential for genomic sequencing to improve care will be context-dependent, varying for different patients and clinical settings. This Article argues that a disciplined approach is needed, incorporating research to assess when and how genomic information can improve clinical outcomes, practice guidelines that direct optimal uses of genomic sequencing, and efforts to limit the production of genomic information unrelated to the clinical needs of the patient. Without this approach, genomic testing could add to current unsustainable healthcare costs and prove unaffordable in the long run.

Pharmacogenomics in clinical practice and drug development

Genome-wide association studies (GWAS) of responses to drugs, including clopidogrel, pegylated-interferon and carbamazepine, have led to the identification of specific patient subgroups that benefit from therapy. However, the identification and replication of common sequence variants that are associated with either efficacy or safety for most prescription medications at odds ratios (ORs) >3.0 (equivalent to >300% increased efficacy or safety) has yet to be translated to clinical practice. Although some of the studies have been completed, the results have not been incorporated into therapy, and a large number of commonly used medications have not been subject to proper pharmacogenomic analysis. Adoption of GWAS, exome or whole genome sequencing by drug development and treatment programs is the most striking near-term opportunity for improving the drug candidate pipeline and boosting the efficacy of medications already in use.