Current Pharmaceutical Design - Volume 15, Issue 32, 2009

The complementary fields of pharmacogenetics and pharmacogenomics have been widely espoused as promising methods both in achieving the goal of tailored drug therapy at an individual level and in the formulation of methods to for the development of novel drug compounds at a global level. By definition, pharmacogenetics is the study of variability in drug response due to heredity. That is, pharmacogenetics seeks to determine the role of genetic determinants in an individual's response to therapy. The related term, pharmacogenomics, refers to the development of novel drugs based upon the evolving knowledge of the genome. The two terms, however, are frequently used interchangeably. Ideally, pharmacogenetics will allow for “individualized therapy” based upon an individual's genetic make-up that will maximize the potential for therapeutic benefit, while minimizing the risk of adverse effects to any given medication. The potential for cost savings (via increased drug efficacy) and for decreasing morbidity and mortality (via increasing drug safety) is immense. Indeed, the formative basis for everyday clinical use of pharmacogenetic testing has been laid out, with two tests now approved by the United States Food and Drug Administration (FDA). These include the Invader® UGTlAl Molecular Assay (for the UGT1A1*28 allele) and the Roche AmpliChip Cytochrome P450 Genotyping test (for variants in CYP2D6 and CYP2C19). The UGT1A1*28 allele has been consistently associated with toxicity related to irinotecan administration [1-3], while CYP2D6 and CYP2C19 variants alter the metabolism of a wide number of medications [4, 5]. In addition to these tests, pharmacogenomic information is present in about 10% of labels for drugs approved by the FDA. A list of valid genomic biomarkers in the context of drug labels is available (www.fda.gov/cder/genomics/genomic_biomarkers_table.htm). Despite the successful translation of pharmacogenetics to the clinical realm for several compounds, as a field, pharmacogenetics has not yet lived up to the widely espoused “promise of personalized medicine” in that tailored treatment is not even conceptually in the guidelines for the vast majority of diseases nor have novel therapeutic compounds been commonly developed using genomic information. From a predictive testing perspective, initial pharmacogenetic studies have often been limited by the lack of reproducibility of results, small sample size, or lack of a significant proportion of the variability of the drug-response phenotype explained by a given genetic variant. Implicit in these limitations is the fact that for complex diseases, drug treatment response is not likely to be explained by simple Mendelian inheritance, in a fashion consistent with the epistatic nature of the underlying disease biology. Techniques that will efficiently identify additional genetic variants that focus on maximizing the sensitivity for detecting true variants or maximizing specificity of the variants as contributing biologically to the drug response phenotype of interest are clearly needed. The focus of this series of articles is on novel ways of investigating or analyzing data that may have pharmacogenetic or pharmacogenomic relevance. We begin with an overview of the pharmacogenetics of two complex diseases -- arrythmias, presented by Dr. Roden and colleagues and asthma, written by Dr. Duan and myself. Each of these overview reviews reinforce the promise of pharmacogenetics, citing several genes implicated in variation in drug-target response. These manuscripts also both highlight the problems with prior association work and the need for better ways to interrogate data related to drug response in these complex diseases. Dr. Akkari and colleagues provide a detailed overview of “Pipeline Pharmacogenetics”, which is the integration of pharmacogenomics into and across the development process, with each successive phase being informed by PGx science performed in the previous phases. This differs in context from the traditional use of pharmacogenetics in drug development, which focuses on genetic variation related to a compounds initial development and safety profile. This approach can increase the rate of success in ushering a promising compound through the pipeline, since companion diagnostic testing accompanies drug development.

Abnormalities of cardiac rhythm are common clinical problems, resulting in symptoms such as palpitations, breathlessness, stroke, and sudden death. Drugs used to treat arrhythmias have variable actions ranging from completely effective to serious adverse effects, including (paradoxically) sudden death due to drug-induced arrhythmias. Experiments to define the genetic basis for arrhythmia susceptibility and variable responses to antiarrhythmic therapies rely on precise clinical phenotyping. Initial studies used candidate gene approaches, but are now turning to contemporary methods such as genome-wide association. Identification of loci for arrhythmia susceptibility in turn provide a starting point for both understanding underlying biologic pathways as well as improved selection appropriate therapies.

Asthma is a chronic disorder causing inflammation and reversible airway obstruction that affects approximately 300 million individuals worldwide. The incidence of asthma has nearly doubled in the past three decades resulting in higher rates of morbidity, mortality and health care costs. Despite the availability of several classes of asthma medications such as β-agonists, leukotriene modifiers and corticosteroids, up to 50% of asthmatics do not benefit from one or more of these drugs. Studies have shown that asthma and drug response phenotypes such as forced expiratory volume in one second (FEV1) are heritable traits, indicating a genetic component of variable response to asthma drugs. This review summarizes the findings of pharmacogenetic investigations on the three main classes of asthma medications. In addition, the limitations of these genetic studies are discussed and future research avenues are proposed to identify novel genetic factors. Although numerous genes have been associated with variable response to common asthma drugs, results are often contradictory across different studies, and remain to be confirmed in larger replication cohorts. Nevertheless, literature in asthma pharmacogenetics demonstrates that genetic variants influence response to asthma treatments and may be used for predictive testing prior to drug administration to avoid adverse reactions and increase drug efficacy.

There has been a decline in the number of new drugs registered over the past decade and regulatory concerns for safety as well as payer concerns for efficacy have focused attention on stratified medicine. Integration of pharmacogenetics into the drug development pipeline will contribute to the development of new stratified drugs. We describe here the concept of pipeline pharmacogenetics and its application throughout the phases of drug discovery. Pipeline pharmacogenetics enables the evaluation of the genetic contribution to safety potentially lowering barriers to registration as well as providing rationale for efficacy and enabling co-development of genetic in vitro diagnostics.

Genome-wide associations studies (GWAS) have become routine in human genetics research; however the application of GWAS to pharmacogenomics research is just beginning. As these studies make their way into pharmacogenetics, there are several considerations specific to pharmacogenetics that should be made. In this manuscript, we discuss these considerations and provide concrete examples with GWAS data for an asthma clinical trial using parentoffspring trios.

The availability of high-throughput genotyping and sequencing platforms has largely removed technological barriers in the mapping the genetic determinants of drug response in human populations, and the set of validated pharmacogenetic variants is gradually increasing. Like the search for disease-susceptibility variation, however, many of the loci identified to date represent the relatively low-hanging fruit with large phenotypic effects but relatively low predictive power. Yet to be discovered is the larger set of variants, each with considerably weaker phenotypic effects, which together can be used to predict drug response more reliably and identify potential targets for novel drug development. Finding these pharmacogenetic variants is particularly challenging because sample size is typically far too small (and thus statistically underpowered) to detect genetic variants with weak effects. Studies of the genetics of gene expression (also described as expression quantitative locus (eQTL) mapping or genetical genomics) represent a novel approach for identification of functional genetic variants that influence gene expression. In these studies, individual gene transcript abundance as measured from expression microarrays are considered as discrete quantitative traits for genetic mapping that are intermediate to clinical outcomes of interest. Early studies using these methods have demonstrated improved power to detect such regulatory variants and have facilitated mapping of disease-susceptibility variants. The potential use of this approach in the study of pharmacogenetics and for the identification of potentially modifiable drug targets is reviewed here.

Drug response and toxicity, complex traits that are often highly varied among individuals, likely involve multiple genetic and non-genetic factors. Pharmacogenomic research aims to individualize therapy in an effort to maximize efficacy and minimize toxicity for each patient. Cell lines can be used as a model system for cellular pharmacologic effects, which include, but are not limited to, drug-induced cytotoxicity or apoptosis, biochemical effects and enzymatic reactions. Because severe toxicities may be associated with drugs such as chemotherapeutics, cell lines derived from healthy individuals or patients provide a convenient model to study how human genetic variation alters response to these drugs that would be unsafe or unethical to administer to human volunteers. In addition to the traditional candidate gene approaches that focus on well-understood candidate genes and pathways, the availability of extensive genotypic and phenotypic data on some cell line models has begun to allow genome-wide association (GWA) studies to simultaneously test the entire human genome for associations with drug response and toxicity. Though with some important limitations, the use of these cell lines in pharmacogenomic discovery demonstrates the promise of constructing a more comprehensive model that may ultimately integrate both genetic and non-genetic factors to predict individual response and toxicity to anticancer drugs.

Cancer therapies through ionizing radiation or chemotherapeutic treatment may result in DNA double strand breaks (DSBs) in cell. DNA-PK has emerged as an attractive target for drug discovery efforts toward DSBs repair and in V(D)J recombination. Hence, the search for potent and selective DNA-PK inhibitors has received particular attention and several series of activity inhibitors have been reported. In this article, we gave a report of the DNA-PK activation and the corresponding inhibitors, which belong to different chemical classes. Then homology modeling and molecular dynamics (MD) simulation were used to build the 3D model of DNA-PK receptor based on the X-ray structure of PI3K. All of the ligands were docked into the putative binding site of the 3D model of DNA-PK using the flexible docking method, and the probable interaction model between DNA-PK and the ligands were obtained. Based on the docking conformations and their alignment inside the binding pocket of DNA-PK, 3D QSAR analyses were performed on 259 ligands using CoMFA and CoMSIA methods. Both CoMFA and CoMSIA provide statistically valid models with good correlation and predictive power (CoMFA: q2 = 0.563, r2 =0.876; CoMSIA: q2 = 0.503, r2 =0.870). Our models would offer help to better comprehend the structure-activity relationship existent for this class of compounds and also facilitate the design of new inhibitors with good chemical derivsity.

Nanocarriers are effective non-viral vectors for drug and gene delivery with low immunogenicity in comparison with viral vectors. However, the lack of organ or cell specificity sometimes hinders their application and brings about unexpected side effects. Active targeting is an outstanding strategy recently developed for drug delivery systems, for example, surface modification of nanocarriers with specific ligands could target the pathological area to provide the maximum therapeutic efficacy. In such cases, the characteristics of the ligands determine the active targeting abilities of the nanocarrier systems. Recently, more attentions have been paid to saccharides as ligands for saccharidemodified nanocarriers, possesing the receptor-mediated targeting properties and showing the potential for cell-specific delivery of drugs and genes. In this review, various kinds of glycosylated nanocarriers are discussed, including: varying ligands, targeting properties, therapeutic effects, and methods for administering the nanocarriers. The advantages as well as the probable associated drawbacks of these vectors are communicated.