Systems biology in pharmacogenomic research: the way to personalized prescribing?

Systems biology approaches to adverse drug effects: the example of cardio-oncology

Increased awareness of the cardiovascular toxic effects of chemotherapy has led to the emergence of cardio-oncology (or onco-cardiology), which focuses on screening, monitoring and treatment of patients with cardiovascular dysfunctions resulting from chemotherapy. Anthracyclines, such as doxorubicin, and HER2 inhibitors, such as trastuzumab, both have cardiotoxic effects. The biological rationale, mechanisms of action and cardiotoxicity profiles of these two classes of drugs, however, are completely different, suggesting that cardiotoxic effects can occur in a range of different ways. Advances in genomics and proteomics have implicated several genomic variants and biological pathways that can influence the susceptibility to cardiotoxicity from these, and other drugs. Established pathways include multidrug resistance proteins, energy utilization pathways, oxidative stress, cytoskeletal regulation and apoptosis. Gene-expression profiles that have revealed perturbed pathways have vastly increased our knowledge of the complex processes involved in crosstalk between tumours and cardiac function. Utilization of mathematical and computational modelling can complement pharmacogenomics and improve individual patient outcomes. Such endeavours should enable identification of variations in cardiotoxicity, particularly in those patients who are at risk of not recovering, even with the institution of cardioprotective therapy. The application of systems biology holds substantial potential to advance our understanding of chemotherapy-induced cardiotoxicity.

Using systems approaches to address challenges for clinical implementation of pharmacogenomics

Many genetic variants have been shown to affect drug response through changes in drug efficacy and likelihood of adverse effects. Much of pharmacogenomic science has focused on discovering and clinically implementing single gene variants with large effect sizes. Given the increasing complexities of drug responses and their variability, a systems approach may be enabling for discovery of new biology in this area. Further, systems approaches may be useful in addressing challenges in moving these data to clinical implementation, including creation of predictive models of drug response phenotypes, improved clinical decision-making through complex biological models, improving strategies for integrating genomics into clinical practice, and evaluating the impact of implementation programs on public health.

A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics

Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.

Systems biology technologies enable personalized traditional Chinese medicine: a systematic review

Traditional Chinese medicine (TCM), an alternative medicine, focuses on the treatment of human disease via the integrity of the close relationship between body and syndrome analysis. It remains a form of primary care in most Asian countries and its characteristics showcase the great advantages of personalized medicine. Although this approach to disease diagnosis, prognosis and treatment has served the medical establishment well for thousands of years, it has serious shortcomings in the era of modern medicine that stem from its reliance on reductionist principles of experimentation and analysis. In this way, systems biology offers the potential to personalize medicine, facilitating the provision of the right care to the right patient at the right time. We expect that systems biology will have a major impact on future personalized therapeutic approaches which herald the future of medicine. Here we summarize current trends and critically review the potential limitations and future prospects of such treatments. Some characteristic examples are presented to highlight the application of this groundbreaking platform to personalized TCM as well as some of the necessary milestones for moving systems biology of a state-of-the-art nature into mainstream health care.

Integrative systems biology approaches in asthma pharmacogenomics

In order to improve therapeutic outcomes, there is a tremendous need to identify patients who are likely to respond to a given asthma treatment. Pharmacogenomic studies have explained a portion of the variability in drug response and provided an increasing list of candidate genes and SNPs. However, as phenotypic variation arises from a network of complex interactions among genetic and environmental factors, rather than individual genes or SNPs, a multidisciplinary, systems-level approach is required in order to understand the inter-relationships among these factors. Systems biology, which seeks to capture interactions between genetic factors and other variables, offers a promising approach to improved therapeutic outcomes in asthma. This aritcle will review and update progress in the pharmacogenomics of asthma and then discuss the application of systems biology approaches to asthma pharmacogenomics.

Biomarkers of therapy responsiveness in asthma: pitfalls and promises

Asthma is one of the most common chronic diseases worldwide. There is a large inter-individual variability in response to asthma treatment. Most patients respond well to standard therapy; however, a small proportion of the patients remain symptomatic despite treatment with high dosages of corticosteroids. Uncontrolled asthma leads to a decreased quality of life. Therefore, it is important to identify individuals who will respond poorly to standard asthma medication, especially to standard maintenance therapy with inhaled corticosteroids, at an early stage. Response to anti-inflammatory therapy is generally monitored by the assessment of clinical symptoms, which only partially correlates with underlying airway inflammation. The identification of specific inflammatory biomarkers might help to guide treatment or predict a corticosteroid response more accurately. Some inflammatory biomarkers are already finding their way into clinical practice (e.g. fraction of nitric oxide in exhaled breath), whereas others are predominantly used as a research tool (e.g. profiles of volatile organic compounds). Currently, there is no inflammatory biomarker used in routine clinical practice to predict a corticosteroid response. More knowledge on the underlying biological mechanism(s) of heterogeneous therapeutic responses could help to identify novel biomarkers. This review will focus on inflammatory patterns and genetic variations that may underlie differences in treatment response in patients with asthma, and will provide an overview of inflammatory biomarkers that could potentially serve as response predictors.

Systems biology data analysis methodology in pharmacogenomics

Pharmacogenetics aims to elucidate the genetic factors underlying the individual's response to pharmacotherapy. Coupled with the recent (and ongoing) progress in high-throughput genotyping, sequencing and other genomic technologies, pharmacogenetics is rapidly transforming into pharmacogenomics, while pursuing the primary goals of identifying and studying the genetic contribution to drug therapy response and adverse effects, and existing drug characterization and new drug discovery. Accomplishment of both of these goals hinges on gaining a better understanding of the underlying biological systems; however, reverse-engineering biological system models from the massive datasets generated by the large-scale genetic epidemiology studies presents a formidable data analysis challenge. In this article, we review the recent progress made in developing such data analysis methodology within the paradigm of systems biology research that broadly aims to gain a 'holistic', or 'mechanistic' understanding of biological systems by attempting to capture the entirety of interactions between the components (genetic and otherwise) of the system.

Molecular basis of chronopharmaceutics

Many pathophysiological circumstances vary during 24 h periods. Many physiologic processes undergo biological rhythms, including the sleep-wake rhythm and metabolism. Disruptive effect in the 24 h variations can manifest as the emergence or exacerbation of pathological conditions. So, chronotherapeutics is gaining increasing interest in experimental biology, medicine, pharmacy, and drug delivery. This science and the plethora of information should be used intelligently for optimizing the effectiveness and safety of the drug, relying on the timing of drug intake. These chronopharmacological findings are affected by not only the pharmacodynamics but also pharmacokinetics of drugs. The mammalian circadian pacemaker is located in the suprachiasmatic nucleus. The molecular mechanisms are associated with Clock genes that control the circadian rhythms in physiology, pathology, and behavior. Clock controls several diseases such as metabolic syndrome, cancer, and so on. CLOCK mutation influences the expression of both rhythmic and nonrhythmic genes in wild-type tissues. These genotypic changes lead to phenotypic changes, affecting the drug pharmacokinetic and pharmacodynamic parameters. This review is intended to elaborate system regulating biological rhythms and the applicability in pharmaceutics from viewpoints of the intraindividual and interindividual variabilities of Clock genes.

Influence of dietary substances on intestinal drug metabolism and transport

Successful delivery of promising new chemical entities via the oral route is rife with challenges, some of which cannot be explained or foreseen during drug development. Further complicating an already multifaceted problem is the obvious, yet often overlooked, effect of dietary substances on drug disposition and response. Some dietary substances, particularly fruit juices, have been shown to inhibit biochemical processes in the intestine, leading to altered pharmacokinetic (PK), and potentially pharmacodynamic (PD), outcomes. Inhibition of intestinal CYP3Amediated metabolism is the major mechanism by which fruit juices, including grapefruit juice, enhances systemic exposure to new and already marketed drugs. Inhibition of intestinal non-CYP3A enzymes and apically-located transport proteins represent recently identified mechanisms that can alter PK and PD. Several fruit juices have been shown to inhibit these processes in vitro, but some interactions have not translated to the clinic. The lack of in vitroin vivo concordance is due largely to a lack of rigorous methods to elucidate causative ingredients prior to clinical testing. Identification of specific components and underlying mechanisms is challenging, as dietary substances frequently contain multiple, often unknown, bioactive ingredients that vary in composition and bioactivity. A translational research approach, combining expertise from clinical pharmacologists and natural products chemists, is needed to develop robust models describing PK/PD relationships between a given dietary substance and drug of interest. Validation of these models through well-designed clinical trials would facilitate development of common practice guidelines for managing drug-dietary substance interactions appropriately.

Toxicogenetics: population-based testing of drug and chemical safety in mouse models

The rapid decline in the cost of dense genotyping is paving the way for new DNA sequence-based laboratory tests to move quickly into clinical practice, and to ultimately help realize the promise of 'personalized' therapies. These advances are based on the growing appreciation of genetics as an important dimension in science and the practice of investigative pharmacology and toxicology. On the clinical side, both the regulators and the pharmaceutical industry hope that the early identification of individuals prone to adverse drug effects will keep advantageous medicines on the market for the benefit of the vast majority of prospective patients. On the environmental health protection side, there is a clear need for better science to define the range and causes of susceptibility to adverse effects of chemicals in the population, so that the appropriate regulatory limits are established. In both cases, most of the research effort is focused on genome-wide association studies in humans where de novo genotyping of each subject is required. At the same time, the power of population-based preclinical safety testing in rodent models (e.g., mouse) remains to be fully exploited. Here, we highlight the approaches available to utilize the knowledge of DNA sequence and genetic diversity of the mouse as a species in mechanistic toxicology research. We posit that appropriate genetically defined mouse models may be combined with the limited data from human studies to not only discover the genetic determinants of susceptibility, but to also understand the molecular underpinnings of toxicity.

Recent Publications on Medications and Pharmacy

Hospital Pharmacy presents this feature to keep pharmacists abreast of new publications in the medical/pharmacy literature. Articles of interest regarding a broad scope of topics are abstracted monthly.