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Yan Q.,PharmTao | Yan Q.,University of Phoenix
Personalized Medicine | Year: 2011

With its multidimensional features and systems biology approaches, developments in psychoneuroimmunology may provide the basis for the translation of scientific discoveries into personalized and systems medicine. To achieve this goal, several key issues need to be emphasized and resolved. These key issues include the identification of biomarkers for accurate diagnosis and treatment, the understanding of the systems interactions and networks, and the systemic profiling of patient subgroups. Recognition of systemic biomarkers may provide insight into the complex multidirectional interactions among psychological and behavioral factors, the nervous system and the immune system. Systems biology studies of complex mechanisms such as inflammation at various levels may enable the discovery of common targets for different diseases from depression to cancer. Such elucidation would enable the classification of patient patterns and subgroups for personalized interventions. Understanding of these key issues would contribute to the establishment of systems models and the development of integrative prevention and treatment strategies in multiple dimensions. © 2011 Future Medicine Ltd.


Yan Q.,PharmTao | Yan Q.,University of Phoenix
Methods in Molecular Biology | Year: 2012

Developments in psychoneuroimmunology (PNI) need to be translated into personalized medicine to achieve better clinical outcomes. One of the most critical steps in this translational process is to identify systemic biomarkers for better diagnosis and treatment. Applications of systems biology approaches in PNI would enable the insights into the correlations among various systems and different levels for the identification of the basic elements of the psychophysiological framework. Among the potential PNI biomarkers, inflammatory markers deserve special attention as they play a pivotal role linking various health conditions and disorders. The elucidation of inflammatory markers, cytokine networks, and immune-brain-behavior interactions may help establish PNI profiles for the identification of potential targets for personalized interventions in at risk populations. The understanding of the general systemic pathways among different disorders may contribute to the transition from the disease-centered medicine to patient-centered medicine. Integrative strategies targeting these factors and pathways would be useful for the prevention and treatment of a spectrum of diseases that share the common links. Examples of the translational implications of potential PNI biomarkers and networks in diseases including depression, Alzheimer's disease, obesity, cardiovascular disease, stroke, and HIV are discussed in details. © 2012 Springer Science+Business Media, LLC.


Yan Q.,PharmTao | Yan Q.,University of Phoenix
Methods in Molecular Biology | Year: 2012

Psychoneuroimmunology (PNI) may provide the scientific basis for personalized and systems medicine. The exploration of the extensive interactions among psychological and behavioral factors, the nervous system, the immune system, and the endocrine system may help understand the mechanisms underlying health, wellness, and diseases. PNI theories based on systems biology methodologies may contribute to the identification of patient patterns for establishing psychological and physiological profiles for personalized medicine. A biopsychosocial model will help elucidate the systemic interrelationships between psychosocial and bio-physiological factors for the development of systems medicine. Many evidences have supported the close relationships between stress, depression, inflammation, and disorders including obesity, cardiovascular disease, diabetes, arthritis, skin diseases, infectious diseases, and sleep disorders. As inflammation is a critical connection among different diseases, the elucidation of the associations may contribute to the findings of systemic therapeutic targets. With the understanding of the translational implications of PNI, integrative interventions in multiple dimensions can be applied to modulate stress responses and promote healthier behaviors. These interventions include combination drug therapies, diets, nutritional supplements, meditation, and other behavioral and mind-body strategies. © 2012 Springer Science+Business Media, LLC.


Yan Q.,PharmTao
Methods in Molecular Biology | Year: 2010

The immune system plays an important role in the development of personalized medicine for a variety of diseases including cancer, autoimmune diseases, and infectious diseases. Immunoinformatics, or computational immunology, is an emerging area that provides fundamental methodologies in the study of immunomics, that is, immune-related genomics and proteomics. The integration of immunoinformatics with systems biology approaches may lead to a better understanding of immune-related diseases at various systems levels. Such methods can contribute to translational studies that bring scientific discoveries of the immune system into better clinical practice. One of the most intensely studied areas of the immune system is immune epitopes. Epitopes are important for disease understanding, host-pathogen interaction analyses, antimicrobial target discovery, and vaccine design. The information about genetic diversity of the immune system may help define patient subgroups for individualized vaccine or drug development. Cellular pathways and host immune-pathogen interactions have a crucial impact on disease pathogenesis and immunogen design. Epigenetic studies may help understand how environmental changes influence complex immune diseases such as allergy. High-throughput technologies enable the measurements and catalogs of genes, proteins, interactions, and behavior. Such perception may contribute to the understanding of the interaction network among humans, vaccines, and drugs, to enable new insights of diseases and therapeutic responses. The integration of immunomics information may ultimately lead to the development of optimized vaccines and drugs tailored to personalized prevention and treatment. An immunoinformatics portal containing relevant resources is available at http://immune.pharmtao.com. © 2010 Springer Science+Business Media, LLC.


Yan Q.,PharmTao
Methods in Molecular Biology | Year: 2010

Systems biology and pharmacogenomics are emerging and promising fields that will provide a thorough understanding of diseases and enable personalized therapy. However, one of the most significant obstacles in the practice of personalized medicine is the translation of scientific discoveries into better therapeutic outcomes. Translational bioinformatics is a powerful method to bridge the gap between systems biology research and clinical practice. This goal can be achieved through providing integrative methods to enable predictive models for therapeutic responses. As a media between bench and bedside, translational bioinformatics has the mission to meet challenges in the development of personalized medicine. On the biomedical side, translational bioinformatics would enable the identification of biomarkers based on systemic analyses. It can improve the understanding of the correlations between genotypes and phenotypes. It would enable novel insights of interactions and interrelationships among different parts in a whole system. On the informatics side, methods based on data integration, data mining, and knowledge representation can provide decision support for both researchers and clinicians. Data integration is not only for better data access, but also for knowledge discovery. Decision support based on translational bioinformatics means better information and workflow management, efficient literature and resource retrieval, and communication improvement. These approaches are crucial for understanding diseases and applying personalized therapeutics at systems levels. © 2010 Springer Science+Business Media, LLC.


Yan Q.,PharmTao
Methods in molecular biology (Clifton, N.J.) | Year: 2010

The immune system plays an important role in the development of personalized medicine for a variety of diseases including cancer, autoimmune diseases, and infectious diseases. Immunoinformatics, or computational immunology, is an emerging area that provides fundamental methodologies in the study of immunomics, that is, immune-related genomics and proteomics. The integration of immunoinformatics with systems biology approaches may lead to a better understanding of immune-related diseases at various systems levels. Such methods can contribute to translational studies that bring scientific discoveries of the immune system into better clinical practice. One of the most intensely studied areas of the immune system is immune epitopes. Epitopes are important for disease understanding, host-pathogen interaction analyses, antimicrobial target discovery, and vaccine design. The information about genetic diversity of the immune system may help define patient subgroups for individualized vaccine or drug development. Cellular pathways and host immune-pathogen interactions have a crucial impact on disease pathogenesis and immunogen design. Epigenetic studies may help understand how environmental changes influence complex immune diseases such as allergy. High-throughput technologies enable the measurements and catalogs of genes, proteins, interactions, and behavior. Such perception may contribute to the understanding of the interaction network among humans, vaccines, and drugs, to enable new insights of diseases and therapeutic responses. The integration of immunomics information may ultimately lead to the development of optimized vaccines and drugs tailored to personalized prevention and treatment. An immunoinformatics portal containing relevant resources is available at http://immune.pharmtao.com.


Influenza virus infection is a public health threat worldwide. It is urgent to develop effective methods and tools for the prevention and treatment of influenza. Influenza vaccines have significant immune response variability across the population. Most of the current circulating strains of influenza A virus are resistant to anti-influenza drugs. It is necessary to understand how genetic variants affect immune responses, especially responses to the HA and NA transmembrane glycoproteins. The elucidation of the underlying mechanisms can help identify patient subgroups for effective prevention and treatment. New personalized vaccines, adjuvants, and drugs may result from the understanding of interactions of host genetic, environmental, and other factors. The systems biology approach is to simulate and model large networks of the interacting components, which can be excellent targets for antiviral therapies. The elucidation of host-influenza interactions may provide an integrative view of virus infection and host responses. Understanding the host-influenza-drug interactions may contribute to optimal drug combination therapies. Insight of the host-influenza-vaccine interactions, especially the immunogenetics of vaccine response, may lead to the development of better vaccines. Systemic studies of host-virus-vaccine-drug-environment interactions will enable predictive models for therapeutic responses and the development of individualized therapeutic strategies. A database containing such information on personalized and systems medicine for influenza is available at http://flu.pharmtao.com.


Yan Q.,PharmTao
Methods in molecular biology (Clifton, N.J.) | Year: 2010

Systems biology and pharmacogenomics are emerging and promising fields that will provide a thorough understanding of diseases and enable personalized therapy. However, one of the most significant obstacles in the practice of personalized medicine is the translation of scientific discoveries into better therapeutic outcomes. Translational bioinformatics is a powerful method to bridge the gap between systems biology research and clinical practice. This goal can be achieved through providing integrative methods to enable predictive models for therapeutic responses. As a media between bench and bedside, translational bioinformatics has the mission to meet challenges in the development of personalized medicine. On the biomedical side, translational bioinformatics would enable the identification of biomarkers based on systemic analyses. It can improve the understanding of the correlations between genotypes and phenotypes. It would enable novel insights of interactions and interrelationships among different parts in a whole system. On the informatics side, methods based on data integration, data mining, and knowledge representation can provide decision support for both researchers and clinicians. Data integration is not only for better data access, but also for knowledge discovery. Decision support based on translational bioinformatics means better information and workflow management, efficient literature and resource retrieval, and communication improvement. These approaches are crucial for understanding diseases and applying personalized therapeutics at systems levels.


Yan Q.,PharmTao
Methods in molecular biology (Clifton, N.J.) | Year: 2010

Bioinformatics is the rational study at an abstract level that can influence the way we understand biomedical facts and the way we apply the biomedical knowledge. Bioinformatics is facing challenges in helping with finding the relationships between genetic structures and functions, analyzing genotype-phenotype associations, and understanding gene-environment interactions at the systems level. One of the most important issues in bioinformatics is data integration. The data integration methods introduced here can be used to organize and integrate both public and in-house data. With the volume of data and the high complexity, computational decision support is essential for integrative transporter studies in pharmacogenomics, nutrigenomics, epigenetics, and systems biology. For the development of such a decision support system, object-oriented (OO) models can be constructed using the Unified Modeling Language (UML). A methodology is developed to build biomedical models at different system levels and construct corresponding UML diagrams, including use case diagrams, class diagrams, and sequence diagrams. By OO modeling using UML, the problems of transporter pharmacogenomics and systems biology can be approached from different angles with a more complete view, which may greatly enhance the efforts in effective drug discovery and development. Bioinformatics resources of membrane transporters and general bioinformatics databases and tools that are frequently used in transporter studies are also collected here. An informatics decision support system based on the models presented here is available at http://www.pharmtao.com/transporter . The methodology developed here can also be used for other biomedical fields.


The study of membrane transporters may result in breakthroughs in the discovery of new drugs and the development of safer drugs. Membrane transporters are essential for fundamental cellular functions and normal physiological processes. These molecules influence drug absorption and distribution and play key roles in drug therapeutic effects. A primary goal of current research in drug discovery and development is to fully understand the interactions between transporters and drugs at both the system levels in the human body and the individual level for personalized therapy. Systematic studies of membrane transporters will help in not only better understanding of diseases from the systems biology point of view but also better drug design and development. The exploration of both pharmacogenomics and systems biology in transporters is necessary to connect individuals' genetic profiles with systematic drug responses in the human body. Understanding of gene-diet interactions and the effects of epigenetic changes on transporter gene expression may help improve clinical drug efficacy. The integration of pharmacogenomics, nutrigenomics, epigenetics, and systems biology may enable us to move from disease treatment to disease prevention and optimal health. The key issues in such integrative understanding include the correlations between structure and function, genotype and phenotype, and systematic interactions among transporters, other proteins, nutrients, drugs, and the environment. The exploration in these key issues may ultimately contribute to personalized medicine with high efficacy but less toxicity.

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