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Author: Tarek A. Leil Publisher: Frontiers Media SA ISBN: 2889196429 Category : Biology Languages : en Pages : 99
Book Description
In 2011, the National Institutes of Health (NIH), in collaboration with leaders from the pharmaceutical industry and the academic community, published a white paper describing the emerging discipline of Quantitative Systems Pharmacology (QSP), and recommended the establishment of NIH-supported interdisciplinary research and training programs for QSP. QSP is still in its infancy, but has tremendous potential to change the way we approach biomedical research. QSP is really the integration of two disciplines that have been increasingly useful in biomedical research; “Systems Biology” and “Quantitative Pharmacology”. Systems Biology is the field of biomedical research that seeks to understand the relationships between genes and biologically active molecules to develop qualitative models of these systems; and Quantitative Pharmacology is the field of biomedical research that seeks to use computer aided modeling and simulation to increase our understanding of the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs, and to aid in the design of pre-clinical and clinical experiments. The purpose of QSP modeling is to develop quantitative computer models of biological systems and disease processes, and the effects of drug PK and PD on those systems. QSP models allow testing of numerous potential experiments “in-silico” to eliminate those associated with a low probability of success, avoiding the potential costs of evaluating all of those failed experiments in the real world. At the same time, QSP models allow us to develop our understanding of the interaction between drugs and biological systems in a more systematic and rigorous manner. As the need to be more cost-efficient in the use of research funding increases, biomedical researchers will be required to gain the maximum insight from each experiment that is conducted. This need is even more acute in the pharmaceutical industry, where there is tremendous competition to develop innovative therapies in a highly regulated environment, combined with very high research and development (R&D) costs for bringing new drugs to market (~$1.3 billion/drug). Analogous modeling & simulation approaches have been successfully integrated into other disciplines to improve the fundamental understanding of the science and to improve the efficiency of R&D (e.g., physics, engineering, economics, etc.). The biomedical research community has been slow to integrate computer aided modeling & simulation for many reasons: including the perception that biology and pharmacology are “too complex” and “too variable” to be modeled with mathematical equations; a lack of adequate graduate training programs; and the lack of support from government agencies that fund biomedical research. However, there is an active community of researchers in the pharmaceutical industry, the academic community, and government agencies that develop QSP and quantitative systems biology models and apply them both to better characterize and predict drug pharmacology and disease processes; as well as to improve efficiency and productivity in pharmaceutical R&D.
Author: Tarek A. Leil Publisher: Frontiers Media SA ISBN: 2889196429 Category : Biology Languages : en Pages : 99
Book Description
In 2011, the National Institutes of Health (NIH), in collaboration with leaders from the pharmaceutical industry and the academic community, published a white paper describing the emerging discipline of Quantitative Systems Pharmacology (QSP), and recommended the establishment of NIH-supported interdisciplinary research and training programs for QSP. QSP is still in its infancy, but has tremendous potential to change the way we approach biomedical research. QSP is really the integration of two disciplines that have been increasingly useful in biomedical research; “Systems Biology” and “Quantitative Pharmacology”. Systems Biology is the field of biomedical research that seeks to understand the relationships between genes and biologically active molecules to develop qualitative models of these systems; and Quantitative Pharmacology is the field of biomedical research that seeks to use computer aided modeling and simulation to increase our understanding of the pharmacokinetics (PK) and pharmacodynamics (PD) of drugs, and to aid in the design of pre-clinical and clinical experiments. The purpose of QSP modeling is to develop quantitative computer models of biological systems and disease processes, and the effects of drug PK and PD on those systems. QSP models allow testing of numerous potential experiments “in-silico” to eliminate those associated with a low probability of success, avoiding the potential costs of evaluating all of those failed experiments in the real world. At the same time, QSP models allow us to develop our understanding of the interaction between drugs and biological systems in a more systematic and rigorous manner. As the need to be more cost-efficient in the use of research funding increases, biomedical researchers will be required to gain the maximum insight from each experiment that is conducted. This need is even more acute in the pharmaceutical industry, where there is tremendous competition to develop innovative therapies in a highly regulated environment, combined with very high research and development (R&D) costs for bringing new drugs to market (~$1.3 billion/drug). Analogous modeling & simulation approaches have been successfully integrated into other disciplines to improve the fundamental understanding of the science and to improve the efficiency of R&D (e.g., physics, engineering, economics, etc.). The biomedical research community has been slow to integrate computer aided modeling & simulation for many reasons: including the perception that biology and pharmacology are “too complex” and “too variable” to be modeled with mathematical equations; a lack of adequate graduate training programs; and the lack of support from government agencies that fund biomedical research. However, there is an active community of researchers in the pharmaceutical industry, the academic community, and government agencies that develop QSP and quantitative systems biology models and apply them both to better characterize and predict drug pharmacology and disease processes; as well as to improve efficiency and productivity in pharmaceutical R&D.
Author: Davide Manca Publisher: Elsevier ISBN: 0444639675 Category : Technology & Engineering Languages : en Pages : 420
Book Description
Quantitative Systems Pharmacology: Models and Model-Based Systems with Applications, Volume 42, provides a quantitative approach to problem-solving that is targeted to engineers. The book gathers the contributions of doctors, pharmacists, biologists, and chemists who give key information on the elements needed to model a complex machine like the human body. It presents information on diagnoses, administration and release of therapeutics, distribution metabolism and excretion of drugs, compartmental pharmacokinetics, physiologically-based pharmacokinetics, pharmacodynamics, identifiability of models, numerical methods for models identification, design of experiments, in vitro and in vivo models, and more. As the pharma community is progressively acknowledging that a quantitative and systematic approach to drug administration, release, pharmacokinetics and pharmacodynamics is highly recommended to understand the mechanisms and effects of drugs, this book is a timely resource. - Outlines a model-based approach (based on Process Systems Engineering-OSE and Computer Aided Process Engineering-CAPE) in quantitative pharmacology - Explains how therapeutics work in the human body and how anatomy and physiology influences drug efficacy - Discusses how drugs are driven to specific targets using nanoparticles - Offers insight into how in vitro and in vivo experiments help understand the drug mechanism of action and optimize their performance - Includes case studies showing the positive outcome of these methods in personalized therapies, therapeutic drug monitoring, clinical trials analysis and drug formulation
Author: Donald E. Mager Publisher: Springer ISBN: 3319445340 Category : Medical Languages : en Pages : 512
Book Description
While systems biology and pharmacodynamics have evolved in parallel, there are significant interrelationships that can enhance drug discovery and enable optimized therapy for each patient. Systems pharmacology is the relatively new discipline that is the interface between these two methods. This book is the first to cover the expertise from systems biology and pharmacodynamics researchers, describing how systems pharmacology may be developed and refined further to show practical applications in drug development. There is a growing awareness that pharmaceutical companies should reduce the high attrition in the pipeline due to insufficient efficacy or toxicity found in proof-of-concept and/or Phase II studies. Systems Pharmacology and Pharmacodynamics discusses the framework for integrating information obtained from understanding physiological/pathological pathways (normal body function system vs. perturbed system due to disease) and pharmacological targets in order to predict clinical efficacy and adverse events through iterations between mathematical modeling and experimentation.
Author: Ronald Gieschke Publisher: Springer Science & Business Media ISBN: 3642397654 Category : Medical Languages : en Pages : 407
Book Description
The development of innovative drugs is becoming more difficult while relying on empirical approaches. This inspired all major pharmaceutical companies to pursue alternative model-based paradigms. The key question is: How to find innovative compounds and, subsequently, appropriate dosage regimens? Written from the industry perspective and based on many years of experience, this book offers: - Concepts for creation of drug-disease models, introduced and supplemented with extensive MATLAB programs - Guidance for exploration and modification of these programs to enhance the understanding of key principles - Usage of differential equations to pharmacokinetic, pharmacodynamic and (patho-) physiologic problems thereby acknowledging their dynamic nature - A range of topics from single exponential decay to adaptive dosing, from single subject exploration to clinical trial simulation, and from empirical to mechanistic disease modeling. Students with an undergraduate mathematical background or equivalent education, interest in life sciences and skills in a high-level programming language such as MATLAB, are encouraged to engage in model-based pharmaceutical research and development.
Author: Babak Sokouti Publisher: Elsevier ISBN: 0443223270 Category : Science Languages : en Pages : 356
Book Description
Systems Biology and In-Depth Applications for Unlocking Diseases: Principles, tools and Application to Disease provides the essence of systems biology approaches in a practical manner, illustrating the basic principles essential to develop and model in real life science applications. Methodologies covered show how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment. Sections provide an introduction and history of systems biology, discuss the tools and resources needed for structure and function of biological systems, and present evidence of systems biology in action. Examples include big data techniques, scale networks, mathematical model development, and much more. This is the perfect reference to provide the fundamental base of knowledge needed for systems biologists, professionals in systems medicine, computational biologists, and bioinformaticians. - Provides detailed and comprehensive coverage of the field of systems biology - Delivers instruction on how to interrogate biological data, with the purpose of obtaining insight about disease diagnosis, prognosis, and treatment - Makes effective steps towards personalized medicine in the treatment of disease - Explains effective disease treatment strategies at early diagnosis stages
Author: Pavel Kraikivski Publisher: Springer Nature ISBN: 3030677427 Category : Science Languages : en Pages : 310
Book Description
This book provides case studies that can be used in Systems Biology related classes. Each case study has the same structure which answers the following questions: What is the biological problem and why is it interesting? What are the relevant details with regard to cell physiology and molecular mechanisms? How are the details put together into a mathematical model? How is the model analyzed and simulated? What are the results of the model? How do they compare to the known facts of the cell physiology? Does the model make predictions? What can be done to extend the model? The book presents a summary of results and references to more relevant sources. The volume contains the classic collection of topics and studies that are well established yet novel in the systems biology field.
Author: Basabdatta Sen Bhattacharya Publisher: Springer ISBN: 3319200372 Category : Medical Languages : en Pages : 329
Book Description
This book is a collection of articles by leading researchers working at the cutting edge of neuro-computational modelling of neurological and psychiatric disorders. Each article contains model validation techniques used in the context of the specific problem being studied. Validation is essential for neuro-inspired computational models to become useful tools in the understanding and treatment of disease conditions. Currently, the immense diversity in neuro-computational modelling approaches for investigating brain diseases has created the need for a structured and coordinated approach to benchmark and standardise validation methods and techniques in this field of research. This book serves as a step towards a systematic approach to validation of neuro-computational models used for studying brain diseases and should be useful for all neuro-computational modellers.
Author: Tarek A. Leil
Author: Tarek A. Leil
Author: Davide Manca
Author: Donald E. Mager
Author: Ronald Gieschke
Author: Yu-Wei Lin
Author: Babak Sokouti
Author: Pavel Kraikivski
Author: Basabdatta Sen Bhattacharya
Author: 
Author: Hong Zhang