Systems Pharmacology And Pharmacodynamics

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.

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.

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

The network approaches of systems pharmacology and toxicology serve as early predictors of the most relevant screening approach to pursue both in drug discovery and development and ecotoxicological assessments. Computational approaches have the potential to improve toxicological experimental design, enable more rapid drug efficacy and safety testing and also reduce the number of animals used in experimentation. Rapid advances in availability of computing technology hold tremendous promise for advancing applied and basic science and increasing the efficiency of risk assessment. This book provides an understanding of the basic principles of computational toxicology and the current methods of predictive toxicology using chemical structures, toxicity-related databases, in silico chemical-protein docking, and biological pathway tools. The book begins with an introduction to systems pharmacology and toxicology and computational tools followed by a section exploring modelling adverse outcomes and events. The second part of the book covers the discovery of protein targets and the characterisation of toxicant-protein interactions. Final chapters include case studies and additionally discuss interactions between phytochemicals and Western therapeutics. This book will be useful for scientists involved in environmental research and risk assessment. It will be a valuable resource for postgraduate students and researchers wishing to learn about key methods used in studying biological targets both from a toxicity and pharmacological activity standpoint.

This volume records the proceedings of the Workshop on Advanced Meth ods of Pharmacokinetic and Pharmacodynamic Systems Analysis, organized by the Biomedical Simulations Resource in May 1990. The meeting brought together over 120 investigators from a number of disciplines, including clinical pharmacology, clinical pharmacy, pharmaceutical science, biomathematics, statistics and biomed ical engineering with the purpose of providing a high-level forum to facilitate the exchange of ideas between basic and clinical research scientists, experimentalists and modelers working on problems in pharmacokinetics and pharmacodynamics. It has been my experience that in many areas of biomedical research, when a meeting of this type is held, the general attitude of those experimentalists willing to attend is one of extreme skepticism: as a group they feel that mathematical modeling has little to offer them in furthering their understanding of the particular biological processes they are studying. This is certainly not the prevailing view when the topic is pharmacokinetics and drug response. Quite the contrary, the use of mathemati cal modeling and associated data analysis and computational methods has been a central feature of pharmacokinetics almost from its beginnings. In fact, the field has borrowed techniques of modeling from other disciplines including applied math ematics, statistics and engineering, in an effort to better describe and understand the processes of drug disposition and drug response.

The state of the art in Biopharmaceutics, Pharmacokinetics, and Pharmacodynamics Modeling is presented in this new second edition book. It shows how advanced physical and mathematical methods can expand classical models in order to cover heterogeneous drug-biological processes and therapeutic effects in the body. The book is divided into four parts; the first deals with the fundamental principles of fractals, diffusion and nonlinear dynamics; the second with drug dissolution, release, and absorption; the third with epirical, compartmental, and stochastic pharmacokinetic models, with two new chapters, one on fractional pharmacokinetics and one on bioequivalence; and the fourth mainly with classical and nonclassical aspects of pharmacodynamics. The classical models that have relevance and application to these sciences are also considered throughout. This second edition has new information on reaction limited models of dissolution, non binary biopharmaceutic classification system, time varying models, and interface models. Many examples are used to illustrate the intrinsic complexity of drug administration related phenomena in the human, justifying the use of advanced modeling methods. This book will appeal to graduate students and researchers in pharmacology, pharmaceutical sciences, bioengineering, and physiology. Reviews of the first edition: "This book presents a novel modelling approach to biopharmaceutics, pharmacokinetics and pharmacodynamic phenomena. This state-of-the-art volume will be helpful to students and researchers in pharmacology, bioengineering, and physiology. This book is a must for pharmaceutical researchers to keep up with recent developments in this field." (P. R. Parthasarathy, Zentralblatt MATH, Vol. 1103 (5), 2007) "These authors are the unique (or sole) contributors in this area that are working on these questions and bring a special expertise to the field that is now being recognized as essential to understanding biological system and kinetic/dynamic characteristics in drug development...This text is an essential primer for those who would envision the incorporation of heterogeneous approaches to systems where homogeneous approaches are not sufficient to describe the system." (Robert R. Bies, Journal of Clinical Pharmacology, Vol. 46, 2006)

With an emphasis on the fundamental and practical aspects of ADME for therapeutic proteins, this book helps readers strategize, plan and implement translational research for biologic drugs. • Details cutting-edge ADME (absorption, distribution, metabolism and excretion) and PKPD (pharmacokinetic / pharmacodynamics) modeling for biologic drugs • Combines theoretical with practical aspects of ADME in biologic drug discovery and development and compares innovator biologics with biosimilar biologics and small molecules with biologics, giving a lessons-learned perspective • Includes case studies about leveraging ADME to improve biologics drug development for monoclonal antibodies, fusion proteins, pegylated proteins, ADCs, bispecifics, and vaccines • Presents regulatory expectations and industry perspectives for developing biologic drugs in USA, EU, and Japan • Provides mechanistic insight into biodistribution and target-driven pharmacokinetics in important sites of action such as tumors and the brain

PKPD awareness is vital if we are to attempt to relate preclinical results to the acute and long term consequences in humans. The debate on whether preclinical findings can be translated to the human usage is still engaging scientists across industry, academia and regulatory bodies. Pharmacokinetics (PK) and pharmacodynamics (PD) comprise traditionally distinct disciplines within pharmacology, the study of the interaction of drugs with the body. It is our intention to show that by deliberately, intimately and systematically integrate these disciplines our understanding of drugs and the efficiency and effectiveness of drug discovery and development may be greatly enhanced. The book is therefore written with a broad audience in mind and focuses on concepts. Pharmacologists of all sorts, safety scientists, pharmacokineticists, medicinal chemists, clinicians, statisticians, veterinarians, animal science professionals, project leaders and students of medical, pharmaceutical and veterinary sciences are the primary targets. This textbook Introduces the basics of PK and PD concepts Outlines the implications of integrating PK and PD analysis Introduces the principles behind different biomarkers and inter-species scaling Discusses experimental design of PK, PD and safety studies in non-human species Covers numerous real life Case Studies from the drug discovery arena