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This is a second edition to the original published by Springer in 2006. The comprehensive volume takes a textbook approach systematically developing the field by starting from linear models and then moving up to generalized linear and non-linear mixed effects models. Since the first edition was published the field has grown considerably in terms of maturity and technicality. The second edition of the book therefore considerably expands with the addition of three new chapters relating to Bayesian models, Generalized linear and nonlinear mixed effects models, and Principles of simulation. In addition, many of the other chapters have been expanded and updated.
- Sales Rank: #368961 in Books
- Published on: 2011-07-01
- Original language: English
- Number of items: 1
- Dimensions: 10.75" h x 8.00" w x 1.75" l, 3.45 pounds
- Binding: Hardcover
- 618 pages
From the Back Cover
Since its publication in 2006, Pharmacokinetic-Pharmacodynamic Modeling and Simulation has become the leading text on modeling of pharmacokinetic and pharmacodynamic data using nonlinear mixed effects models and has been applauded by students and teachers for its readability and exposition of complex statistical topics. Using a building block approach, the text starts with linear regression, nonlinear regression, and variance models at the individual level and then moves to population-level models with linear and nonlinear mixed effects models. Particular emphasis is made highlighting relationships between the model types and how the models build upon one another.
With the second edition, new chapters on generalized nonlinear mixed effects models and Bayesian models are presented, along with an extensive chapter on simulation. In addition, many chapters have been updated to reflect recent developments. The theory behind the methods is illustrated using real data from the literature and from the author's experiences in drug development. Data are analyzed using a variety of software, including NONMEM, SAS, SAAM II, and WinBUGS. A key component of the book is to show how models are developed using an acceptance-rejection paradigm with the ultimate goal of using models to explain data, summarize complex experiments, and use simulation to answer "what-if" questions. Scientists and statisticians outside the pharmaceutical sciences will find the book invaluable as a reference for applied modeling and simulation.
About the Author
Peter Bonate has 16 years industrial experience, 13 years as a clinical pharmacologist/pharmacokineticist and three years in drug metabolism and bioanalysis. He is currently a Director in the Clinical Pharmacology, Modeling, and Simulation department at GlaxoSmithKline in the oncology and rare diseases therapeutic areas. He has worked at Genzyme, Hoechst Marion Roussel, Eli Lilly, and Quintiles. He received his PhD in 1996 from Indiana University in Medical Neurobiology with an emphasis on the pharmacokinetics of drugs of abuse. He received an MS in statistics from the University of Idaho and an MS in Pharmacology from Washington State University, both in 1990. In 2003 he was elected a Fellow of the American College of Clinical Pharmacology and in 2007 was elected a fellow of the American Association of Pharmaceutical Scientists (AAPS). He was founder of the Modeling and Simulation focus group, has served as chair of the population pharmacokinetics focus group, and was the Clinical Pharmacology and Translational Research Section Chair within AAPS. He has served or currently serves on the editorial boards for the Journal of Clinical Pharmacology, Pharmaceutical Research, Journal of Pharmacokinetics and Pharmacodynamics, and The AAPS Journal. He has more than 50 publications in the field of pharmacokinetics and clinical pharmacology, is co-editor of the 3-volume series Pharmacokinetics in Drug Development published by AAPS Press in 2004 and 2011, and is author of the book Pharmacokinetic-Pharmacodynamic Modeling and Simulation published by Springer in 2006. In 2010, he became an Adjunct Assistant Professor at the Indiana University School of Medicine and the University of North Carolina, Chapel Hill.
Most helpful customer reviews
1 of 1 people found the following review helpful.
Kudos!
By Richard Reeves
This is a remarkable book - a single-author monograph covering a difficult and large field. Dr Bonate has the industry experience to write authoritatively about real problems in PK/PD modeling, and includes a few valuable examples that delve deeply into the problems that will be encountered in real projects. Overall, I recommend this to anyone willing to do the work to read it.
Complaints are minor, and feel a bit unfair to even mention. Firstly, the book could have used an editor. A few sections are a bit off-topic (for example, a tour of ECGs with misinformation about lead nomenclature, multiple typos and some grammatical errors/imprecision, use of abbreviations before they are defined (common with cut/paste during revision), and an absolutely dreadful index - typical of modern-day books in the technical medical arena - use the ToC to find things instead. Dr Bonate has a spectacular grasp of mathematics compared with this reviewer (an MD and physicist by background) - very few medical people will be able to keep up with the theoretical presentations. Statisticians will probably be ok with the assumed knowledge base, PK people perhaps... But he makes a good effort at helping guide the reader, if diligent, through arcana and traps alike, freely offering very valuable tips and rules of thumb of the sort that can only be gleaned by suffering through simulations and fittings. I would have appreciated a few more simple examples first, before delving into things like 'Generation of Weibull Random Variates', just to pull a (random) example - but for advanced practitioners, the deep-dives may be the most valuable aspect.
I personally found the book interesting enough to read it cover to cover, and appreciated the human touch in the Preface that captured some of the immense effort this must have been to complete. In summary, for anyone really serious about trying to understand and contribute to PK/PD analysis, this is an excellent book to own and consult frequently.
1 of 1 people found the following review helpful.
Book with a great chapter about modeling
By C. Gelmi
I have been teaching modeling and simulation for several years. By itself, Chapter 1: "The Art of Modeling", is simply an excellent overview of the topic; and not only applies to pharmacokinetic-pharmacodynamic modeling, but to modeling in general. It covers the usual suspects: what is a model, types of models, properties of a useful model, model development process, goodness-of-fit criteria and metrics, and model validation. Furthermore, gives a good introduction to subtle but important topics, such as: model discrimination criteria (AIC, F-test, etc.), identifiability of compartmental models, importance of effective communication and ethics in modeling. I have not gone through the details in all the other chapters, but given my good impression based in Chapter 1, I am sure that this textbook will become a must read to any serious modeler in the field of pharmacokinetic-pharmacodynamic.
0 of 3 people found the following review helpful.
Great book for entry level PK/PD students
By Jing Wang
The author is well-known in the PK/PD modeling field. It is a reader-friendly book. It is very easy to understand. You would not be bored by the terminology. The author explained the theory and ideas by the simplest words. Actually, it is a very fun book. You are just like reading a story, not a boring science book.
This book is for students/professionals with adequate backgroup of PK/PD, math and statistics. It is especially useful for an entry level modeler or future modeler.
I love this book.
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