Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications

The importance of pharmacokinetics(PK) and pharmacodynamics(PD) in drug development is becoming increasingly recognized and now permeates the program from preclinical development through Phase IV clinical trials.1-2 However, PK/PD data is generally very noisy and sophisticated data analysis techniques must be used to estimate parameters of interest. Modern PK/PD has developed into a relatively sophisticated mathematical discipline. Scientists involved with PK/PD data are dependent on the availability of sophisticated software packages. Despite the lack of a complete understanding of the methodology, the user of such packages needs to be convinced of their accuracy and reliability. It is incumbent on the PK/PD scientists to obtain a reasonable understanding of the methodology behind a software package to correctly interpret the output and diagnostics.3 However, until now there has been very little literature available that explains, in simple terms, how to fit models and interpret output data. Anyone desiring a single definitive source of information on PK/PD modeling should consider Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications. It is an extraordinary book covering virtually all mathematical and conceptual perspectives inherent within the PK/PD modeling process. It provides an introduction into PK/PD concepts using simple illustrations, and differentiates itself from other texts in this area in that it bridges the gap between relevant theory and the actual application of theory to real life situations.4 The fourth edition continues the central thesis of the first 3 editions: How do we go from kinetic and dynamic data to insight in the most effective way? This edition is the fourth in an evolution of the original text published in 1994 and has been expanded to over 1200 pages, mirroring the growth of the subject over the last decade. It is also a testament to the increasing sophistication of PK/PD analyses being undertaken by scientists working in the drug discovery/development arena. The new edition contains many new case studies, but also includes an extension of the experimental design chapter. This book emphasizes how to critically evaluate the output from fitting a model to data to applying statistical techniques for model selection and discussion. Chapters 1 to 6 make up the concepts section of the book, and the case studies make up the applications section. The concepts section provides a basic introduction to PK/PD modeling principles. Chapter 1 briefly introduces the general principles and the book's contents. Chapter 2 emphasizes various aspects of pharmacokinetics, including one- and multi-compartment systems, absorption and disposition kinetics, clearance concepts, turnover, nonlinearities, non-compartmental analysis, exposure assessment, and inter-species scaling. Chapter 3 presents an extensive library of basic and mechanistic pharmacodynamic models, including receptor binding models, pharmacodynamic models, kinetics of drug actions, interaction models, effect compartment models, turnover models, dose-response-time data analysis, tolerance and rebound models, and transduction models. Chapter 4 provides an overview of parameter estimates, including criteria for best fit, search algorithms, and weighing. Chapter 5 is placed intentionally after the pharmacokinetics and pharmacodynamics chapters, and covers general modeling strategies. Chapter 6 contains a brief discussion of design elements, including tools for experimental design, and general design issues of kinetic/dynamic studies. The applications section of the book illustrates the application of concepts to specific modeling situations commonly encountered in the drug industry and in research laboratories. More than 100 data sets and practical solutions are included. Several new exciting data sets on tolerance-rebound, dose-response-time models, bacterial growth model, turnover, non-linear kinetics, oscillating input functions, and toxicokinetics are also solved and discussed in this section. The book has several key strengths. First, and perhaps most important, this book bridges the gap between standard texts in pharmacokinetics, pharmacology, and numerical analysis, and provides unique insight into the field of pharmacometrics in a manner that is easy to understand. Complex mathematics is minimized, and extensive graphical presentations accompany the theory, which enables the scientist with little formal training in this area to conceptualize the underlying principles. The second major strength is that, in addition to its clear and straightforward presentation of methodology, this book also includes a CD with all application examples and WinNonlin (Pharsight, St. Louis, MO) command files. The command files are intended both as a complement to the book and as a framework for the user's own modeling problems, thereby saving time when carrying out data analysis. Many thoughts and ideas presented in the book have evolved from the authors' own practice and teaching experiences, while observing and evaluating students' work. Thus, some of the theories have been formulated to help students overcome common mistakes and misconceptions typical among kineticists and junior modelers. Therefore, another important strength is that the book can also serve to remedy the most common dysfunctions of a modeler, including lack of experience with exploratory data analysis, too much trust in the modeling software, weighting away data, slavery under formulas, and lack of holistic view of the analysis-modeling process.5 This book is both a valuable introductory text for new researchers and a useful reference for established scientists. In addition, it is a useful reference for a variety of undergraduate and graduate courses in PK/PD. Overall, we believe that this book is an essential resource for anyone wanting to gain a better understanding and awareness of the modeling carousel.