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<p>Concepts and Principles of Clinical Data Graphics.- Graphics for Exploratory Analysis and Data Discovery in the Life Sciences.- Grables: Visual Displays That Combine the Best Attributes of Graphs and Tables.- The Use of Figures in Epidemiological Publications: A Survey of Current Practice and Consequent Recommendations.- Use of Graphics for Studies with Small Sample Sizes: A Simulated Case Study of an Early-Phase Asset for Treatment of Type 2 Diabetes Mellitus (T2DM).- Exploring Pharmacokinetic and Pharmacodynamic Data.- (Interactive) Graphics for Biomarker Assessment.- Graphical Displays for Biomarker Data.- Statistical Graphics in Clinical Oncology.- Efficient and Effective Review of Clinical Trial Data Safety Using Interactive Graphs and Tables.- Visualizing Dose-Response when the Signal to Noise Ratio is Low: The Bronchodilatory Response in Chronic Obstructive Pulmonary Disease.- Statistical Graphics in Late-Stage Drug Development.- Graphical Data Exploration in QT Model Building and Cardiovascular Drug Safety.- Data Visualization at the Individual Patient Level.- Graphics for Meta-Analysis.- Visualization of QT Data for Thorough QT Study Analysis and Review.- Graphics for Safety Analysis.- Cardiac Safety.- Data Visualization for Clinical Trials Data Management and Operations.- Post-Approval Uses of Clinical Data, Phase IV Data, and Sales &amp; Marketing Data Visualizations.- Using Exploratory Visualization in the Analysis of Medical Product Safety in Observational Healthcare Data.</p>

<b>Andreas Krause</b><p>Andreas Krause has 20 years of experience in the pharmaceutical industry. Holding a PhD in statistics and econometrics, his areas of expertise include modeling and simulation, also known as pharmacometrics, biostatistics and bioinformatics. He is director and lead scientist modeling and simulation in the department of clinical pharmacology at Actelion Pharmaceuticals Ltd in Allschwil, Switzerland.</p><p>Graphics and visualization are a key element of his work as evidenced by a multitude of presentations and workshops. Recent publications include <i>Interactive Visualization of Modeling Results for Effective Team Communication and Decision Making</i> and <i>Visualization Concepts for Modeling and Simulation</i> (the former with Ronald Gieschke, the latter with Kevin Dykstra and Richard Pugh), both in the Journal of Clinical Pharmacology, 50(9), 2010.</p><p>Andreas Krause is co-author of <i>The Basics of S-Plus</i> (with Melvin Olson, Springer-Verlag, 1997-2005) and co-editor of <i>Applied Statistics in the Pharmaceutical Industry</i> (with Steve Millard, Springer-Verlag, 2001).</p><p> <b>Michael O’Connell</b></p><p>Michael O'Connell leads the Industry Analytics Group at TIBCO Software, developing analytic solutions across a number of industries including Life Sciences, Financial Services, Energy, Consumer Goods &amp; Retail, and Telco, Media &amp; Networks. He has been working on statistical software applications for the past 20 years, and has published more than 50 papers and several software packages on statistical methods. Michael has been particularly active in developing statistical graphics applications for review and reporting in clinical development, as has received several industry awards for his work in Life Sciences including recently being voted in the <i>Top 100 Inspiring People in the Pharmaceutical Industry</i>.  Michael did his Ph.D. work in Statistics at North Carolina State University and is an Adjunct Professor Statistics in the department.</p>

<p>Graphics promote scientific insight, better business and more effective communication. However, in the Life Sciences, drug development processes are still largely reliant on tables and listings.</p><p>This book sets out to change this situation. The primary aim of the volume is to provide a rich collection of examples showing graphical review and reporting across the Life Sciences industry. Medical researchers and investigators will find many applications that can be applied to their own work. The code for many of the graphs is available on the companion web page, so that analysts can implement them directly. Statisticians and modelers will find graphics that support the exploratory analysis and the model building process as well as effective communication of results. Pharmacologists and pharmacokineticists will find a variety of graph types to display longitudinal data and explore its information.</p><p>A variety of therapy areas are covered, including diabetes, hypertension, oncology, pulmonology and neurology. ECG and TQT data analysis is treated in detail and concepts for efficacy and safety data analysis are shown along with examples of grables, a combination of graphics and tables. Graphics for individual patient data, meta analysis, biomarker and genetic data, health economics, safety and pharmacovigilance, development operations and sales and marketing data, complete the diversity of applications.</p><p>The book contains contributions from about 40 eminent researchers in the field, including a foreword by Professor Stuart Pocock.</p>

<p>Devoted to the graphics of patient data</p><p>Introduces general principles of good visualization to make readers understand the concepts, but the main focus is on the creativity and usefulness</p><p>Large number of color illustrations</p>

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