Covers the latest research on a sensitive and controversial topic in a professional and well researched manner.

Provides practical outlook as well as model guidelines and software tools that should be of interest to people who use the software tools described and those who do not.

Related title by Co-author Geert Molenbergh has sold more than 3500 copies world wide.

Provides dual viewpoints: from scientists in the industry as well as regulatory authorities.

Phase I trials are a critical first step in the study of novel therapeutic approaches. They follow years of development in the laboratory, and precede Phase II and III trials where testing of the drug becomes more focused yet is conducted on a wider scale. The primary goals of Phase I trials are to identify the recommended dose, schedule and pharmacologic behaviour of new agents or new combinations of agents, and to describe the adverse effects of treatment. In cancer therapeutics, such studies have particular challenges. In general, because of the nature of the effects of treatment, most studies are conducted in patients with advanced malignancy, rather than in healthy volunteers. Furthermore, the endpoints of these trials are usually measures of adverse effects, but increasingly investigators are interested in assessment of the effects of new drugs on their molecular target. These factors render the design, conduct, analysis and ethical aspects of Phase I cancer clinical trials unique. This book provides a practical guide to Phase I cancer trials and is appropriate for oncology trainees or specialists interested in understanding cancer drug development. Topics covered include preclinical requirements needed for first-in-man investigation of new agents, principles and statistical design, ethical considerations of Phase I studies, pharmacokinetics, pharmacodynamics, and studies in special populations. Practical information on protocol development, study activation and conduct, as well as how to write reports of the results, are incorporated. Numerous appendices offer document templates to use in Phase I study development, and examples from actual Phase I trials are interspersed throughout, making this a true 'hands-on' guide. In an exciting time in cancer research, as the number and type of new potential anti-cancer drugs is increasing dramatically, this book provides much needed information on the first stage in getting a drug approved.

Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming their clinical utility in randomized clinical trials. The foundation of modern clinical trials was laid many years before modern developments in biotechnology and genomics. Drug development in many diseases is now shifting to molecularly targeted treatment. Confronted with such a major break in the evolution toward personalized or predictive medicine, the methodologies for design and analysis of clinical trials is now evolving. This book is one of the first attempts to contribute to this evolution by laying a foundation for the use of appropriate statistical designs and methods in future clinical trials for predictive medicine. It is a useful resource for clinical biostatisticians, researchers focusing on predictive medicine, clinical investigators, translational scientists, and graduate biostatistics students.

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment's efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate endpoint that can be measured in a more convenient or cost-effective way. This book focuses on the use of surrogate endpoint evaluation methods in practice, using SAS and R.

Phase I trials are a critical first step in the study of novel cancer therapeutic approaches. Their primary goals are to identify the recommended dose, schedule and pharmacologic behavior of new agents or new combinations of agents and to describe the adverse effects of treatment. In cancer therapeutics, such studies have particular challenges. Due to the nature of the effects of treatment, most such studies are conducted in patients with advanced malignancy, rather than in healthy volunteers. Further, the endpoints of these trials are usually measures adverse effects rather than molecular target or anti-tumor effects. These factors render the design, conduct, analysis and ethical aspects of phase I cancer trials unique. As the only comprehensive book on this topic, Phase I Cancer Clinical Trials is a useful resource for oncology trainees or specialists interested in understanding cancer drug development. New to this edition are chapters on Phase 0 Trials and Immunotherapeutics, and updated information on the process, pitfalls, and logistics of Phase I Trials

Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming their clinical utility in randomized clinical trials. The foundation of modern clinical trials was laid many years before modern developments in biotechnology and genomics. Drug development in many diseases is now shifting to molecularly targeted treatment. Confronted with such a major break in the evolution toward personalized or predictive medicine, the methodologies for design and analysis of clinical trials is now evolving. This book is one of the first attempts to contribute to this evolution by laying a foundation for the use of appropriate statistical designs and methods in future clinical trials for predictive medicine. It is a useful resource for clinical biostatisticians, researchers focusing on predictive medicine, clinical investigators, translational scientists, and graduate biostatistics students.

An important factor that affects the duration, complexity and cost of a clinical trial is the endpoint used to study the treatment's efficacy. When a true endpoint is difficult to use because of such factors as long follow-up times or prohibitive cost, it is sometimes possible to use a surrogate endpoint that can be measured in a more convenient or cost-effective way. This book focuses on the use of surrogate endpoint evaluation methods in practice, using SAS and R.