This book focuses on the new discipline of translational medicine as it pertains to drug development within the pharmaceutical and biotechnology industry. It is essential for anyone interested in translational medicine from a variety of backgrounds: university institutes, medical schools, pharmaceutical companies and drug development researchers and decision-makers.

This book acquaints students and practitioners in the related fields of pharmaceutical sciences, clinical trials, and evidence-based medicine with the necessary study design concepts and statistical practices to allow them to understand how drug developers plan and evaluate their drug development. Two goals of the book are to make the material accessible to readers with minimal background in research and to be straightforward enough for self-taught purposes. By bringing the topic from the early discovery phase to clinical trials and medical practice, the book provides an indispensable overview of an otherwise confusing and fragmented set of topics. The author’s experience as a respected scientist, teacher of statistics, and one who has worked in the clinical trials arena makes him well suited to write such a treatise.

Essentials of Translational Pediatric Drug Development: From Past Needs to Future Opportunities provides integrated and up-to-date insights relevant for both translational researchers and clinicians active in the field of pediatric drug development. The book covers all key aspects from different stakeholder perspectives, providing a literature overview and careful reflection on state-of-the-art approaches. It will be an ideal guide for researchers in the field who are designing and performing high quality, innovative pediatric-adapted drug development by helping them define needs/challenges and possible solutions that advance and harmonize pediatric drug development.Despite the broad consensus that children merit the same quality of drug treatment as any other age group, children remain frequently neglected during drug research and development. Even with the adoption of multiple legislations addressing this problem, the lack of efficacy and safety data of marketed as well as newly developed drugs still remain in the pediatric population. Covers both theoretical and practical aspects of translational pediatric drug development Approaches the topic from different stakeholder perspectives (academics, industry, regulators, clinicians and patient/parent advocacy groups) Offers best practices and future perspectives for the improvement of translational pediatric drug development

This book concerns use of real world data (RWD) and real world evidence (RWE) to aid drug development across product cycle. RWD are healthcare data that are collected outside the constraints of conventual controlled randomized trials (CRTs); whereas RWE is the knowledge derived from aggregation and analysis of RWD.

Computational Approaches in Drug Discovery, Development and Systems Pharmacology provides detailed information on the use of computers in advancing pharmacology. Drug discovery and development is an expensive and time-consuming practice, and computer-assisted drug design (CADD) approaches are increasing in popularity in the pharmaceutical industry to accelerate the process. With the help of CADD, scientists can focus on the most capable compounds so that they can minimize the synthetic and biological testing pains. This book examines success stories of CADD in drug discovery, drug development and role of CADD in system pharmacology, additionally including a focus on the role of artificial intelligence (AI) and deep machine learning in pharmacology. Computational Approaches in Drug Discovery, Development and Systems Pharmacology will be useful to researchers and academics working in the area of CADD, pharmacology and Bioinformatics. Explains computer use in pharmacology using real-life case studies Provides information about biological activities using computer technology, thus allowing for the possible reduction of the number of animals used for research Describes the role of AI in pharmacology and applications of CADD in various diseases

Theory of Drug Development presents a formal quantitative framework for understanding drug development that goes beyond simply describing the properties of the statistics in individual studies. It examines the drug development process from the perspectives of drug companies and regulatory agencies. By quantifying various ideas underlying drug development, the book shows how to systematically address problems, such as: Sizing a phase 2 trial and choosing the range of p-values that will trigger a follow-up phase 3 trial Deciding whether a drug should receive marketing approval based on its phase 2/3 development program and recent experience with other drugs in the same clinical area Determining the impact of adaptive designs on the quality of drugs that receive marketing approval Designing a phase 3 pivotal study that permits the data-driven adjustment of the treatment effect estimate Knowing when enough information has been gathered to show that a drug improves the survival time for the whole patient population Drawing on his extensive work as a statistician in the pharmaceutical industry, the author focuses on the efficient development of drugs and the quantification of evidence in drug development. He provides a rationale for underpowered phase 2 trials based on the notion of efficiency, which leads to the identification of an admissible family of phase 2 designs. He also develops a framework for evaluating the strength of evidence generated by clinical trials. This approach is based on the ratio of power to type 1 error and transcends typical Bayesian and frequentist statistical analyses.