This book offers a high-level review of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to clinical-trial methodology. It includes an overview of possible deviations from the traditional development plan and new regulatory approval pathways. It also discusses how to select appropriate metrics to formulate decisions criteria, determine go/no-go decisions for progressing a drug candidate to…
This book offers a high-level review of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to clinical-trial methodology. It includes an overview of possible deviations from the traditional development plan and new regulatory approval pathways. It also discusses how to select appropriate metrics to formulate decisions criteria, determine go/no-go decisions for progressing a drug candidate to the next stage and predict the effectiveness of a product. Lastly, it includes common mistakes made by drug developers under the current drug-development paradigm.
The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have an understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization.
The authors provide software solutions for the analytical approaches discussed, and the book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making.
This book offers a high-level review of evidence-based decisions in drug development. Because of the inseparable relationship between designs and decisions, a good portion of this book is devoted to clinical-trial methodology. It includes an overview of possible deviations from the traditional development plan and new regulatory approval pathways. It also discusses how to select appropriate metrics to formulate decisions criteria, determine go/no-go decisions for progressing a drug candidate to the next stage and predict the effectiveness of a product. Lastly, it includes common mistakes made by drug developers under the current drug-development paradigm.
The book offers useful insights to statisticians, clinicians, regulatory affairs managers and decision-makers in the pharmaceutical industry who have an understanding of the drug-development process and the clinical trials conducted to support drug-marketing authorization.
The authors provide software solutions for the analytical approaches discussed, and the book includes enough technical details to allow statisticians to replicate the quantitative illustrations so that they can generate information to facilitate decision-making.
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