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Quantitative Decisions in Drug Development (Hardcover, 2nd ed. 2021)
Loot Price: R2,468
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Quantitative Decisions in Drug Development (Hardcover, 2nd ed. 2021)
Series: Springer Series in Pharmaceutical Statistics
Expected to ship within 12 - 17 working days
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This book focuses on important decision points and evidence needed
for making decisions at these points during the development of a
new drug. It takes a holistic approach towards drug development by
incorporating explicitly knowledge learned from the earlier part of
the development and available historical information into decisions
at later stages. In addition, the book shares lessons learned from
several select examples published in the literature since the
publication of the first edition. The second edition reiterates the
need for making evidence-based Go/No Go decisions in drug
development discussed in the first edition. It substantially
expands several topics that have seen great advances since the
publication of the first edition. The most noticeable additions
include three adaptive trials conducted in recent years that offer
excellent learning opportunities, the use of historical data in the
design and analysis of clinical trials, and extending decision
criteria to the cases when the primary endpoint is binary. The
examples used to illustrate the additional materials all come from
real trials with some post-trial reflections offered by the
authors. The book begins with an overview of product development
and regulatory approval pathways. It then discusses how to
incorporate prior knowledge into study design and decision making
at different stages of drug development. Prior knowledge includes
information pertaining to historical controls. To assist decision
making, the book discusses appropriate metrics and the formulation
of go/no-go decisions for progressing a drug candidate to the next
development stage. Using the concept of the positive predictive
value in the field of diagnostics, the book leads readers to the
assessment of the probability that an investigational product is
effective given positive study outcomes. Lastly, the book points
out 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 a basic
understanding of the drug-development process and the clinical
trials conducted to support drug-marketing authorization. The
authors provide software codes for select analytical approaches
discussed in the book. The book includes enough technical details
to allow statisticians to replicate the quantitative illustrations
so that they can generate information to facilitate decision-making
themselves.
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