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Very little has been published on optimization of pharmaceutical
portfolios. Moreover, most of published literature is coming from
the commercial side, where probability of technical success (PoS)
is treated as fixed, and not as a consequence of development
strategy or design. In this book there is a strong focus on impact
of study design on PoS and ultimately on the value of portfolio.
Design options that are discussed in different chapters are
dose-selection strategies, adaptive design and enrichment. Some
development strategies that are discussed are indication
sequencing, optimal number of programs and optimal decision
criteria. This book includes chapters written by authors with very
broad backgrounds including financial, clinical, statistical,
decision sciences, commercial and regulatory. Many authors have
long held executive positions and have been involved with decision
making at a product or at a portfolio level. As such, it is
expected that this book will attract a very broad audience,
including decision makers in pharmaceutical R&D, commercial and
financial departments. The intended audience also includes
portfolio planners and managers, statisticians, decision scientists
and clinicians. Early chapters describe approaches to portfolio
optimization from big Pharma and Venture Capital standpoints. They
have stronger focus on finances and processes. Later chapters
present selected statistical and decision analysis methods for
optimizing drug development programs and portfolios. Some
methodological chapters are technical; however, with a few
exceptions they require a relatively basic knowledge of statistics
by a reader.
Platform trials test multiple therapies in one indication, one
therapy for multiple indications, or both. These novel clinical
trial designs can dramatically increase the cost-effectiveness of
drug development, leading to life-altering medicines for people
suffering from serious illnesses, possibly at lower cost.
Currently, the cost of drug development is unsustainable.
Furthermore, there are particular problems in rare diseases and
small biomarker defined subsets in oncology, where the required
sample sizes for traditional clinical trial designs may not be
feasible. The editors recruited the key innovators in this domain.
The 20 articles discuss trial designs from perspectives as diverse
as quantum computing, patient's rights to information, and
international health. The book begins with an overview of platform
trials from multiple perspectives. It then describes impacts of
platform trials on the pharmaceutical industry's key stakeholders:
patients, regulators, and payers. Next it provides advanced
statistical methods that address multiple aspects of platform
trials, before concluding with a pharmaceutical executive's
perspective on platform trials. Except for the statistical methods
section, only a basic qualitative knowledge of clinical trials is
needed to appreciate the important concepts and novel ideas
presented.
Platform trials test multiple therapies in one indication, one
therapy for multiple indications, or both. These novel clinical
trial designs can dramatically increase the cost-effectiveness of
drug development, leading to life-altering medicines for people
suffering from serious illnesses, possibly at lower cost.
Currently, the cost of drug development is unsustainable.
Furthermore, there are particular problems in rare diseases and
small biomarker defined subsets in oncology, where the required
sample sizes for traditional clinical trial designs may not be
feasible. The editors recruited the key innovators in this domain.
The 20 articles discuss trial designs from perspectives as diverse
as quantum computing, patient's rights to information, and
international health. The book begins with an overview of platform
trials from multiple perspectives. It then describes impacts of
platform trials on the pharmaceutical industry's key stakeholders:
patients, regulators, and payers. Next it provides advanced
statistical methods that address multiple aspects of platform
trials, before concluding with a pharmaceutical executive's
perspective on platform trials. Except for the statistical methods
section, only a basic qualitative knowledge of clinical trials is
needed to appreciate the important concepts and novel ideas
presented.
Very little has been published on optimization of pharmaceutical
portfolios. Moreover, most of published literature is coming from
the commercial side, where probability of technical success (PoS)
is treated as fixed, and not as a consequence of development
strategy or design. In this book there is a strong focus on impact
of study design on PoS and ultimately on the value of portfolio.
Design options that are discussed in different chapters are
dose-selection strategies, adaptive design and enrichment. Some
development strategies that are discussed are indication
sequencing, optimal number of programs and optimal decision
criteria. This book includes chapters written by authors with very
broad backgrounds including financial, clinical, statistical,
decision sciences, commercial and regulatory. Many authors have
long held executive positions and have been involved with decision
making at a product or at a portfolio level. As such, it is
expected that this book will attract a very broad audience,
including decision makers in pharmaceutical R&D, commercial and
financial departments. The intended audience also includes
portfolio planners and managers, statisticians, decision scientists
and clinicians. Early chapters describe approaches to portfolio
optimization from big Pharma and Venture Capital standpoints. They
have stronger focus on finances and processes. Later chapters
present selected statistical and decision analysis methods for
optimizing drug development programs and portfolios. Some
methodological chapters are technical; however, with a few
exceptions they require a relatively basic knowledge of statistics
by a reader.
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